Incredibly Strange Programming Languages

Incredibly Strange Programming Languages

If you've ever suspected that “all programming languages are pretty much the same; they just have different syntax,” well, you will never suspect that again! Covering languages from the unusually powerful (Idris) to the illuminated (قلب) to the profoundly limited (BlooP), and all points in between, these languages will help you think differently about approaches to software problems you face in your day job. Of course we’ll have a lot of fun, but these languages are no joke. The practical benefit of an impractical language is the power to find new approaches to common problems.

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Craig Stuntz

May 06, 2016
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Transcript

  1. 3.

    <spoilers> • Today, many languages look mostly the same •

    “Mainstream” languages will change • There are specific reasons why they change • Just learning about certain languages can help you learn how to write interesting code Spoiler alert! I’m going to give you a whirlwind tour of more than ten different languages. You probably won’t walk out of here productive in all of them. That’s not my goal. Learning interesting languages give you insight into the code you may be writing in 5-10 years. Also, I’d like to suggest that learning languages for their own sake can help you learn new ways of solving problems in any language
  2. 4.

    My challenge to you, when you leave this talk, is

    to choose at least one of the languages you see here which happens to tickle your fancy, and Google it. (Unless it’s P#, which is totally un-Googleable, but I’ll give you the link for that.) Picking one really odd PL you’ve never heard of and diving into it for an evening will help you understand computation in a new light.
  3. 5.

    My challenge to you, when you leave this talk, is

    to choose at least one of the languages you see here which happens to tickle your fancy, and Google it. (Unless it’s P#, which is totally un-Googleable, but I’ll give you the link for that.) Picking one really odd PL you’ve never heard of and diving into it for an evening will help you understand computation in a new light.
  4. 6.

    https://upload.wikimedia.org/wikipedia/commons/0/06/Human_computers_-_Dryden.jpg And that’s what this is really about: Understanding computation,

    via the languages we use to communicate our thoughts about it. Human computers in the National Advisory Committee for Aeronautics (NACA) High Speed Flight Station "Computer Room", Dryden Flight Research Center Facilities, 1949 Computer science computing on a computer
  5. 7.

    http://jsforcats.com/ First, though, let’s ask the obvious question: Why bother?

    Today, you can call yourself a “full stack” developer if you know only JavaScript. Why bother looking at any other language? Didn’t Turing tell us they’re all equivalent anyway?
  6. 8.

    https://www.flickr.com/photos/lenore-m/2514975647/ Languages are tools we use to express the solution

    to problems, and sometimes it’s helpful to have more than one tool.
  7. 11.

    https://www.flickr.com/photos/40726522@N02/9385054093/ You can make delicious hummus using only a pot

    and a hammer, but if you want to make it from dried chick peas in under an hour, (click) you need a pressure cooker. Using the right tools does matter!
  8. 12.

    https://www.flickr.com/photos/40726522@N02/9385054093/ You can make delicious hummus using only a pot

    and a hammer, but if you want to make it from dried chick peas in under an hour, (click) you need a pressure cooker. Using the right tools does matter!
  9. 13.

    Also, we will probably do things differently in the future.

    In programming, “the future” isn’t the year 2364, it’s next decade.
  10. 15.

    var query = from total in Enumerable.Range(0,100).Reverse() select (total >

    0) ? string.Format("{0} bottles of beer on the wall\n{0} bottles of beer\nTake one down, pass it around", total) : string.Format("{0} bottles left", total); foreach (var item in query) { Console.WriteLine(item); } http://rosettacode.org/wiki/99_Bottles_of_Beer If I want to print the lyrics to “99 bottles of beer on the wall,” I could write a program in C#
  11. 16.

    plural = 's' 99.downto(1) do |i| puts "#{i} bottle#{plural} of

    beer on the wall," puts "#{i} bottle#{plural} of beer" puts "Take one down, pass it around!" plural = '' if i - 1 == 1 if i > 1 puts "#{i-1} bottle#{plural} of beer on the wall!" puts else puts "No more bottles of beer on the wall!" end end http://rosettacode.org/wiki/99_Bottles_of_Beer Ruby
  12. 17.

    var beer = 99; while (beer > 0) { var

    verse = [ beer + " bottles of beer on the wall,", beer + " bottles of beer!", "Take one down, pass it around", (beer - 1) + " bottles of beer on the wall!" ].join("\n"); console.log(verse); beer--; } http://rosettacode.org/wiki/99_Bottles_of_Beer JavaScript
  13. 18.

    "#>,_ "#Beer Song>,_ #include <iostream> using namespace std; int main(){

    for( int b=-1; b<99; cout $% '\n') for ( int w=0; w<3; cout $% ".\n"){ if (w==2) cout $% (( b--) ?"Take one dow" "n and pass it arou" "nd":"Go to the sto" "re and buy some mo" "re"); if (b<0) b=99 ; do{ if (w) cout $% ", "; if (b) cout $% b; else cout $% ( (w) ? 'n' : 'N') $% "o more"; cout $% " bottle" ; if (b&'1) cout $% 's' ; cout $% " of beer"; if (w&'1) cout $% " on th" "e wall" ;} while (!w++);} return 0 ; } "# "# by barrym 2011-05-01 "# no bottles were harmed in the "# making of this program!!! http://rosettacode.org/wiki/99_Bottles_of_Beer C++
  14. 19.

    def sing(b, end): print(b or 'No more','bottle'+('s' if b-1 else

    ''), end) for i in range(99, 0, -1): sing(i, 'of beer on the wall,') sing(i, 'of beer,') print('Take one down, pass it around,') sing(i-1, 'of beer on the wall.\n') http://rosettacode.org/wiki/99_Bottles_of_Beer Python And they kinda all look the same. Why do so many programming languages all look so similar?
  15. 20.

    https://www.quora.com/Are-all-programming-languages-based-on-C There are may families of programming languages. Don’t worry

    about trying to see the details here; just take my word there are lots. (click) Point is, mainstream development today uses a super-limited branch of this big chart.
  16. 21.

    https://www.quora.com/Are-all-programming-languages-based-on-C There are may families of programming languages. Don’t worry

    about trying to see the details here; just take my word there are lots. (click) Point is, mainstream development today uses a super-limited branch of this big chart.
  17. 22.

    Lineage 1960 1970 1980 ALGOL LISP APL ML Prolog ALGOL

    BCPL C C++ 1990 2000 C# Java JavaScript Ruby ML OCaml F# 2010 Swift LISP Scheme Clojure APL J SASL SASL Miranda Haskell Prolog Erlang Elixir PHP Here is a simpler, some would say vastly oversimplified, representation. What does this tell us? ALGOL-based languages really common. You can consider yourself a polyglot knowing only ALGOL family languages, even if you’ve used ALGOL! For many of us, our day jobs are 100% in this pool. 1972 was a very interesting year for PLs! C, ML, Prolog, and SASL 1995 brought us Java, JavaScript, PHP, Ruby, and OCaml Recently, we’ve seen a resurgence of ML languages: F#, Swift, Elm Why is that? Why do these waves exist? Will there be another fundamental change in how we’ll program in the future?
  18. 23.

    Mainstream Programming Paradigm Shifts 1950s “Beats machine code” (Assembler) 1960s

    - mid-1970s “Beats assembler” (FORTRAN, COBOL) mid-1970s - mid-1990s “The Great Leap Backwards” (C, C++) mid-1990s - today? “Safer, Web” (Java, JavaScript) Mainstream programmers don't change languages very often, but it does happen, and it is instructive to consider the reasons why. This chart is a vast overgeneralization, but it's a starting point for discussion. 1950s used ASM because compilers not invented. 60s-70s growth of real applications + maintenance. In the late 70s we moved towards smaller computers with less processing power and storage than your WiFi light bulbs today. Language capabilities similarly downscaled during this era. 1990s moved to safer languages for wrong reasons (worried about leaks; should have worried about security, but OK….)
  19. 24.

    Change is coming • Quantum computing • Distributed systems •

    End of Moore’s Law - Storage faster than CPU • Safety and privacy We will change again. JavaScript is not the perfect language which we will use until the end of time. I’m not sure what the mainstream language of 2025 will be, but I’m going to show you some features JS will probably never have, and speculate on what we might see in the future.
  20. 25.

    Is This Some Kind of Joke? HAI 1.2 CAN HAS

    STDIO? VISIBLE "HAI WORLD!!!1!" KTHXBYE http://lolcode.org/ When you heard the title,"Incredibly Strange Programming Languages," you might have thought about joke languages. Some of them are pretty funny! The example on the side is a real programming language called LOLCode. I got a good laugh out of this, but it didn't really make me think about programming any differently.
  21. 26.

    – Harold Abelson and Gerald Jay Sussman with Julie Sussman

    Structure and Interpretation of Computer Programs “Establishing new languages is a powerful strategy for controlling complexity in engineering design; we can often enhance our ability to deal with a complex problem by adopting a new language that enables us to describe (and hence to think about) the problem in a different way…” I'm after something different. I want to find languages which teach me new approaches to common problems which I can use in my day-to-day work, even if I am not implementing my code in that language.
  22. 27.

    What’s In a Name? Does it matter what you call

    your language? Does it matter what the reserved words are? If Ruby were instead called “Yukihiro”, would that change anything? Maybe! You see, the answer possibly depends on the character set used.
  23. 28.

    Console.WriteLine("Hello, World!"); There are a lot of assumptions baked into

    our programming languages, tools, and libraries. One of them is that we will write code mostly in ASCII, left to right text.
  24. 29.
  25. 30.

    var hello = "Hello, World!".Substring(0, 5); Far worse, though, is

    that we program based on assumptions which are simply false, like the notion that characters and Unicode code units and code points are the same thing. But we can get away with that, right, because our software is mostly used by English speakers, or, well, at least not Klingons, right?
  26. 31.

    http://www.unicode.org/reports/tr51/index.html#Emoji_ZWJ_Sequences Sorry. Emoji are ruining everything. (click) So we’re just

    going to have to live with the realities of Unicode. It is not safe to presume code points are characters. It is not safe to presume encoding or text direction. It would be helpful to consider what happens when you abandon these assumptions.
  27. 32.

    http://www.unicode.org/reports/tr51/index.html#Emoji_ZWJ_Sequences " = U+1F1E8 REGIONAL INDICATOR SYMBOL LETTER C U+1F1E6

    REGIONAL INDICATOR SYMBOL LETTER A Sorry. Emoji are ruining everything. (click) So we’re just going to have to live with the realities of Unicode. It is not safe to presume code points are characters. It is not safe to presume encoding or text direction. It would be helpful to consider what happens when you abandon these assumptions.
  28. 33.

    بلق http://nas.sr/%D9%82%D9%84%D8%A8/ I want to tell you about a language

    called ‘alb. If you speak Arabic, please come up to the podium after the presentation and accept my apologies for my mispronunciations. بلق means Heart, but is actually an Arabic recursive acronym for ةجمرب ةغل :بلق ‘alb: lughat barmajeh meaning Heart: A Programming Language. Designed by Ramsey Nasser Roughly half a billion people speak Arabic. Not quite as many as English, but still pretty common. So why not have a programming language in Arabic? What could possibly go wrong?
  29. 34.

    A whole lot, it turns out! There’s a strong technical

    bias in our tooling which favors left-to-right, ASCII code.
  30. 37.

    You know what else won’t work? Your terminal. Any text

    editors you might try. (RTL handled incorrectly in Atom, Sublime, others)
  31. 38.

    http://nas.sr/%D9%82%D9%84%D8%A8/ “The Arabs have a rich tradition of calligraphy and

    poetry attached to the text of their language. Computer scientists have a strangely similar relationship with the text that they write as well, and that overlap was something I became fascinated with.” -Ramsey Nasser Ramsey said at this point it became an art project to try to continue, so he ran with it! Kufic-style tile mosaic of بلق implementation of Fibonacci sequence
  32. 39.

    Mainstream languages depend on punctuation which doesn’t really work in

    Arabic. Curly braces, semicolons, commas, and the like would have to go. But () are OK, so he used LISP syntax. I’ve added the translations. Ramsey’s REPL is strictly Arabic. Note the ligatures in the name. Also the Arabic numerals. Program to compute Fibonacci numbers print Fibonacci 10 => 55 The language itself is less surprising than the fact that he got it to work at all given such adversarial tooling.
  33. 40.

    Mainstream languages depend on punctuation which doesn’t really work in

    Arabic. Curly braces, semicolons, commas, and the like would have to go. But () are OK, so he used LISP syntax. I’ve added the translations. Ramsey’s REPL is strictly Arabic. Note the ligatures in the name. Also the Arabic numerals. Program to compute Fibonacci numbers print Fibonacci 10 => 55 The language itself is less surprising than the fact that he got it to work at all given such adversarial tooling.
  34. 41.

    Mainstream languages depend on punctuation which doesn’t really work in

    Arabic. Curly braces, semicolons, commas, and the like would have to go. But () are OK, so he used LISP syntax. I’ve added the translations. Ramsey’s REPL is strictly Arabic. Note the ligatures in the name. Also the Arabic numerals. Program to compute Fibonacci numbers print Fibonacci 10 => 55 The language itself is less surprising than the fact that he got it to work at all given such adversarial tooling.
  35. 42.

    http://nas.sr/بلق/ You can learn more at Ramsey’s site. Not easy

    to type if you don’t have an Arabic keyboard installed.
  36. 43.

    Is Turing Completeness a Good Idea? Another assumption you hear

    a lot is that languages are all equivalent due to Turing completeness. Turing completeness is widely misunderstood. A Turing complete language can implement any function whose values can be computed by an algorithm, a series of steps. Nearly all programming languages are Turing complete, but some language designers have experimented with more limited languages. Why would you ever want that?
  37. 44.

    “You theorized a machine that could solve any problem. It

    didn’t just do one thing; it did everything.” (fictional) Joan Clarke to (fictional) Alan Turing The Imitation Game (2014) http://theimitationgamemovie.com/#blog/104786411214 A Misunderstanding Here’s a quote from a Hollywood movie. It is fiction. The real Joan Clarke had a double first degree in math from Cambridge and would never say this. Turing never claimed his machines could solve any problem. To the contrary, his purpose was to prove that problems existed which they could not solve!
  38. 45.

    BlooP FlooP GlooP I’m going to tell you about three

    languages, BlooP, FlooP, and GlooP. BlooP is not Turing complete. It is less powerful than the languages you use every day. The other two add some additional features for more power. All three come from Douglas Hofstadter’s book Gödel Escher Bach
  39. 46.

    The book became kinda popular. Apparently moreso than Kurt Gödel

    himself. Anyway, I’m going to talk about chapter XIII
  40. 47.

    BlooP DEFINE PROCEDURE “PRIME?” [N]: BLOCK 0: BEGIN IF N

    = 0 THEN: QUIT BLOCK O; CELL(0) (() 2; LOOP AT MOST MINUS [N,2] TIMES: BLOCK 1: BEGIN IF REMAINDER [N,CELL(0)] = 0, THEN: QUIT BLOCK 0; CELL(0) (() CELL(0) + 1; BLOCK 1: END; OUTPUT (() YES; BLOCK 0: END. BlooP looks like a standard 1970s PL until you look closely at its loops. This function is a predicate which determines if the argument is prime. The interesting thing about the looping construct in BlooP is you can’t have a loop without a bound. This turns out to be the only meaningful restriction on the language. There are really no other surprises. Important point is we were able to find an algorithm which works with a bounded loop. There exist algorithms which can’t be expressed with bounded loops. Notably, we should be able to write a universal mahcine, a program which evaluates BlooP source code, and we can, but not in BlooP!
  41. 48.

    FlooP MU-LOOP: BLOCK n: BEGIN . . . BLOCK n:

    END. FlooP adds exactly one additional feature: an unbounded loop. Hence, it’s a more powerful language. This power comes at a high price. Not all FlooP programs terminate with a sensible result. Some loop forever. But! You can implement a program which evaluates all BlooP code. That’s really useful! But you cannot write a program in FlooP which determines if an arbitrary FlooP program will terminate; Turing and Alonzo Church proved that. So we’ve solved one problem and created another!
  42. 49.

    GlooP So we need a more powerful language to determine

    if FlooP programs terminate. GlooP is a language which is more powerful than FlooP. This slide is blank because it doesn’t — and can’t — exist. Hofstadter points out that a language like this would be magical. You could prove a number of open problems in mathematics by implementing them in FlooP and then using GlooP to see if they terminate for all inputs. So GlooP is impossible.
  43. 50.

    Is obvious why you might want a Turing complete language.

    With such a language, you can implement any algorithm. Why would you want a Turing complete language? In some domains, decidability is a feature. For example, the C# type system is not Turing complete, which means that the C# compiler can always give you an answer as to whether or not your code typechecks. There should never be a time when the compiler runs forever and never returns an answer. This is not true of all programming languages! Turing complete features in PLs include the Scala type system and C++ templates.
  44. 51.

    Another example is in cryptography, where you want successful and

    unsuccessful decryption to take precisely the same amount of time to avoid insecurity via timing oracles. This is hard and there are entire books on the subject, but one of the keys is choosing a subset of your language which leads to deterministic execution paths.
  45. 52.

    Client Server Data Cyphertext Result Cyphertext Computation Data Plaintext Result

    Plaintext Another example is homomorphic encryption, which allows doing computations on encrypted data. You give your encrypted financial data to a cloud service, and it computes your encrypted tax return — without ever decrypting your cyphertext! Of course there are restrictions, because you can’t branch based on a value in data, since it’s encrypted. The limitations end up looking a lot like BlooP, so it’s really useful to know how to do useful work in that world.
  46. 54.

    Does Order of Operation Matter? When we look at source

    code, we can generally figure out in which order things happen. Async features of some languages make this a bit harder, but at least within a method it should be clear what’s going on, right? Maybe.
  47. 56.

    C# if (true *+ LaunchMissiles()) { !" do stuff Well,

    you’ve seen this before. In C#, are there any missiles flying after this code executes?
  48. 57.

    C# IEnumerable<int> stuff = from i in new[] { 1,

    2, 3 } select i * i; !" Line A DoStuff(); !" Line B DoStuffWithStuff(stuff); !" Line C We see a similar effect with enumerables; in which order do the labeled statements execute? (BCA, probably) But for the most part, you can generally look at code in C# and it will be obvious in which order stuff executes.
  49. 58.

    “Now I'm a pretty lazy person and am prepared to

    work quite hard in order to avoid work.” Martin Fowler Refactoring https://www.flickr.com/photos/adewale_oshineye/2933030620/ Haskell, by contrast, is lazy by default. As the programmer, however, you may have to work a little harder. What does this mean?
  50. 59.

    There’s a function called increment. Adds 1 to its argument.

    Line 5 traces when it’s called. Line 6 adds 1 to the argument to the function and returns that value. In the main function, we call the increment function 3 times and store the results in local variables. Then we print two of those results. Look at the order of execution! The first call to increment never appears, and the second two are out of order! That’s laziness at work. None of the calls to increment are invoked until the time at which the result value is needed, in the putStrLn. In practice, you can’t look at nontrivial Haskell code and guess the order of operations, so you write programs where it doesn’t matter.
  51. 60.

    f x = x + 1 g x = x

    + 3 composed = f . g OK, so what’s the point? Doesn’t that just make everything harder? One of the principal benefits of laziness is that it enables easier composition of functions. I’ll start by defining composition, since the syntax may be unfamiliar. Composition simply combines two functions. Haskell uses the period operator, reminiscent of the circle used in math for function composition. First we define two functions, f and g, then we define a third which is their composition. It’s equivalent to calling g and then calling f on its result. All three take one argument and return a value of the same type. Does the code on the slide make sense? Again, I just want to make it clear what that dot operator does.
  52. 61.

    The huge win of composition is you can write methods

    which are simple and correct. I want to write a function to find the minimum value in a list. If you sort a list and take the first, you’ll get the minimum, right? But there’s a problem here, and it’s not correctness. What is it? (Performance)
  53. 62.

    minimum :: Ord a &. [a] "→ a minimum =

    head . sort The Haskell sort, by contrast, is so lazy that it only finds the smallest element when we use “head” to ask for the first result from the sort, and its performance is on the same order as other efficient methods of finding the minimum. This code will never sort the entire list (click) Calling the minimum function is the same as taking the head of the sorted list, and performance is similar to other methods of taking the minimum. Downside of lazy eval: Difficult to reason about performance. Haskell programmers know that taking the head of the sort is efficient, but it’s not obvious from looking at the code. However, performance is often non-obvious in many environments! So lazy evaluation helps produce obviously correct and efficient code.
  54. 63.

    minimum :: Ord a &. [a] "→ a minimum =

    head . sort minimum [3, 2, 1] = head . sort $ [3, 2, 1] The Haskell sort, by contrast, is so lazy that it only finds the smallest element when we use “head” to ask for the first result from the sort, and its performance is on the same order as other efficient methods of finding the minimum. This code will never sort the entire list (click) Calling the minimum function is the same as taking the head of the sorted list, and performance is similar to other methods of taking the minimum. Downside of lazy eval: Difficult to reason about performance. Haskell programmers know that taking the head of the sort is efficient, but it’s not obvious from looking at the code. However, performance is often non-obvious in many environments! So lazy evaluation helps produce obviously correct and efficient code.
  55. 65.

    If What Order Wrong Happen Things? The notion of “order

    of operation” is even harder in a distributed system. Because our CPUs aren't getting much faster these days, many programs behave as distributed systems, even if they happen to be running on a single computer.
  56. 66.

    Explain farmer puzzle. Of course, Most of you will immediately

    realize that this is simply a distributed consensus problem. (click) the two sides of the river, naturally, represent two networked systems. (click) the river itself is a potential network partition, (click) and our goal is to prove that given the specification of the problem, there exists an invariant that no one gets eaten. We’re using this example because it’s easier to explain than Paxos. The real problem is that, like many client requests, this might turn out to be impossible. Perhaps you have seen this problem before and knows that a solution exists, but (click) what if I threw them a cobra and a honey badger? Is there a solution then, and what is it? Many real-world distributed systems problems turn out to be quite complicated!
  57. 67.

    System A System B Explain farmer puzzle. Of course, Most

    of you will immediately realize that this is simply a distributed consensus problem. (click) the two sides of the river, naturally, represent two networked systems. (click) the river itself is a potential network partition, (click) and our goal is to prove that given the specification of the problem, there exists an invariant that no one gets eaten. We’re using this example because it’s easier to explain than Paxos. The real problem is that, like many client requests, this might turn out to be impossible. Perhaps you have seen this problem before and knows that a solution exists, but (click) what if I threw them a cobra and a honey badger? Is there a solution then, and what is it? Many real-world distributed systems problems turn out to be quite complicated!
  58. 68.

    System A System B Possible Network Partition Explain farmer puzzle.

    Of course, Most of you will immediately realize that this is simply a distributed consensus problem. (click) the two sides of the river, naturally, represent two networked systems. (click) the river itself is a potential network partition, (click) and our goal is to prove that given the specification of the problem, there exists an invariant that no one gets eaten. We’re using this example because it’s easier to explain than Paxos. The real problem is that, like many client requests, this might turn out to be impossible. Perhaps you have seen this problem before and knows that a solution exists, but (click) what if I threw them a cobra and a honey badger? Is there a solution then, and what is it? Many real-world distributed systems problems turn out to be quite complicated!
  59. 69.

    System A System B Possible Network Partition THEOREM Spec ⇒

    ☐NobodyGetsEaten Explain farmer puzzle. Of course, Most of you will immediately realize that this is simply a distributed consensus problem. (click) the two sides of the river, naturally, represent two networked systems. (click) the river itself is a potential network partition, (click) and our goal is to prove that given the specification of the problem, there exists an invariant that no one gets eaten. We’re using this example because it’s easier to explain than Paxos. The real problem is that, like many client requests, this might turn out to be impossible. Perhaps you have seen this problem before and knows that a solution exists, but (click) what if I threw them a cobra and a honey badger? Is there a solution then, and what is it? Many real-world distributed systems problems turn out to be quite complicated!
  60. 70.

    System A System B Possible Network Partition THEOREM Spec ⇒

    ☐NobodyGetsEaten Explain farmer puzzle. Of course, Most of you will immediately realize that this is simply a distributed consensus problem. (click) the two sides of the river, naturally, represent two networked systems. (click) the river itself is a potential network partition, (click) and our goal is to prove that given the specification of the problem, there exists an invariant that no one gets eaten. We’re using this example because it’s easier to explain than Paxos. The real problem is that, like many client requests, this might turn out to be impossible. Perhaps you have seen this problem before and knows that a solution exists, but (click) what if I threw them a cobra and a honey badger? Is there a solution then, and what is it? Many real-world distributed systems problems turn out to be quite complicated!
  61. 71.

    https://lorinhochstein.wordpress.com/2014/06/04/crossing-the-river-with-tla/ This is a formal specification of the crossing the

    river problem in TLA+, a language created by Leslie Lamport of MSR. TLA+ lets you formally define properties of systems which change over time and space using temporal logic. One thing you may notice is it’s beautiful, meant to be easier to read than to write. Distributed consensus problems are often the most error-prone pieces of a system, especially if implemented ad hoc. TLA+ doesn’t implement this code, rather, it just makes sure that the algorithm you want to implement is even correct and complete.
  62. 73.

    If we assert that the problem cannot be solved, the

    TLA+ model checker will find a counterexample showing that it can be solved. However, a limitation of TLA+ is that it can only verify the soundness of your model. It cannot verify that you have implemented your model in executable code correctly.
  63. 74.

    http://research.microsoft.com/en-us/um/people/lamport/tla/formal-methods-amazon.pdf Despite this limitation, however, it turns out to be

    extraordinarily useful. Amazon now uses TLA+ for all of its AWS internal protocols, and they have found a number of bugs in the protocols themselves with it, as summarized by the chart on the side.
  64. 77.

    https://github.com/p-org/PSharp/ Still, you might want to find bugs in your

    implementation as well as your model. So I’m going to tell you about another language out of MSR. You’ve heard of Microsoft C# and maybe F#. What about P#? Like TLA+, P# formally models a distributed system. But it compiles to C#, so the models are executable. Model on the screen is a server. There are a couple events, ping and pong. When the server receives ping, it sends pong. Pretty simple system. But it fits on a slide
  65. 78.

    P# is translated via Roslyn to a somewhat more verbose

    and difficult to read syntax in C#. But this is not really that interesting.
  66. 79.

    Like TLA+, it can explore the entire model space and

    find errors in the conceptual model. Unlike TLA+ P# can directly translate to executable code, and it finds the model errors by running exhaustive tests on the real-world system instead of the model. P# does this by augmenting the model with liveness and safety monitors which track execution of the system.
  67. 80.

    The examples on the screen represent real results from finding

    errors in the design of production Microsoft Azure Storage tools which are mostly written in C#. The team wrote a test driver which injected “fake” node failures into the system, chaos monkey style, and the test harness watched how or if the system recovered. P# then exhaustively explores the entire state space of the model.
  68. 81.

    http://p-org.github.io/PSharp/ If you want to learn more, it might seem

    like it’s reasonable to start at the P# homepage, which links to the docs. Also….
  69. 83.

    Is Real Privacy Even Possible? When we share data with

    an online service, even if we trust the service itself, how can we be sure they won’t accidentally leak our data?
  70. 84.

    It’s certainly easy to screw this up. FB story Jeeves

    is a system for enforcing privacy at the language level. It can be laid as a DSL over Scala, Python, etc.
  71. 85.

    https://github.com/jeanqasaur/jeeves/blob/master/demo/jcal/tests.py Here is what Jeeves does, at the most basic

    level. Django app for Calendar / Events. Alice is holding a surprise party for Eve. Real privacy is more complicated.
  72. 86.

    https://github.com/jeanqasaur/jeeves/blob/master/demo/jcal/jcal/models.py Have an event. Looks like a normal Django model.

    (click) Special method to identify private events (click) This code notes the event should be visible to the host and guests, but not to the public (click) Special values for properties of private events. The Jeeves runtime will ensure that even if we compute derived values from this data, anonymity will be preserved in all contexts.
  73. 87.

    https://github.com/jeanqasaur/jeeves/blob/master/demo/jcal/jcal/models.py Have an event. Looks like a normal Django model.

    (click) Special method to identify private events (click) This code notes the event should be visible to the host and guests, but not to the public (click) Special values for properties of private events. The Jeeves runtime will ensure that even if we compute derived values from this data, anonymity will be preserved in all contexts.
  74. 88.

    https://github.com/jeanqasaur/jeeves/blob/master/demo/jcal/jcal/models.py Have an event. Looks like a normal Django model.

    (click) Special method to identify private events (click) This code notes the event should be visible to the host and guests, but not to the public (click) Special values for properties of private events. The Jeeves runtime will ensure that even if we compute derived values from this data, anonymity will be preserved in all contexts.
  75. 89.

    https://github.com/jeanqasaur/jeeves/blob/master/demo/jcal/tests.py So again, flipping back to the tests, we can

    see that Jeeves is hiding the data when the current user is Eve. This would also be true using data derived from this event.
  76. 90.

    http://arxiv.org/pdf/1507.03513v5.pdf The core idea is to keep trust policy in

    a small and easily understood segment of the application. “allows programmers to factor out information flow policies from the rest of web programs and rely on a web framework to dynamically enforce the policies.”
  77. 93.

    If you program in JavaScript or C#, it might not

    be obvious that the language has a fundamental type, unless it’s null or undefined.
  78. 94.

    C Bag of bits C# , Java Object (ref. types)

    Value types Lisp Atom List Haskell Algebraic data types Julia, MATLAB Vector, Matrix APL, J Array Idris Theorem The data types provided in languages like C and C# are so under specified that it is difficult to think of them as having a fundamental datatype at all. So we have these boring arguments about whether enforcing them at compile time or runtime is a good idea at all. But many other languages are built around a more specific datatype which permits making functions which work on broad array of values. More importantly, a more powerful type theory allows the compiler to assist the programmer in producing correct and expressive code.
  79. 95.
  80. 96.

    This isn't what I would call idiomatic Idris code, but

    I'm trying to make it recognizable to developers who typically work in other languages. It’s also written to demonstrate a very specific point, as you’ll see in a second. I want to write a function to compute the average of a list of integers. If I call it with []… How can I fix that?
  81. 97.

    I’ve added an implicit argument ({}) stating there must be

    a proof that the list is non-empty. Tells us something interesting about the types in Idris. We often think of types as denoting the sorts of values an argument might contain. But in Idris types also denote the behavior of the code. Here, the type signature says, “All code which calls this function must first test the list to make sure it is non-empty.” So when I compile, even with a non-empty list, the compiler tells me I haven’t proven it’s non-empty, because I can call formatAverage with any old list. How can we check the non-emptiness of a variable at compile time?
  82. 101.
  83. 102.
  84. 103.
  85. 105.

    Very simple. Vigil deletes the offending method from the source

    code. Of course, now our innocent_fn which calls the now-nonexistent say_hello isn’t so innocent anymore….
  86. 106.
  87. 107.

    It’s deleted as well. There’s not much left, is there?

    And innocent_fn doesn’t exist anymore. Uh oh!
  88. 109.

    This is hard to read, but vigil is now deleting

    itself. Because all errors must be punished.
  89. 110.

    Best place to learn about Vigil is GitHub. There’s an

    article in WIRED, but to hell with WIRED.
  90. 112.

    Weird Machines Finally, I’m going to talk about weird machines.

    I won’t try to explain much about these, because, to be honest, I don’t fully understand them.
  91. 113.

    LIQUi|̼ let circUa = CompileUa N a qs "# Compile

    1 Shor step let count = circUa.GateCount() ∗ n∗2 let hits, misses = "# Get total gate count Gate.CacheStats() "# Get gate caching stats let gp = GrowPars(30, 2, false) "# Params for growing let circUa = circUa.GrowGates(k, gp ) "# Grow the circuit circUa.Dump() "# Dump circuit to file ShorRun circUa rslt n a qs "# Run Shor let m = Array.m api "# Accumulate all the ( fun i bit "→ bit <<< i ) rslt "# ..phase estim ation bits |> Array.sum "# ..m = quantum result let permG, permS, permN = k.Perms "# Get permutation stats http://stationq.github.io/Liquid/ You’ve heard of Language Integrated Query, now there’s Language Integrated Quantum operations! LIQUi|> is a Domain Specific Language and runtime for simulation of quantum computing on classical hardware. There is good reason to believe that quantum computing hardware is possible, but we don’t know how to build it.
  92. 114.

    We can simulate the hardware and run quantum algorithms (albeit

    much, much slower) on classical hardware. So we can learn how to program quantum computers in parallel with learning how to build them.
  93. 115.

    We can simulate the hardware and run quantum algorithms (albeit

    much, much slower) on classical hardware. So we can learn how to program quantum computers in parallel with learning how to build them.
  94. 117.

    Kappa %agent: A(b,c) %agent: B(a,c) %agent: C(b,a) ## %var: ’V’

    1 %var: ’k1’ INF %var: ’k2’ 1.0E-4/’V’ %var: ’k_off’ 0.1 ## ’a.b’ A(b),B(a) "→ A(b!1),B(a!1) @ ’k2’ (’k1’) ’a.c’ A(c),C(a) "→ A(c!1),C(a!1) @ ’k2’ (’k1’) ’b.c’ B(c),C(b) "→ B(c!1),C(b!1) @ ’k2’ (’k1’) ## ’a..b’ A(b!a.B) "→ A(b) @ ’k_off’ ’a..c’ A(c!a.C) "→ A(c) @ ’k_off’ ’b..c’ B(c!b.C) "→ B(c) @ ’k_off’ ## %var: ’n’ 1000 ## %init: ’n’ A(),B(),C() %mod: [E] > 10000 do \$STOP %def: "dotSnapshots" "true" Kappa, one member of the growing family of rule-based languages.
  95. 118.

    Rule-based modeling has attracted recent attention because they allows one

    to deal with the combinatorial complexity of multi-state and multi-component biological molecules. What does that mean? Kappa programs simulate biological processes.
  96. 119.

    Rule-based modeling has attracted recent attention because they allows one

    to deal with the combinatorial complexity of multi-state and multi-component biological molecules. What does that mean? Kappa programs simulate biological processes.
  97. 121.

    What Have We Learned? There are lots of interesting languages

    you can play with today. Many look nothing like the languages you use in your day job They will help you learn to think about computing differently.