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Cryptocurrency is an abject disaster

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This post is long overdue. Let’s get it over with.

🛑 Hey! If you write a comment about this article online, disclose your stake in cryptocurrency. I will explain why later in this post. For my part, I held <$10,000 USD worth of Bitcoin prior to 2016, plus small amounts of altcoins. I made a modest profit on my holdings. Today my stake in all cryptocurrency is $0.

Starting on May 1st, users of sourcehut’s CI service will be required to be on a paid account, a change which will affect about half of all builds.sr.ht users.1 Over the past several months, everyone in the industry who provides any kind of free CPU resources has been dealing with a massive outbreak of abuse for cryptocurrency mining. The industry has been setting up informal working groups to pool knowledge of mitigations, communicate when our platforms are being leveraged against one another, and cumulatively wasting thousands of hours of engineering time implementing measures to deal with this abuse, and responding as attackers find new ways to circumvent them.

Cryptocurrency has invented an entirely new category of internet abuse. CI services like mine are not alone in this struggle: JavaScript miners, botnets, and all kinds of other illicit cycles are being spent solving pointless math problems to make money for bad actors. Some might argue that abuse is inevitable for anyone who provides a public service — but prior to cryptocurrency, what kind of abuse would a CI platform endure? Email spam? Block port 25. Someone might try to host their website on ephemeral VMs with dynamic DNS or something, I dunno. Someone found a way of monetizing stolen CPU cycles directly, so everyone who offered free CPU cycles for legitimate use-cases is now unable to provide those services. If not for cryptocurrency, these services would still be available.

Don’t make the mistake of thinking that these are a bunch of script kiddies. There are large, talented teams of engineers across several organizations working together to combat this abuse, and they’re losing. A small sample of tactics I’ve seen or heard of include:

  • Using CPU limiters to manipulate monitoring tools.
  • Installing crypto miners into the build systems for free software projects so that the builds appear legitimate.
  • Using password dumps to steal login credentials for legitimate users and then leveraging their accounts for mining.

I would give more examples, but secrecy is a necessary part of defending against this — which really sucks for an organization that otherwise strives to be as open and transparent as sourcehut does.

Cryptocurrency problems are more subtle than outright abuse, too. The integrity and trust of the entire software industry has sharply declined due to cryptocurrency. It sets up perverse incentives for new projects, where developers are no longer trying to convince you to use their software because it’s good, but because they think that if they can convince you it will make them rich. I’ve had to develop a special radar for reading product pages now: a mounting feeling of dread as a promising technology is introduced while I inevitably arrive at the buried lede: it’s more crypto bullshit. Cryptocurrency is the multi-level marketing of the tech world. “Hi! How’ve you been? Long time no see! Oh, I’ve been working on this cool distributed database file store archive thing. We’re doing an ICO next week.” Then I leave. Any technology which is not an (alleged) currency and which incorporates blockchain anyway would always work better without it.

There are hundreds, perhaps thousands, of cryptocurrency scams and ponzi schemes trussed up to look like some kind of legitimate offering. Even if the project you’re working on is totally cool and solves all of these problems, there are 100 other projects pretending to be like yours which are ultimately concerned with transferring money from their users to their founders. Which one are investors more likely to invest in? Hint: it’s the one that’s more profitable. Those promises of “we’re different!” are always hollow anyway. Remember the DAO? They wanted to avoid social arbitration entirely for financial contracts, but when the chips are down and their money was walking out the door, they forked the blockchain.

That’s what cryptocurrency is all about: not novel technology, not empowerment, but making money. It has failed as an actual currency outside of some isolated examples of failed national economies. No, cryptocurrency is not a currency at all: it’s an investment vehicle. A tool for making the rich richer. And that’s putting it nicely; in reality it has a lot more in common with a Ponzi scheme than a genuine investment. What “value” does solving fake math problems actually provide to anyone? It’s all bullshit.

And those few failed economies whose people are desperately using cryptocurrency to keep the wheel of their fates spinning? Those make for a good headline, but how about the rural communities whose tax dollars subsidized the power plants which the miners have flocked to? People who are suffering blackouts as their power is siphoned into computing SHA-256 as fast as possible while dumping an entire country worth of CO₂ into the atmosphere?2 No, cryptocurrency does not help failed states. It exploits them.

Even those in the (allegedly) working economies of the first world have been impacted by cryptocurrency. The price of consumer GPUs have gone sharply up in the past few months. And, again, what are these GPUs being used for? Running SHA-256 in a loop, as fast as possible. Rumor has it that hard drives are up next.

Maybe your cryptocurrency is different. But look: you’re in really poor company. When you’re the only honest person in the room, maybe you should be in a different room. It is impossible to trust you. Every comment online about cryptocurrency is tainted by the fact that the commenter has probably invested thousands of dollars into a Ponzi scheme and is depending on your agreement to make their money back.3 Not to mention that any attempts at reform, like proof-of-stake, are viciously blocked by those in power (i.e. those with the money) because of any risk it poses to reduce their bottom line. No, your blockchain is not different.

Cryptocurrency is one of the worst inventions of the 21st century. I am ashamed to share an industry with this exploitative grift. It has failed to be a useful currency, invented a new class of internet abuse, further enriched the rich, wasted staggering amounts of electricity, hastened climate change, ruined hundreds of otherwise promising projects, provided a climate for hundreds of scams to flourish, created shortages and price hikes for consumer hardware, and injected perverse incentives into technology everywhere. Fuck cryptocurrency.

A personal note

This rant has been a long time coming and is probably one of the most justified expressions of anger I've written for this blog yet. However, it will probably be the last one.

I realize that my blog has been a source of a lot of negativity in the past, and I regret how harsh I've been with some of the projects I've criticised. I will make my arguments by example going forward: if I think we can do better, I'll do it better, instead of criticising those who are just earnestly trying their best.

Thanks for reading 🙂 Let's keep making the software world a better place.


  1. If this is the first you’re hearing of this, a graceful migration is planned: details here ↩︎

  2. “But crypto is far from the worst contributor to climate change!” Yeah, but at least the worst offenders provide value to society. See also Whataboutism. ↩︎

  3. This is why I asked you to disclose your stake in your comment upfront. ↩︎

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Rust is for Professionals

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A professional programmer delivers value through the authoring and maintaining of software that solves problems. (There are other important ways for professional programmers to deliver value but this post is about programming.)

Programmers rely on various tools to author software. Arguably the most important and consequential choice of tool is the programming language.

In this post, I will articulate why I believe Rust is a highly compelling choice of a programming language for software professionals. I will state my case that Rust disposes software to a lower defect rate, reduces total development and deployment costs, and is exceptionally satisfying to use. In short, I hope to convince you to learn and deploy Rust.

My Background and Disclaimers

Before I go too far, I'm targeting this post towards professional programmers - people who program (or support programming through roles like management) as their primary line of work or who spend sufficient time programming outside of work. I consider myself a professional programmer both because I am a full-time engineer in the software industry and because I contribute to some significant open source projects outside of my day job.

The statement Rust is for Professionals does not imply any logical variant thereof. e.g. I am not implying Rust is not for non-professionals. Rather, the subject/thesis merely defines the audience I want to speak to: people who spend a lot of time authoring, maintaining, and supporting software and are invested in its longer-term outcomes.

I think opinion pieces about programming languages benefit from knowing the author's experience with programming. I first started hacking on code in the late 1990's. I've been a full-time software developer since 2007 after graduating with a degree in Computer Engineering (after an aborted attempt at Biomedical Engineering - hence my affinities for hardware and biological sciences). I've programmed in the following languages: C, C++ (only until C++11), C#, Erlang, Go, JavaScript, Java, Lua, Perl, PHP, Python, Ruby, Rust, shell, SQL, and Verilog. Notably missing from this list is a Lisp and a Haskell/Scala type language. Of these languages, I've spent the most time with C, C#, JavaScript, Perl, PHP, Python, and Rust.

I'm not that strong in computer science or language theory: many colleagues can talk circles around me when it comes to describing computer science and programming language concepts like algorithms, type theory, and common terms used to describe languages. (I have failed many technical interviews because of my limitations here.) In contrast, I perceive my technical strengths as applying an engineering rigor and practicality to problem solving. I care vastly more about how/why things work the way they do and the practical consequences of decisions/choices we make when it comes to software. I find that I tend to think about 2nd and 3rd order effects and broader or longer-term consequences more often than others. Some would call this systems engineering.

I've programmed all kinds of different software. Backend web services, desktop applications, web sites, Firefox browser internals, the Mercurial version control tool, build systems, system/machine management. Notably missing are mobile programming (e.g. iOS/Android) and serious embedded systems (I've hacked around with Raspberry Pis and Arduinos, but those seem very friendly compared to other embedded devices). My strongest affinity is probably towards systems software and general purpose tools: I enjoy building software that other people use to build things. Infrastructure if you will.

Finally, I am expressing my personal opinion in this post. I do not speak for any employer, present or former. While I would love to see more Rust at my current employer, this post is not an attempt to influence what happens behind my employer's walls: there a better ways to conduct successful nemawashi / 根回し than a public blog post. I am not affiliated with the Rust Project in any capacity beyond a very infrequent code contributor and issue filer: I view myself as a normal Rust user. I did work at Mozilla - the company who bankrolled most of Rust's initial development. I even briefly worked in the same small Vancouver office as Graydon Hoare, Rust's primary credited inventor! While I was keen for Rust to succeed because it was affiliated with my then employer, I was most definitely not a Rust evangelist or fan boy while at Mozilla. I have little to personally benefit from this post: I'm writing it because I enjoy writing and I believe the message is important.

With that out of the way, let's talk about Rust!

Rust Makes Me Irrationally Giddy

When I look back at my professional self when I was in my 20s, I feel like I was young and dumb and overly exuberant about computers, technology, new software, and the like. An older, more grizzled professional, I now accept the reality that it is a miracle computers and software work as well as they do as often as they do. Point at any common task on a computer and an iceberg of complexity and nuance lingers under the surface. Our industry is abound in the repetition of proven sub-optimal ideas. You see practices cargo culted across the decades (like the 80 character terminal/line width and null-terminated strings, which can both be traced back to Hollerith punchcards from the late 19th century). You witness cycles of pendulum swings, the same fads and trends, just with different labels (microservices are the new SOA, YAML is the new XML, etc). I can definitely relate to people in this industry who want to drop everything and move to a farm or something (but I grew up in Indiana and had cows living down the street, so I know this lifestyle isn't for me).

Rust is the first programming language I've encountered in years that makes me excited. And not just normal excited: irrationally excited. Like the kind of excitement you have for something when you are naive about its limitations and don't know any better (like many blockchain/cryptocurrency advocates). I feel like the discovery of Rust is transporting me back to my younger self, before I discovered the ugly realities of how computers and software work, and is giving me hope that better tools, better ways of building software could actually exist. To channel my inner Marie Kondo: Rust sparks joy.

When I started learning Rust in earnest in 2018, I thought this was a fluke. It is just the butterflies you get when you think you fall in love, I told myself. Give it time: your irrational excitement will fade. But after using Rust for ~2.5 years now, my positive feelings about it have only grown stronger. There's a reason Rust has claimed the top spot in Stack Overflow's most loved languages survey for 5 years and running. And not by the skin of its teeth: Rust is blowing the competition out of the water. 19% over TypeScript and Python. 23% over Kotlin and Go. If this were a Forrester report for a company-offered product, Rust would be the clear market leader and marketers and salespeople would be using this result to sign up new customers in droves and print money hand over fist.

Let me tell you why Rust excites me.

Rust is Different (In a Good Way)

After you've learned enough programming languages, you start to see common patterns. Manual versus garbage collected memory management. Control flow primitives like if, else, do, while, for, unless. Nullable types. Variable declaration syntax. The list goes on.

To me, Rust introduced a number of new concepts, like match for control flow, enums as algebraic types, the borrow checker, the Option and Result types/enums and more. There were also behaviors of Rust that were different from languages I knew: variables are immutable by default, Result types must be checked they aren't an error to avoid a compiler warning, refusing to compile if there are detectable memory access issues, and tons more.

Many of the new concepts weren't novel to Rust. But considering I've had exposure to many popular programming languages, the fact many were new to me means these aren't common features in mainstream languages. Learning Rust felt like fresh air to me: here was a language designed to be general purpose and make inroads into industry adoption while also willing to buck many of the trends of conventional language design from the last several decades.

When going against conventional practice, it is very easy to unintentionally alienate yourself from potential users. Design a programming language too unlike anything in common use and you are going to have a difficult time attracting users. This is a problem with many academic/opinionated programming languages (or so I hear). Rust does venture away from the tried and popular. And that does contribute to a steeper learning curve. However, there is enough familiarity in Rust's core language to give you a foothold when learning Rust. (And Rust's official learning resources are terrific.)

I feel like Rust's language designers set out to take a first principles approach to the language using modern ideas and ignoring old, disproven ones, realized they needed to ground the language in familiarity to achieve market penetration, and produced reasonable compromises to yield something that was new and novel but familiar enough to not completely alienate its large potential user base.

If you don't like being exposed to new ideas and ways of working, Rust's approach is probably a negative to you. But if you are like me and enjoy continuously expanding your knowledge and testing new ideas, Rust's novelty and willingness to be different is a much welcomed attribute.

Rust: Toolbox Included

It used to be that programming languages were just compilers or interpreters. In recent years, we've seen more and more programming languages bundled with other tools, such as build/packaging tools, code formatters, linters, documentation generators, language servers, centralized package repositories, and more.

I'm not sure what spurred this trend (maybe it was Go?), but I think it is a good move. Programming languages are ecosystems and the compiler/interpreter is just one part of a complex system. If you care about end-user experience and adoption (especially if you are a new language), you want an as turnkey on-boarding experience as possible. I think that's easier to pull off when you offer a cohesive, multi-tool strategy to attract and retain users.

We refer to programming languages with a comprehensive standard library as batteries included. I'm going to refer to programming languages with additional included tools beyond the compiler/interpreter as toolbox included.

Rust, is very much a toolbox included language. (Unless you are installing it via your Linux distribution: in that case Linux packagers have likely unbundled all the tools into separate packages, making the experience a bit more end-user hostile, as Linux packagers tend to do for reasons that merit their own blog post. If you want to experience Rust the way its maintainers intended - the Director's Cut if you will - install Rust via rustup.)

In addition to the Rust compiler (rustc) and the Rust standard library, the following components are all officially developed and offered as part of the Rust programming language on GitHub:

  • Cargo - Rust's package manager and build system.
  • Clippy - A Rust linter.
  • rustdoc - Documentation generator for Rust projects.
  • rustfmt - A Rust code formatter.
  • rls - A Rust Language Server Protocol implementation.
  • crates.io - Rust's official, public package registry.
  • rustup - Previously mentioned Rust installer.
  • vscode-rust - Visual Studio Code extension adding support for Rust. (JetBrains has their own high quality extension for their IDEs, which they develop themselves.)
  • The Rust Programming Language Book
  • And many more.

As an end-user, having all these tools and resources at my fingertips, maintained by the official Rust project is an absolute joy.

For the local tools, rustup ensures they are upgraded as a group, so I don't have to worry about managing them. I periodically run rustup update to ensure my Rust toolbox is up-to-date and that's all I have to do.

Contrast with say Node.js, Python, and Ruby, where the package manager is on a separate release cadence from the core language and I have to think about managing multiple tools. (Rust will likely have to cross this bridge once there are multiple implementations of Rust or multiple popular package managers. But until then, things are very simple.)

Further contrast with languages like JavaScript/Node.js, Python, and Ruby, where tools like a code formatter, linter, and documentation generator aren't always developed under the core project umbrella. As an end-user, you have to know to seek out these additional value-add tools. Furthermore, you have to know which ones to use and how to configure them. The fragmentation also tends to yield varying levels of quality and end-user experience, to the detriment of end-users. The Rust toolbox, by contrast, feels simple and polished.

Rust's toolbox included approach enables me to follow unified practices (arguably best practices) while expending minimal effort. As a result, the following tend to be very similar across nearly every Rust project you'll run into:

  • Code formatting. (Nearly everyone uses rustfmt.)
  • Adherence to common coding and style conventions. (Nearly everyone uses clippy.)
  • Project documentation. (Nearly everyone uses rustdoc.)

Cargo could warrant its own dedicated section. But I'll briefly touch on it here.

Cargo is Rust's official package manager and build system. With cargo, you can:

  • Create new Rust projects with a common project layout.
  • Build projects.
  • Run project tests.
  • Update project dependencies.
  • Generate project documentation (via rustdoc).
  • Install other Rust projects from source.
  • Publish packages to Rust package registries.

As a build system, Cargo is generally a breeze to work with. Configuration files are TOML. Adding dependencies is often a 1 line addition to a Cargo.toml file. Dependencies often just work on the first try. It's not like say C/C++, where taking on a new dependency can easily consume a day or two to get it integrated in your build system and compatible with your source code base. I can't emphasize enough how much joy it brings to be able to leverage an it just works build tool for systems-level programming: I'm finding myself doing things in Rust like parsing ELF, PE, and Mach-O binaries because it is so easy to integrate low-level functionality like this into any Rust program. Cargo is boring. And when it comes to build systems, that's a massive compliment!

No other language I've used has as comprehensive and powerful of a toolbox as Rust does. This toolbox is highly leveraged by the Rust community, resulting is remarkable consistency across projects. This consistency makes it easier to understand, use, and contribute back to other Rust projects. Contrast this with say C/C++, where large code bases often employ multiple tools in the same space on different parts of the same code base, leading to cognitive dissonance and overhead.

As a professional programmer, Rust's powerful and friendly toolbox enables me to build Rust software more easily than with other languages. I spend less time wrangling tools and more time coding. That translates to less overhead delivering value through software. Other languages would be wise to emulate aspects of Rust's model.

Rust is Humane

Of all the programming languages I've used, Rust seems to empathize with its users the most.

There's a few facets to this.

A lot of care seems to have gone into the end-user experience of the Rust toolbox.

The Rust compiler often gives extremely actionable error and warning messages. If something is wrong, it tells me why it is wrong, often pointing out exactly where in source code the problem resides, drawing carets to the source code where things went wrong. In many cases, the compiler will emit a suggested fix, which I can incorporate automatically by pressing a few keys in my IDE. Contrast this with C/C++ and even Go, which tend to have either too-terse-to-be-actionable or too-verbose-to-make-sense-of feedback. By comparison, output from other compilers often comes across as condescending, as if they are saying git gud, idiot. Rust's compiler output tends to come across as I'm sorry you had a problem: how can I help? I feel like the compiler actually cares about my [valuable] time and satisfaction. It wants to keep me in flow.

Then there's Clippy, a Rust linter maintained as part of the Rust project.

One thing I love about Clippy is - like the compiler - many of the lints contain suggestions, which I can incorporate automatically through my IDE. So many other linters just tell you what is wrong and don't seem to go the extra mile to be respectful of my time by offering to fix it for me.

Another aspect of Clippy I love is it is like having an invisible Rust mentor continuously providing constructive feedback to help me level-up my Rust. I don't know how many times I've written Rust code similarly to how I would write code in other languages and Clippy suggests a more Rustic solution. Most of the time I'm like oh, I didn't know about that: that's a much better pattern/solution than what I wrote!

Do I agree with Clippy all the time? Nope. But I do find its signal to noise ratio is exceptionally high compared to other linters I've used. And Clippy is trivial to configure and override, so disagreements are easy to manage. Like the Rust compiler, I feel that Clippy is respectful of my time and has the long term maintainability and correctness of my software at heart.

Then there's the Rust Community - the people behind the core Rust projects. The Rust Community is one of the most professional and welcoming I've seen. Their Code of Conduct is sufficiently comprehensive and actionable. They have their vigorous debates like any other community. But the conversation is civil. Bad apples are discarded when they crop up.

At a talk I made about PyOxidizer at a Rust meetup a few years back, I made a comment in passing about a negative comment I encountered on a Rust sub-Reddit. After the talk, a moderator of that sub who was in the audience (unbeknownst to me) approached for more information so they could investigate, which they did.

I once tweeted about a somewhat confusing, not-very-actionable compiler error I encountered. A few minutes later, some compiler developers were conversing in replies. A few hours later, a pull request was created and a much better error message was merged in short order. I'm not a special one-off here either: I've stumbled across Stack Overflow questions and other forums where Rust core developers see that someone is encountering a confusing issue, question the process that got them to that point, and then make refinements to minimize it from happening in the future. The practice is very similar to what empathetic product managers and user experience designers do.

Not many other communities (or companies for that matter) seem to demonstrate such a high level of compassion and empathy for their users. To be honest, I'm not sure how Rust manages to pull it off, as this tends to be very expensive in terms of people time and it can be very easy to not prioritize. One thing is for certain: the Rust Community is loaded with empathetic people who care about the well-being of users of their products. And it shows from the interaction in forums to the software tools they produce. To everyone who has contributed in the Rust Community: thank you for all that you have done and for setting an example for the rest of us to live up to.

Rust is Surprisingly High Level

One of the reasons I avoided learning Rust for years is that I perceived it was too low level and therefore tedious. Rust was being advertised as a systems programming language and you would hear stories of fighting the borrow checker. I assumed I'd need to be thinking a lot about memory and ownership. I assumed the cost to author and maintain Rust code would be high. I thought Rust would be a safer C/C++, with many of the software development lifecycle caveats that apply. And for the software I was writing at a time, the value proposition of Rust seemed weak. I thought a combination of C and say Python was good enough. When I started writing PyOxidizer, I initially thought only the run-time code calling into the Python interpreter C APIs would be written in Rust and the rest would be Python.

How wrong I was!

When I actually started coding Rust, I was shocked at how high-level it felt. Now, depending on the space of your software, Rust code can be very low-level and tedious (not unlike C/C++). However, for the vast majority of code I author, Rust feels more like Python than C. And even the lower-level code feels much higher level than C or even C++.

In my mind, the expressiveness of Rust comes very close to higher-level, dynamic languages (like JavaScript, Python, and Ruby) while maintaining the raw speed of C/C++ all without sacrificing low-level control for cases when you need it. And it does all of this while maintaining strong safety guarantees (unlike say Go, which has the billion dollar mistake: null references).

I had a mental Venn diagram of the properties of programming languages (gc versus non-gc, static versus dynamic typing, compiled versus interpreted, etc) and which traits (like execution speed, development time, etc) would be possible and Rust invalidated large parts of that model!

You often don't need to think about memory management in Rust: once you understand the rules the borrow checker enforces, memory is largely something that exists but is managed for you by the language, just like in garbage collected languages. Of course there are scenarios where you should absolutely be thinking about memory and should have a grasp on what Rust is doing under the hood. But in my experience, most code can be blissfully ignorant of what is actually happening at the memory level. (However, awareness of value ownership when programming Rust does add overhead, so it's not like the cognitive load required for reasoning about memory disappears completely.)

Rust has both a stack and a heap. But when programming you often don't need to distinguish these locations. You can do things in Rust like return a reference to a stack allocated value and pass this reference around to other functions. This would be a CVE factory in C/C++. But because of Rust's borrow checker, this is safe (and a common practice) in Rust. It also predisposes the code towards better performance! Often in C/C++ you will allocate on the heap because you need to return a reference to memory and returning a reference to a stack allocated value is extremely dangerous. This heap allocation incurs run-time overhead. So Rust allowing you to do the fast thing safely is a nice mini win.

In many statically typed languages, I feel like my programming speed is substantially reduced by having to repeatedly spell out or think about type names. In C, it feels like I'm always writing type names so I can perform casting. Newer versions of C++ and Java have improved matters significantly (e.g. the auto keyword). However, I haven't programmed them enough recently to know how they compare to Rust on this front. All I know is that I'm writing type names a lot less frequently in Rust than I thought I would be and that my programming output isn't limited by my typing speed as much as it historically was in C/C++.

Despite being compiled down to assembly and exposing extremely low-level control, Rust often feels like a higher-level language. Equivalent functionality in Rust is often more concise and/or readable than in C/C++, while performing similarly, all while having substantially stronger safety guarantees. As a professional programmer, the value proposition is blinding: Rust enables me to do more with less, achieve a lower defect rate, and not sacrifice on performance.

Correctness, Quality, Execution Speed, and Development Velocity: Pick 4

The operation of computers and operating systems is exceptionally complex.

All programming languages justifiably attempt to abstract away aspects of this complexity to make it easier to deliver value through software. For example:

  • Assembly is hard: here's a higher level language that compiles down to assembly or is implemented in a language that does.
  • Managing memory manually is hard: use garbage collection.
  • Concurrency is hard: only allow 1 thread to run at a time (JavaScript, Python, etc).
  • Text encoding is hard: strings are Unicode/UTF-8.
  • Operating systems have different interfaces: here's a pile of abstractions in the standard library for things like I/O, networking, filesystem paths, etc.
  • Strong, static typing isn't very flexible and can impose high change costs: use dynamic typing.
  • And tons more.

These abstractions often have undesirable consequences/trade-offs:

  • Garbage collection adds run-time overhead (10% is a number that's commonly cited).
  • Garbage collection adds random slowdowns/pauses, making it difficult to achieve consistency in long-tail latency optimization (i.e. ensuring consistency in P99.9, P99.99, and beyond percentiles).
  • Interpreted languages tend to be slower than compiled languages unless you invest lots of time into a JIT.
  • Limiting execution to a single thread limits the ability to harness the full power of modern CPUs, which tend to have several cores.
  • Primitives like environment variables, process arguments, and filenames aren't guaranteed to be UTF-8 and coercing them to UTF-8 can be lossy.
  • Dynamic typing doesn't catch as many bugs at compile time and you have to be more diligent about guarding against invariants.
  • And tons more.

In other words, there are trade-offs with nearly every decision in programming language and [standard] library design. There are usually no obviously correct and undesirable consequence-free decisions.

And we further have to consider the fallibility of people and the inevitability that mistakes will be made, that bugs and regressions will be introduced and will need addressing. As an industry, we generally accept that mistakes occur and bugs are an unavoidable aspect of software development. If new features and enhancements are value, bugs and defects are anti-value. Like financial debt, existence of bugs and sub-optimal code can be tolerated to varying extents. But this is a highly nuanced topic and different people, companies, and projects will have different perspectives on it. We can all agree that bugs are an inevitable fact of software.

We also need to confront the reality that as an industry we have very little empirical data that says much of significance about topics like static versus dynamic typing. Although we do know some things. As Alex Gaynor informs us in What science can tell us about C and C++'s security, the result of ~2/3 of security vulnerabilities being caused by memory unsafety seems to reproduce against a sufficiently diverse set of projects and companies. That result and the implications of it are worth paying attention to!

With that being said, let's dive into my take on the matter.

Of all the programming languages I've used, I feel that Rust has the strongest disposition towards authoring and maintaining correct, high-quality software. It does this by offering a myriad of features that are designed to prevent (or at least minimize) defects. In addition, I believe Rust shifts the detection of defects to earlier in the software development lifecycle, greatly reducing the cost to mitigate defects and therefore develop software.

(As an aside, every time the topic of Rust's safety and correctness comes up, random people on the Internet rush to their keyboards to say things along the lines of C/C++ and other languages can be made to be just as safe as Rust: it's the bad programmers who are using C/C++ wrong. To those people: please stop. Your belief implies the infallibility of people and machines and that mistakes won't be made. If things like memory unsafety bugs in C/C++ could be prevented, industry titans like Apple, Google, and Microsoft would have found a way. These companies are likely taking many more measures to prevent security vulnerabilities than you are and yet the ~2/3 of security vulnerabilities being caused by memory unsafety (read: humans and machines failing to reason about run-time behavior) result still occurs. To the wiser among us, I urge you to call out perpetrators of this good programmers don't create bugs myth when you see it, just like you would/should if you encounter racist, sexist, or other non-inclusive behaviors. The reason is that belief in this myth can lead to physical or emotional harm, just like non-inclusive -isms. Security bugs, for example, can lead to disclosure of private or sensitive data, which can result in real world harm. Think a stalker or abusive former partner learning where you now live. Or a memory unsafety error in a medical device leading to device malfunction, injuring or killing a patient. Because this is a sensitive topic, I want to be clear that I'm not trying to compare the relative harms incurred by racism, sexism, other -isms, or the mythical perfect programmer. Rather, all I'm saying is each of these surpass the minimum threshold of harm incurred that justifies calling out and stopping the harmful behavior. I believe that as professionals we have an ethical and professional obligation to actively squash the mythical perfect programmer fallacy when we encounter it. Debates on the merits and limits of tools to prevent/find defects is fine: belief in the perfect programmer is not. Sorry for the mini rant: I just get upset by people who think software exists in a vacuum and doesn't have real-world implications for people's safety.)

In the sections below, I'll outline some of Rust's features and behaviors that support my assertion that Rust is biased towards correct and higher quality outcomes and lowers total development cost.

The Borrow Checker

To the uninitiated, the borrow checker is perhaps Rust's most novel contribution to programming. It is a compile time mechanism that enforces various rules about how Rust code must behave. Think of these as laws that Rust code must obey. But these are more like societal laws, not scientific laws (which are irrefutable), as Rust's laws can be broken, often leading to negative consequences, just like societal laws.

Rust's ownership rules are as follows:

  • Each value in Rust has a variable that's called its owner.
  • There can only be one owner at a time.
  • When the owner goes out of scope, the value will be dropped / released.

Then there are rules about references (think intelligent pointers) to owned values:

  • At any given time, you can have either one mutable reference or any number of immutable references.
  • References must always be valid.

Put together, these rules say:

  • There is only a single canonical owner of any given value at any given time. The owner automatically releases/frees the value when it is no longer needed (just like a garbage collected language does when the reference count goes to 0).
  • If there are references to an owned value, that reference must be valid (the owned value hasn't been dropped/released) and you can only have either multiple readers or a single writer (not e.g. a reader and a writer).

The implications of these rules on the behavior of Rust code are significant:

  • Use after free isn't something you have to worry about because references can't point to dropped/released values.
  • Buffer underruns, overflows, and other illegal memory access can't exist because references must be valid and point to an owned value / memory range.
  • Memory level data races are prevented because the single writer or multiple readers rule prevents concurrent reading and writing. (An assertion here is any guards - like locks and mutexes - have appropriate barriers/fences in place to ensure correct behavior in multi-threaded contexts. The ones in the standard library should.)

I used to think that these rules limited the behavior of Rust code. That statement is true. However, as I've thought about it more, I've refined my take to be that ownership and reference rules reinforce properties that well-behaved software exhibits.

If a C/C++ program had illegal memory access, you would say it is buggy and the behavior is not correct. If a Java program attempted to mutate a value on thread A without a lock or other synchronization primitive and thread B raced to read it, leading to data inconsistency, you would also call that a bug and incorrect behavior. If a JavaScript/Python/Ruby function were changed such that it started mutating a value that should be constant, you would call that a bug and incorrect behavior.

While Rust's ownership and reference rules do limit what software can do, the functionality they are limiting is often unsafe or buggy, so losing this functionality is often desirable from a quality and correctness standpoint. Put another way, Rust's borrow checker eliminates entire classes of [common] bugs by preventing patterns that lead to incorrect, buggy behavior.

This. Is. Huge.

Rust's borrow checker catches bugs for which other languages have no automated mechanism or no low cost, low latency mechanism for detecting. There are ways to achieve aspects of what the borrow checker does in other languages. But they tend to require contorting your coding style to accomplish and/or employing high cost tools (often running asynchronously to the compiler) such as {address, memory, thread} sanitizers or fuzzing. With Rust, you get this bug detection built into the language and compiler: no additional tools needed. (I'm not saying you shouldn't run additional tools like sanitizers or fuzz testing against Rust: just that you get a significant benefit of these tools for a drastically lower cost since they are built in to the core language.)

Rust's ownership and reference rules help ensure your software is more well-behaved and bug-free. But, sometimes those rules are too strict. Fortunately, Rust isn't dogmatic about enforcing them. There are legitimate cases where you can't work in the confines of these rules.

Say you want to share a cache between multiple threads. Caches need to be both readable and writable by multiple threads. This violates the reference rules and maybe the single owner ownership rule, depending on how things are implemented. Fortunately, there are primitives in the std::sync module like RwLock and Arc (atomically reference counted) you can use here. Arc (and its non-threadsafe Rc counterpart) give you reference counting, just like a garbage collected language. Primitives like RwLock allow you to wrap an inner value and temporarily acquire an appropriate reference to it, mutable or non-mutable. There's a bit of slight of hand here, but the tricks employed enable you to satisfy the ownership and reference rules and use common programming techniques and patterns while still having the safety and correctness protections the borrow checker enforces.

Data Races: What Data Races?

Multi-threaded and concurrent programming is hard. Really hard. Like it is exceptionally easy to introduce hard-to-diagnose-and-debug bugs hard.

There are many reasons for this. We can all probably relate to the fact that reasoning about multi-threaded code is just hard: instead of 1 call stack to reason about there are N. Further complicating matters are that many of us don't have a firm grasp on how memory works at a very low level. Do you know all the ins and outs on how CPU caches work on the architecture you are targeting? Me neither! (But this is a very good place to start excavating a rabbit hole.)

If you are like me, you've spent many years of your professional career not having to care about multi-threading or concurrent programming because you spend so much time in languages with single threads, are only implementing code that runs in single threaded contexts, or you've recognized the reality that implementing this code safely and correctly is hard and you've intentionally avoided the space or chosen software architectures (like queue-based message passing) to minimize risks. Or maybe if you are say a Java programmer you sprinkle synchronized everywhere out of precaution or in response to race conditions / bugs once they are found. (Everyone's personal experience is different, of course.)

Long story short, the aforementioned ownership and reference rules enforced by the borrow checker eliminate data races. This was a major oh wow moment for me when I learned Rust: I had heard about memory safety but didn't realize the same forces behind it were also responsible for making concurrency safe!

This property is referred to as fearless concurrency. I encourage you to read Aaron Turon's Fearless Concurrency as well as the Fearless Concurrency chapter in the Rust Book as well.

Operating Systems Abstractions Ground in Reality

Rust is the only programming language I've used that attempts to expose operating system primitives like environment variables, command arguments, and filesystem paths and doesn't completely mess it up. Truth be told, this is kind of a niche topic. But as I help maintain a version control tool which needs to care about preserving content identically across systems, this topic is near and dear to my heart.

In POSIX land, primitives like environment variables, command arguments, and filesystem paths are char*, or a bag of null-terminated bytes.

On Windows, these primitives are wchar_t*, or wide bytes.

On both POSIX and Windows, the encoding of the raw bytes can be... complicated.

Nearly every programming language / standard library in existence attempts to normalize these values to its native string type, which is typically Unicode or UTF-8. That's doable and correct a lot of the time. Until it isn't.

Rust, by contrast, has standard library APIs like std::env::vars() that will coerce operating system values to Rust's UTF-8 backed String type. But Rust also exposes the OsString type, which represents operating system native strings. And there are function variants like std::env::vars_os() to access the raw values instead of the UTF-8 normalized ones.

Rust paths internally are stored as OsString, as that as the value passed to the C API to perform filesystem I/O. However, you can coerce paths to String easily enough or define paths in terms of String without jumping through hoops.

The point I'm trying to get across is that Rust's abstractions are ground in the reality of how computers work. Given the choice, Rust will rarely sacrifice the ability to do something correctly. In cases like operating system interop, Rust gives you the choice of convenience or correctness, rather than forcing inconvenience or incorrectness on you, like nearly every other language.

Encoding and Enforcing Invariants in the Type System

Rust enums are algebraic data types. Rust enum variants can have values associated with them and Rust enums, like structs (Rust's main way to define a type), can have functions/methods hung off of them. Rust enums are effectively fully-featured, specialized types, where value instances must be a certain variant of that enum. This makes Rust enums much more powerful than in other languages where enums simply map to integer values and/or can't have associated functions. This power unlocks a lot of possibility and harnessed the right way can drastically improve correctness of code and lead to fewer defects.

Programming inevitably needs to deal with invariants, the various possibilities that can occur. Programmers will reach for control flow operators to handle these: if x do this, else if y do that, switch statements, and the like. Handling every possible invariant can be complex, especially as software evolves over time and the ground beneath you is constantly shifting.

As you become more familiar with Rust, you'll find yourself encoding and enforcing invariants in the type system more and more. And enums are likely the main way you accomplish this.

Let's start with a contrived example. In C/C++, if you had a function that accepted either an Apple or an Orange value, you might do something like: void eat(Apple* apple, Orange* orange). Then you'd have inline logic like if apple != null. In a dynamically typed language, you could pass a single argument, but you'd perform inline type comparison. e.g. with Python you'd write if isinstance(fruit, Apple).

With Rust, you'd declare and use an enum. e.g.

struct Apple {}
struct Orange {}

enum Fruit {
    Apple(Apple),
    Orange(Orange),
}

impl Fruit {
    fn eat(&self) {
        match self {
            Self::Apple(apple) => { ... },
            Self::Orange(orange) => { ... },
        }
    }
}

let apple = Fruit::Apple(Apple { });
apple.eat();

This (again contrived) example shows how we Rust enum variants can hold inner values, how we can define methods on Rust enums (so they behave like regular types), and introduces the match control flow operator.

Quickly, match is a super powerful operator. It will compare its argument against provided patterns and evaluate the arm that matches. Patterns must be comprehensive or the compiler will error. In the case of enums, if you add a variant - say Banana for our Fruit example - and fail to add that variant to existing match expressions, you will get compiler errors!

As you become more proficient with Rust, you'll find yourself moving lots of (often redundant) control flow expressions and conditional dispatch (if X do this, if Y do that) into enum variants and encoding the dispatched actions into that enum/type directly. Conceptually, this is logically little different from having a base type or interface or by having a single wrapper class holds various possible values. But the guarantees are stronger because each distinct possibility is strongly defined as an enum variant. And when combined with the match control flow operator, you can have the Rust compiler verify that all variants are accounted for every time you take conditional action based on the variant.

The 2 most common enums in Rust are Option and Result. The following sections will explain how they work and further demonstrate how invariants can be encoded and enforced in Rust's type system.

Option: A Better Way to Handle Nullability

Many programming languages have the concept of nullable types: the ability for a value to be null or some null-like value. You will often find this expressed in languages as null, nil, None, or some variant thereof.

When programming in these languages, nullable values must be accounted or it could lead to errors. Languages like C/C++ and Go will attempt to to resolve the address behind null/nil, leading to at least a program crash and possibly a security vulnerability. Languages like Java and Python will raise exceptions (NullPointerException in Java - frequently abbreviated NPE because it is so common - and likely TypeError in Python).

The prevalence of failure to account for nullable values is a major reason why null references were coined by their inventor as the billion dollar mistake. (I suspect the real world value is much greater than $1B.)

Having an easy-to-ignore nullable invariant lingering in type systems seems like a massive foot gun to me. And indeed every programmer with sufficient experience has likely introduced a bug due to failure to account for null. I sure have!

Rust doesn't have a null value. Therefore no null references and no billion dollar mistake. Instead, Rust's standard library has Option, an enum representing nullable types / values. And Option is vastly superior to null values.

Option<T> is an enum with 2 variants, Some(T) or None: an instance of some type or nothing. What makes Option different from languages with null references is you have to explicitly ask for the inner value: there is no automatic dereference. Rust forces you to confront the reality that a value is nullable and by doing so can drastically reduce a very common bug class. I say drastically reduce instead of eliminate because it is still possible to shoot yourself in the foot. For example, you can call Option.unwrap() to obtain the inner value, triggering a panic if the None variant is present. Despite the potential for programming errors, this solution is strictly better than null references because Option forces you to confront the reality of nullability and use of the dangerous access mechanisms is relatively easy to audit for. (Clippy has some lints to encourage best practices here.)

The existence of Option<T> means that if you are operating on a non-Option value, that value is guaranteed to exist and not be null. If you are operating on Option, the fact it is optional is explicitly encoded in the type and you know you need to account for it. If the value passed into a function was once always defined and a later refactor changed it to be optional (or vice versa), that semantic change is reflected in the type system and Rust forces you to confront the implications when that change is made, not after it was deployed to production and you started seeing segfaults, NPEs, and the like.

After using Rust's Option<T> to express nullability, you will look at every other language with null references and bemoan how primitive and unsafe it feels by comparison. You will yearn for Rust's safer approach biasing towards correctness and higher quality software. Option<T> is massive feature for the professional programmer who cares about these traits.

Result: A Better Way to Handle Errors

Different programming languages have different ways of handling errors. Returning integers or booleans to express success or failure is common. As is throwing and trapping/catching exceptions.

Like nullability, history has shown us that programmers often fail to handle error invariants, with bugs of varying severity ensuing. Even Linux filesystems fail to handle errors!

I argue that the traditional programming patterns we use to handle errors bias towards buggy outcomes, especially with the return an integer/error value approach. It is easy to forget to check the return value of a function. In C/C++, maybe a function once returned nothing (void) and was later refactored to return an integer error code. You have to know to audit for existing callers when making these changes or updating dependencies. Furthermore, handling errors requires effort. That if err != 0 or if err != nil pattern gets mighty annoying to type all of the time! Plus, you have to know what value to compare against: success can often be 0, -1, or 1 or any other arbitrary value. Getting error handling correct 100% of the time is hard. You will fail and this will lead to bugs.

Result is Rust's primary/preferred mechanism for propagating errors and it is different from traditional approaches.

Like Option<T>, Result<T, E> is an enum with 2 variants: Ok(T) and Err(E). That is, a value is either success, wrapping an inner value of type T or error, wrapping an inner value of type E describing that error.

Like Option<T>, Result<T, E> forces you to confront the existence of invariants. Before operating on the value returned by a function, you need to explicitly access it and that forces you to confront that an error could have occurred. In addition, the Result type is annotated and the compiler will emit a warning when you don't check it. Scenarios like changing an infallible function returning a type T to fallible returning a Result<T, E> will fail to compile (due to typing violations) or make compiler warning noise if there are call sites that fail to account for that change.

In addition to making it more likely that errors are acted upon correctly, Rust also contains a ? operator for simplifying handling of errors.

As I said above, typing patterns like if err != 0 or if err != nil can become extremely tedious. Your brain knows what it needs to type to handle errors but it takes precious seconds to do so, slowing you down. You may have code where the majority of the lines are the same error handling boilerplate over and over, increasing verbosity and arguably decreasing readability.

Rust's ? operator will return an Err(E) variant or evaluate to the inner value from the Ok(T) variant. So you can often add an ? operator after a function call returning a Result<T, E> to automatically propagate an error. Typing a single character is vastly easier and simpler than writing explicit control flow for error handling!

The benefits of ? are blatantly apparent when you have functions calling into multiple fallible functions. Long functions with multiple if err != 0 blocks followed by the next logical operation often reduce to a 1-liner. e.g. bar(foo()?)? or foo.do_x()?.do_y()?. When I said earlier that Rust feels like a higher level language, the ? operator is a significant contributor to that.

There are some downsides to Result<T, E> in terms of programming overhead and consistency between Rust programs. I'll cover these later in the post.

Result<T, E> biases Rust code towards correctness by forcing programmers to confront the reality that an error could exist and should be handled. Once you program in Rust, you will look at error handling mechanisms like returning an error integer or nullable value, realize how brittle and/or tedious they are, and yearn for something better.

The unsafe Escape Hatch

If some of Rust's limitations are too much for you, Rust has an in case of emergency break glass feature called unsafe. This is kind of like C mode where you can do things like access and manipulate raw memory through pointers. You can cast a value to a pointer and back to a new Rust reference/value, effectively short circuiting the borrow checker for that particular reference/value.

A common misconception is unsafe disables the borrow checker and/or loosens type checking. This is incorrect: many of those features are still running in unsafe code. However, because Rust can't fully reason about what's happening (e.g. it doesn't know who owns a raw memory address and when it will be freed), it can't properly enforce all of its rules that guarantee safety, leading to, well, unsafety. (See Unsafe Rust for more on this topic.)

unsafe is a necessary evil. In many Rust programs, you won't have to ever use it. But if you do have to use it, its presence will draw review scrutiny like moths to light. So unlike say C/C++ where practically every memory access is a potential security bug and it is effectively impossible in many scenarios to comprehensively audit for memory safety (if there were there would be no memory safety bugs), using unsafe safely is often viable because scrutiny can be concentrated on its relatively few occurrences. And more experienced Rust programmers know how to encapsulate unsafe into safe wrappers, limiting how much code needs to be audited when code around unsafe changes.

What I've personally been enlightened by is the myriad of operations that Rust considers unsafe. As you learn more and more Rust, you'll encounter random functions sprinkled across the standard library that are unsafe and you'll wonder why. The docs usually tell you and that's how you learn something new (and maybe horrifying) about how computers actually work.

Fearless Refactoring

A significant portion of the software development lifecycle is evolving existing code. Fixing bugs. Extending existing code with new functionality. Refactoring code to fix bugs or prepare for new features. Using code in new, unplanned ways.

In many code bases, the amount of people time spent evolving the code dwarfs the time for creating actual greenfield code/features. (Unfortunately, quantifying when you are doing evolution versus greenfield coding is quite difficult, so both facets often get lumped together into simply software development time. But in my mind they are discrete - although highly interdependent - units of work and the evolution time tends to dwarf the greenfield time on established projects.) So it follows that long-term evolution/maintainability of code bases is more important than initial code creation time.

There is a sufficient body of industry research demonstrating that the cost to fix defects rises exponentially as you progress through the software development lifecycle (do a search for say software development lifecycle cost of fixing a bug).

Furthermore, human memory functions not unlike multi-tier caches and your ability to recall information will diminish over time. (You probably know what you were doing 5 minutes ago, might remember what you were doing at this time yesterday, and probably have no clue what you were doing on this date 20 years ago.)

In terms of coding, the best way to address a defect is to not introduce it in the first place. If you can't do that, your goal is to detect and correct it as early in the development process as possible, as close as possible to when the source code creating that defect came into existence. Practically, in order of descending desirability:

  1. Don't introduce defect (this is impossible because humans are fallible).
  2. Detect and correct defect as soon as the bad key press occurs (within reason: you don't want the programmer to lose too much flow) (milliseconds later).
  3. At next build / test time (seconds or minutes later).
  4. When code is shared with others (maybe you push a branch and CI tells you something is wrong) (minutes to days later).
  5. During code review (minutes to days later).
  6. When code is integrated (e.g. merged) (minutes to days later).
  7. When code is deployed (minutes to days or even months later).
  8. When a bug is reported long after the code has been deployed (weeks to years later).

The earlier a defect is caught, the better the chances that the author (or other involved parties) have relevant code paged in and can fix it with less effort and with lower chances of introducing additional defects. For me, authoring new code is relatively easy compared to refactoring old code. That's because I have new code fully paged into my brain and I know it like the back of my hand. I know where the sharp edges are and how you'll get cut if you make certain changes. However, if several months pass without revisiting the code, most of that heightened awareness evaporates. If I need to change or review that code, my ability to do that with a high degree of confidence and efficiency is drastically eroded.

Generally speaking, the earlier a defect is caught, the less damage it can do. Ideally, a defect is caught and fixed at local development time, before you burden a reviewer with finding it and certainly before it causes harm or anti-value after being deployed!

In addition, compressing the software development lifecycle allows you to ship enhancements sooner, which enables you to deliver value sooner. This is what we're trying to do as professional programmers after all!

Because the cost to fix a defect rises exponentially as it moves through the software development lifecycle, it follows that you want defect detection to occur logarithmically to offset that cost. That means you want as many defects as possible to be caught as early as possible.

Compared to other programming languages I've used, Rust is exceptional at detecting defects earlier in the development lifecycle and as a result can drastically lower overall development costs. Here are the main factors contributing to this belief:

  • The type system is relatively strong and prevents many classes of bugs.
  • The borrow checker and the rules it enforces prevent safety issues at compile time. Some of these violations can be detected by other languages' compilers. However, in many cases sufficient auditing (like {address, memory, thread} sanitizers) is run much less frequently, often only in CI tests, which can be hours or days later.
  • Confidence that the above 2 function as advertised.
  • Invariants can be encoded and enforced in the type system through features like enums being algebraic data types.
  • Variables are immutable by default and must be explicitly annotated as mutable. This forces you to think about where and how data mutation occurs, enabling you to spot issues sooner.
  • Option<T> significantly curtails the billion dollar mistake.
  • Result<T, E> forces you to reckon about handling errors.

The Rust compiler is just exceptional at detecting common defects.

Did your code refactor introduce a use-after-free or dangling reference? Don't worry: the borrow checker will detect that. CVE prevented.

Did you introduce a race condition by performing a mutation somewhere that was previously immutable? The borrow checker will detect that. You potentially just saved hours of time debugging a hard-to-reproduce bug.

Did you add an enum variant but forget to add that variant to a match expression? If you avoided using the match all _ expression, the compiler will tell you match arms aren't exhaustive and give you an error.

Did a value that was previously always defined become nullable? Changing the type from T to Option<T> will yield compiler errors due to type mismatch.

Did an Option<T> that was previously always Some(T) suddenly become None? Hopefully following Rust best practices mean your code will just work. In the worst case you get a panic (with a stack trace). But that's on par with say a Java NPE and is strictly better than a null dereference that you get with languages like C/C++.

Did you change or add a function returning Result<T, E> but forget to check if that Result is an Ok(T) or Err(E), the compiler will tell you.

I could go on. Rust is full of little examples like these where the core language and standard library nudge you towards working code and help detect defects earlier during development, saving vast amounts of time and money later.

The Rust compiler is so good at rooting out problems that many Rust programmers have adopted the expression, if it compiles it works. This statement is obviously falsifiable. But compared to every other programming language I've used, I'm shocked by how often it is true.

For other programming languages, a working compile is the beginning of your verification or debugging journey. For Rust, it often feels like the hard part is over and you are almost done. With other languages, you often have an indefinite number of iterations to fix language defects (like null dereferences or dynamic typing errors) beyond the compile step. You need to address these in addition to any logical/intent defects in your code. And fixing logical/intent defects could introduce more post-compile defects. As a programmer, you just don't know when the process will be done. With Rust, the compiler errors tell you exactly what the language defects are. So by the time you appease the compiler, you are left with just your logical/intent defects. I greatly prefer the Rust workflow which separates these because I'm getting clearer feedback on my progress: I know that once I've addressed all the language defects the compiler complains about that is just a matter of fixing logical/intent defects. I know I'm a giant step closer to victory.

The Progress Principle is a psychological observation that people tend to prefer a series of more smaller wins over fewer larger wins. And (unexpected) setbacks can more than offset the benefits of wins. (The book is an easy read and I've found its insights applicable to software development workflows.) Whether Rust's language designers realized it or not, Rust's development workflow plays into our psychological dispositions as described by The Progress Principle: defects (setbacks) tend to occur earlier (at compile time), not at unexpected later times (during code review, CI testing, deploy, etc) and our progress towards a working solution is composed of small wins, such as fixing compiler errors and knowing when you transition from language defects into logical/intent defects. For me, this makes iterating on Rust more fulfilling and enjoyable than other languages.

Rust Makes You a Better Overall Programmer

Whether you realize it or not, every programmer has a personal, generalized model of how to program, how to reason about code, best practices, and what not. When we program, we specialize that model to the language and environment/project we're programming for. The mental model that each of us has its shaped by our experience: which languages we know, which concepts we've been exposed, mistakes we've made, people we've worked with and the practices they've instilled.

If for no other reason, you should learn Rust to expand your generalized model of how to program so that you can apply Rust's principles outside of Rust.

Before I learned Rust, I had a mental model of the lifetimes of various values/variables/memory and how they would be used. If I were coding C, I would attempt to document these in function comments. e.g. if returning a pointer, the comment would say how long the memory behind that pointer lives or who is responsible for freeing it. So when I encountered Rust's ownership and reference rules when learning Rust, they substantially overlapped with my personal mental model of how you should reason about memory in order to avoid bugs. I distinctly remember reading the Rust Book and thinking wow, this seems to be a formalization of some of the concepts and best practices living in my head!

After using Rust for several months, I realized that my prior mental model around reasoning about safe program behavior was woefully incomplete and that Rust's was far superior.

Rust's different ways of doing things will inevitably force you to think about type design, data access patterns, control flow, etc more than most other programming languages. In most other languages, it is much easier to just write runnable code and defer the complexity around ensuring the code is safe/correct and free from certain classes of bugs, like memory access violations and race conditions. Rust's ways of doing things forces you to confront many of these problems up-front, before anything runs.

Rust's stricter model and way about authoring software eventually percolates into your personal generalized model of how to program in any programming language. As you internalize patterns needed to program Rust proficiently, you will subconsciously cherry-pick aspects of Rust and apply them when programming in other languages, making you a better programmer in those languages.

For example, when you program C/C++, you will realize the minefield of memory safety issues that linger in those languages. Many of those mines never explode. But knowing Rust and the patterns needed to appease the borrow checker and write safe code, you have a better sense of where the mines are located, the patterns that lead to them exploding, and you can take preemptive steps or apply extra scrutiny to avoid tripping them. (If you are like me, you'll reach the conclusion that C/C++ is intrinsically unsafe and is beyond saving, vowing to avoid it as much as possible because it is just too dangerous to use safely/responsibly.)

Similarly, when programming in any language, you'll probably think more about variable mutability and non-mutability, even if those languages don't have the concept of mutability on variables. You'll be more attune to certain patterns for mutating data: where mutation occurs, who has a mutable reference, when there are both mutable and non-mutable references in existence. Again, your knowledge from Rust will subconsciously raise your awareness for classes of bugs, making you a better programmer.

The same thing applies to multi-threaded programming and race conditions. After internalizing Rust's model of how to achieve multi-threading safely, you will probably not look at multi-threading in other languages the same way again. If you are like me, you will be horrified by how the lack of Rust's enforced ownership/reference rules predisposes code to so many horrible and hard-to-debug bugs. Again, you will probably find yourself changing your approach to multi-threading to minimize risk.

Fun fact: while at Mozilla I heard multiple anecdotes of [very intelligent] Firefox developers thinking they had found a bug in Rust's borrow checker because they thought it was impossible for a flagged error to occur. However, after sufficient investigation the result was always (maybe with an exception or two because Mozilla adopted Rust very early) that the Rust compiler was correct and the developer's assertions about how code could behave was incorrect. In these cases, the Rust compiler likely prevented hard-to-debug bugs or even exploitable security vulnerabilities. I remember one developer exclaiming that if the bug had shipped, it would have taken weeks to debug and would likely have gone unfixed for years unless its severity warranted staffing.

I strongly feel that I am a better programmer overall after learning Rust because I find myself applying the [best] practices that Rust enforces on me when programming in other languages. For this reason, even if you don't plan to use Rust in any serious capacity, I encourage people to learn Rust because exposure to its ideas will likely transform the ways you think about programming for the better.

Rust Downsides and Dispelling Some Rust Myths

This post has been rather positive about Rust so far. Rust, like everything, is far from perfect and it has its downsides. Professionals know the limitations of their tools and you should know some of the issues you'll run into when using Rust.

In addition, Rust is still a relatively young and unpopular programming language. Since relatively few people know Rust, there are a handful of myths and inaccuracies circling about the language. I'll also dispel some of those here.

Steeper Learning Curve

A common criticism levied against Rust is it is harder to learn than other programming languages. I think this is a valid concern. My experience is Rust took longer to learn and level-up than other languages I've learned recently, notably Go, Kotlin, and Ruby.

I think the primary reason for this is the borrow checker and the rules it enforces. Many programmers have never encountered forced following of ownership and reference rules before and this concept is completely foreign at first. I liken it to a new way to program. If you only have experience with dynamically typed languages that will allow you to compile a ham sandwich, there's a good chance you'll be frustrated by Rust. Rust will likely challenge your conceptions of how programming should work and may frustrate you in the process.

In addition to the borrow checker itself, there are a myriad of types and patterns you'll encounter and eventually need to understand to appease the borrow checker.

Beyond the borrow checker, Rust's standard library is comprehensive and offers a lot of types and traits. It will take a while to be exposed to many of them and know when/how to use each.

You will likely be adding 3rd party crates as dependencies to your project for common functionality not (yet) in the standard library. These expand the scope of concepts you need to learn.

I hope I'm not scaring anybody away: you can go pretty far in Rust without encountering or understanding most of the standard library. That being said, every new type, trait, concept, and crate you learn unlocks new possibilities and avenues for delivering value through programming. So there is an incentive to take the time to learn them sooner than later.

I learned Rust mostly independently for a personal project. While learning resources such as Learn Rust, the Rust Language Cheat Sheet, and even Clippy are fantastic, in hindsight I probably would have become more proficient sooner had I contributed to an existing Rust project and/or had ongoing technical collaboration with more experienced Rust developers. This is probably no different than any other programming language. But because of Rust's steeper learning curve, I think the benefits of peer exposure are more significant. That being said, I've heard anecdotes of teams with no Rust experience learning Rust together with successful results. So there's no formal recipe for success here.

Finally, despite the steeper learning curve, I'd say the return on investment pays off pretty quickly. As I've argued elsewhere in this post, the Rust compiler and type system helps prevent many classes of bugs. So while it may take longer to initially learn and compose idiomatic Rust code, it won't take long for Rust to offset the time that you would have spent chasing bugs, performance optimizations, and the like.

Rust Moves Too Fast

Rust releases a new version every 6 weeks. By contrast, many other programming languages release ~yearly. This faster release cadence has been a common complaint about Rust.

Quickly, I think people conflate release cadence with churn and hardship from that release cadence. Generally speaking, release cadence isn't the thing you care about: it's how disrupted you are from the releases. If your old release continues to work just as well as the new release, release cadence doesn't really matter (many major websites deploy/release dozens of times per day and you don't care because you can't tell: you only care when the UI or behavior changes). So the thing most of us care about is how frequently Rust releases cause disruption. And disruption is often caused by backwards incompatibility and the introduction of new features, which when adopted, force upgrades.

A few years ago, I think the concern that Rust moves too fast was valid: there were significant features in seemingly every release and crates were eager to jump on the new features, forcing you to upgrade if you wanted to keep your dependency tree up to date. I feel like I caught the tail end of this relative chaos in 2018-2019.

But in the last 18-24 months, things seem to have quieted down. Many of the major language features that people were eager to jump on have landed. The only ongoing churn I'm aware of in Rust is in the async ecosystem, and that seems to be stabilizing. New Rust releases are generally pretty quiet in terms of must use features. The last milestone release in my mind was 1.45 in July 2020, which stabilized procedural macros. The community was pretty quick to jump on that feature/release. My Rust projects have targeted 1.45+ for a while now with minimal issues.

9 months with no major disruptions is on par with the release cadence of other programming languages.

In my opinion, the concern that Rust moves too fast, while once valid, no longer generally applies. Pockets of truth for segments of users caring about niche and lesser-used features, yes. But nothing that applies to the entire Rust ecosystem.

Compiling Is Too Slow

A lot of people have commented that Rust builds take too long. It is true: compiling Rust tends to take longer than C/C++, Go, Java, and other languages requiring an ahead-of-time compile step.

While a lot has been done to make the Rust compiler faster (it feels substantially faster than it was a few years ago), it still isn't as fast as other languages.

Not to dismiss the problem, but in a lot of cases, the speed of Rust compilation is fast enough. Incremental builds for small libraries or programs will take a few hundred milliseconds to a second or two. I suspect most of the people complaining about build times today are developing very large Rust programs (tens of thousands of lines of code and/or hundreds of dependencies).

A contributing problem to build times is dependency count. The simplicity of Cargo makes it very easy to accumulate dependencies in Rust and each additional crate will slow your build down. PyOxidizer has ~400 dependencies at this point in time, for example (I've been throwing the kitchen sink at it in terms of features).

There are a few things under your control to mitigate this problem.

First, install sccache, a transparent compiler cache. By default it caches to the local filesystem. But you can also point it at Redis, Memcached, or blob stores in AWS, Azure, or GCP. Firefox's CI uses an S3 backed cache and the hit rate (for both Rust and C/C++) is 90-99% on nearly every build. For PyOxidizer - a medium sized Rust project - sccache reduces full build times from ~53s wall and ~572s CPU to ~32s wall to 225s CPU on my 16 core Ryzen 5950X. The wall time savings on a lower CPU core count machine are even more significant.

Speaking of CPU core counts, the second thing you can do is give yourself access to more CPU cores. Laptops tend to have at most 4 CPU cores. Consider buying desktops or moving builds to remote machines, often with dozens of CPU cores. This requires spending money. But when you factor in people time saved and the cost of that time and the value of someone's happiness/satisfaction, it can often be justified.

I'm not trying to dismiss the problems that slow builds can impose, but if you want to justify their cost, you can argue that the Rust compiler does more at compilation time than other languages and that this overhead brings benefits, such as preventing bugs earlier in the software development lifecycle. There's no such thing as a free lunch and Rust's relatively slower builds are a tax you pay for the correctness the compiler guarantees. To me, that's a justifiable trade-off.

Rust is Too Young or Isn't Production Ready

The isn't production ready concern is likely disproven by the existence of Rust in production in critical roles at a sufficient number of reputable companies. At this point, there are very few technical reasons to say Rust isn't production ready. Non-technical reasons such as lack of organizational knowledge or a limited talent pool for hiring from, yes. But little on the technical front.

The too young part is ultimately a judgement call for how comfortable you are with new technologies.

I'm generally pretty conservative/skeptical about adopting new technology. If you are in this industry long enough you eventually get humbled by your exuberance.

I was probably in the Rust is too young boat as late as 2017, maybe 2018. While I was cheering on Rust as a Mozillian, I was skeptical it was going to take off. Birthing successfully languages is hard. The language still seemed to move too fast and have too many missing features. Things seemed to stabilize around the 2018 edition. That's also when you started commonly hearing of companies adopting Rust. Lots of startups at first. Then big companies started joining in.

Today, companies you have heard of like Amazon, Cloudflare, Discord, Dropbox, Facebook, Google, and Microsoft are adopting Rust to varying degrees. There are 58,750 published crates on crates.io.

I won't drop names, but I've heard of Rust spreading like wildfire at some companies you've heard of. The stories are pretty similar: random person or team wants to try Rust. Something small and isolated with a minimal blast radius in case of disaster is tried first. Rust is an overwhelming success. As more and more people are exposed to Rust, they see the light, cries for Rust become louder, and it becomes even more widely adopted.

The I'm Writing Fewer Bugs Trap

When I program in Rust, I strongly feel that my base rate of defect introduction is substantially less than other programming languages. I have confidence that the Rust compiler coupled with practices like encoding and enforcing invariants in the type system leads to fewer defects. In some cases I feel like the surface area for bugs is limited to logical defects, which are mis-expressions of the human programmer's intent. And since no automated tool can reliably scan for human intent, there's no way to prevent logical bugs, and that surface area is the best we can ever expect from automated scanning.

Knowing what tests to write and how much effort to invest in test writing is a difficult skill to level up and is full of trade-offs. With Rust, I find myself writing fewer tests than in other languages because I have confidence that the compiler will detect issues that would otherwise require explicit testing.

I feel that my beliefs and practices are rooted in reality and justifiable. Yet I recognize the danger in placing too much faith in my tools, in Rust.

In theory, Rust alleviates the need for running additional verification tools, like {address, memory, thread} sanitizers because the safe subset of Rust prevents the issues these tools detect. Many defects caught by fuzzing are also similarly prevented by the design of Rust (but not all: fuzzing is generally a good idea).

What I'm trying to say is that it is really easy to fall into a trap where you are over-confident about the abilities of Rust to prevent defects and you find yourself letting your guard down and not maintaining testing and other verification best practices.

I'm still evolving my beliefs in this area. But my general opinion is that you should still run things like {address, memory, thread} sanitizers and fuzzing because unsafe likely exists somewhere in the compiled code, as likely does C or assembly code. And because a chain is only as strong as its weakest link, it only takes any bug to undermine the safety of the entire system. So while these additional verification tools likely won't find as many issues as they would in unsafe languages, I still think it is a good idea to continue to run them against Rust, especially for high value code bases.

Error Handling

Result<T, E> isn't a panacea. Because errors are full on types rather than simple primitives like integers, you need to spend effort reasoning and coding about how different error types interact. And often you need to write a bit of boilerplate code to facilitate that interaction. This can cancel out a lot of the efficiency benefits of Rust's ? operator for handling errors.

There are a handful of 3rd party Rust crates specializing in error handling that you'll likely to encounter. These include anyhow, error-chain, failure, and thiserror.

Rust's error handling landscape can at times feel fragmented and make you yearn for something more defined/opinionated in the standard library. The Rust Community recognizes that this is an area that can be improved and has formed an error handling project group to improve this space. So hopefully we see some quality of life improvements to error handling in time.

Conclusion

I am irrationally effusive about Rust. When I see this level of excitement in others, I am extremely skeptical. I was skeptical myself when my former colleagues at Mozilla were talking up Rust years ago. But having used Rust for 2.5 years now and authored tens of thousands of lines of Rust code, the initial relationship euphoria has worn off and I am most definitely in love.

Cynically, Rust has ruined in programming in other languages for me. Less cynically, Rust has spoiled me.

When I look at other languages without the rules enforced by Rust's borrow checker, all I see are sharp edges waiting to materialize into bugs.

When I look at other languages with weaker type systems, I think about all the time I spend having to defend against invariants and how much cognitive load and programming/review effort I need to incur to maintain the baseline of quality that I get with Rust.

When I look at programming languages like Python, Ruby, and TypeScript where you can bolt a type system onto a language that doesn't have it, I think why would I want to do that when I can use an even better type system while likely achieving much better performance with Rust? (It's tempting to reach for a metaphor involving lipstick and pigs.)

When I look at other languages, I generally see the same pile of decades old ideas packaged in different boxes. Some of these ideas are good and probably timeless (e.g. functions and variables). Some are demonstrably bad and should be largely excised from common use (e.g. null references - the billion dollar mistake).

When I interface with Rust's tooling, I feel like it is respectful of my time and has my best interests (producing working software) at heart. I feel the maintainers of the tooling care about me.

When I program in Rust, I feel that I'm producing fewer defects overall. The compiler is catching defects that would otherwise be caught later in the software development lifecycle, leading to increased software development costs.

When I interact with Rust's community of people, respect and empathy abounds.

Does Rust have its problems and limitations? Of course it does: nothing is perfect! But in my opinion, its trade-offs are often strictly better than those found in other programming languages I've used.

At the end of the day, Rust is a programming language and therefore a tool. Adept professionals know not to get too attached to your tools: ultimately it is the value you deliver, not how you deliver it. (Of course the choice of tools can significantly impact the quality and timeline of value delivery!) Will my thoughts on Rust and preferred languages change over time as the landscape shifts: of course they will! But for the time being, Rust brings so much to the table that its competition lacks that I'm overly excited about Rust and its ability to advance the state of software/programming and therefore the industry.

In closing, my current CTO uses the phrase commitment to craft as a desired mindset for their technical organization. That phrase translates to various themes: higher quality / lower defect rate, build with the long-term in mind, implement efficient solutions, etc. Like an artist reaches for a preferred paintbrush or a chef for a preferred knife because their preferred tool enables them to better express their craft, I feel that Rust often enables me to better express the potential of my professional craft more than other programming languages. I strongly feel that Rust predisposes software to higher quality outcomes - both in terms of defect rate and run-time efficiency - while also reducing total development and execution costs over the entire software development lifecycle. That makes Rust my first choice language - my go-to tool - for many new projects at this point in time. If you likewise value commitment to craft, I urge you to explore Rust so that you too can better harness the potential of our programming craft.

But don't take my word on it, read what 42 companies using Rust in production have to say.

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careyhimself
166 days ago
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Christchurch, New Zealand
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Saturday Morning Breakfast Cereal - Science Fictions

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Click here to go see the bonus panel!

Hovertext:
If anyone's having deja vu, this was run in Nautilus magazine a while back. I'm linking to the amazon page where you can buy.


Today's News:
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careyhimself
241 days ago
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Christchurch, New Zealand
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kleer001
239 days ago
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Say it again for the kids in the back
jlvanderzwan
240 days ago
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Wasn't this already published before?
Levitz
230 days ago
Hovertext helps: "If anyone's having deja vu, this was run in Nautilus magazine a while back." So yes :)

Saturday Morning Breakfast Cereal - Human

1 Comment and 8 Shares


Click here to go see the bonus panel!

Hovertext:
If your reaction is 'but it's easy to count the dots' you might want to check your motherboard.


Today's News:
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careyhimself
444 days ago
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Christchurch, New Zealand
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wffurr
444 days ago
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Is it 18? I counted 18, but it's hard to do without screaming.
Cambridge, MA
geordie
444 days ago
Yes.
jlvanderzwan
444 days ago
Yeah. I find it helps to close one eye, and scan left-to-right

leah blogs: Ken Thompson's Unix password

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Somewhere around 2014 I found an /etc/passwd file in some dumps of the BSD 3 source tree, containing passwords of all the old timers such as Dennis Ritchie, Ken Thompson, Brian W. Kernighan, Steve Bourne and Bill Joy.

Since the DES-based crypt(3) algorithm used for these hashes is well known to be weak (and limited to at most 8 characters), I thought it would be an easy target to just crack these passwords for fun.

Well known tools for this are john and hashcat.

Quickly, I had cracked a fair deal of these passwords, many of which were very weak. (Curiously, bwk used /.,/.,, which is easy to type on a QWERTY keyboard.)

However, kens password eluded my cracking endeavor. Even an exhaustive search over all lower-case letters and digits took several days (back in 2014) and yielded no result. Since the algorithm was developed by Ken Thompson and Robert Morris, I wondered what’s up there. I also realized, that, compared to other password hashing schemes (such as NTLM), crypt(3) turns out to be quite a bit slower to crack (and perhaps was also less optimized).

Did he really use uppercase letters or even special chars? (A 7-bit exhaustive search would still take over 2 years on a modern GPU.)

The topic came up again earlier this month on The Unix Heritage Society mailing list, and I shared my results and frustration of not being able to break kens password.

Finally, today this secret was resolved by Nigel Williams:

From: Nigel Williams <<a href="mailto:nw@retrocomputingtasmania.com">nw@retrocomputingtasmania.com</a>>
Subject: Re: [TUHS] Recovered /etc/passwd files

ken is done:

ZghOT0eRm4U9s:p/q2-q4!

took 4+ days on an AMD Radeon Vega64 running hashcat at about 930MH/s
during that time (those familiar know the hash-rate fluctuates and
slows down towards the end).

This is a chess move in descriptive notation, and the beginning of many common openings. It fits very well to Ken Thompson’s background in computer chess.

I’m very happy that this mystery has been solved now and I’m pleased of the answer.

[Update 16:29: fix comment on chess.]

NP: Mel Stone—By Now

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careyhimself
718 days ago
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Christchurch, New Zealand
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718 days ago
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beslayed
695 days ago
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.
jepler
718 days ago
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ha!
Earth, Sol system, Western spiral arm

Differentiation and Integration

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"Symbolic integration" is when you theatrically go through the motions of finding integrals, but the actual result you get doesn't matter because it's purely symbolic.
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careyhimself
943 days ago
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Christchurch, New Zealand
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satadru
941 days ago
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This feels like a variant of ay of several classic Sidney Harris cartoons. (I say that approvingly.)
New York, NY
davidar
942 days ago
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Nondeterministic integration: start -> ask an oracle -> differentiate the answer provided by the oracle to verify it matches what you were trying to integrate -> done!
jepler
943 days ago
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OH NO
Earth, Sol system, Western spiral arm
Covarr
943 days ago
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This is why I never got past calculus. It wasn't too difficult, just too annoying.
East Helena, MT
alt_text_bot
943 days ago
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"Symbolic integration" is when you theatrically go through the motions of finding integrals, but the actual result you get doesn't matter because it's purely symbolic.
cjheinz
943 days ago
Note tho, that to computers, integration is easy - just total some shit up, whereas differentiation - find the instantaneous rate of a change of a function - is hard. This is very evident when you use the Minsky economics systems dynamics program.
duerig
943 days ago
Ah. But the trick with computational integration is that you are totaling an *infinite* amount of shit up. :)
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