

Dijkstra was not insane

Recently, a reader on the Higher-Order Perl discussion mailing list made a remark about Edsger Dijkstra and his well-known opposition to the break construction (in Perl, last ) that escapes prematurely from a loop. People often use this as an example to show that Dijkstra was excessively doctrinaire, and out of touch with the reality of programming[1], but usually it's because they don't know what his argument was. I wrote a response, explaining where Dijkstra was coming from, and I am very happy with how it came out, so I'm reposting it here. The list subscriber said, in part: On a side note, I never read anything by Dijkstra that wasn't noticeably out of touch with the reality of programming, which qualifies them as screeds to me. And I say that as a former Pascal programmer, and as one who has read, and bought into, things like Kernighan's "Why Pascal is Not My Favorite Programming Language" and the valid rants about how some form of breaking out of a loop without having to proceed to the end is very useful, without destroying structure (except by Dijkstra's definition of structure)... A lot of people bring up the premature-loop-exit prohibition without understanding why Dijkstra suggested it; it wasn't just that he was a tightassed Dutchman. Dijkstra's idea was this: suppose you want to prove, mathematically, that your program does what it is supposed to do. Please, everyone, suspend your judgment of this issue for a few paragraphs, and bear with me. Let's really suppose that we want to do this. Dijkstra's idea is that the program is essentially a concatenation of blocks, each of which is trying to accomplish something or other, and each of which does not make sense to run unless some part of the program state is set up for it ahead of time. For example, the program might be to print a sorted list of links from a web page. Then the obvious blocks are: A get the web page and store it in a variable B extract the links from the text in the variable into an array C sort the array D print out the array contents Section C is trying to sort the array; if it is correct then the array will be sorted by the time step D commences. But it doesn't make sense to commence step C unless the array is populated. Garbage in, garbage out, as they used to say when I was in elementary school. We say that the "precondition" for C is that the array be populated with URLs, and the "postcondition" is that the array be in sorted order. What you would want to prove about C is that if the precondition holds—that is, if the array is properly populated before C begins—then the postcondition will hold too—that is, the array will be in sorted order when C completes. It occurs to me that calling this a "proof" is probably biasing everyone's thinking. Let's forget about mathematical proofs and just think about ordinary programmers trying to understand if the program is correct. If the intern in the next cubicle handed you his code for this program, and you were looking it over, you would probably think in very much this way: you would identify block C (maybe it's a subroutine, or maybe not) and then you would try to understand if C, given an array of URLs, would produce a properly sorted array by the time it was done. C itself might depend on some sub-blocks or subroutines that performed sub-parts of the task; you could try to understand them similarly. Having proved (or convinced yourself) that C will produce the postcondition "array contains sorted list of URLs", you are in an excellent position to prove (or convince yourself) that block D prints out a sorted array of URLs, which is what you want. Without that belief about C, you are building on sand; you have almost nothing to go on, and you can conclude hardly anything useful about the behavior of D. Now consider a more complex block, one of the form: if (q) { E; } else { F; } Suppose you believe that code E, given precondition x, is guaranteed to produce postcondition y. And suppose you believe the same thing about F. Then you can conclude the same thing about the entire if-else block: if x was true before it began executing, then y will be true when it is done.[2] So you can build up proofs (or beliefs) about small bits of code into proofs (or beliefs) about larger ones. We can understand while loops similarly. Suppose we know that condition p is true prior to the commencement of some loop, and that if p is true before G executes, then p will also be true when G finishes. Then what can we say about this loop? while (q) { G; } We can conclude that if p was true before the loop began, then p will still be true, and q will be false, when the loop ends. BUT BUT BUT BUT if your language has break , then that guarantee goes out the window and you can conclude nothing. Or at the very least your conclusions will become much more difficult. You can no longer treat G atomically; you have to understand its contents in detail. So this is where Dijkstra is coming from: features like break [3] tend to sabotage the benefits of structured programming, and prevent the programmer from understanding the program as a composition of independent units. The other subscriber made a seemingly disparaging reference to "Dijkstra's idea of structure", but I hope it is clear that it was not an arbitrary idea. Dijkstra's idea of structure is what will allow you to understand a large program as a collection of modules. Regardless of your opinion about formal verification methods, or correctness proofs, or the practicality of omitting break from your language, it should at least be clear that Dijkstra was not being doctrinaire just for the sake of doctrine. Some additional notes Here are some interesting peripheral points that I left out of my main discussion because I wanted to stick to the main point, which was: "Dijkstra was not insane". I said in an earlier post that "I often find Dijkstra's innumerable screeds very tiresome in their unkind, unforgiving, and unrealistic attitudes toward programmers." But despite this, I believe he was a brilliant thinker, and almost every time he opened his mouth it was to make a carefully-considered argument. You may not like him, and you may not agree with him, but you'll be better off listening to him. An archive of Dijkstra's miscellaneous notes and essays (a pre-blogging blog, if you like) is maintained at the University of Texas. I recommend it. I said: if (q) { E; } else { F; } Suppose you believe that code E, given precondition x, is guaranteed to produce postcondition y. And suppose you believe the same thing about F. Then you can conclude the same thing about the entire if-else block. Actually, your job is slightly easier. Let's write this: [x] E [y] to mean that code E, given precondition x, produces postcondition y. That is, if we know that x is true when E begins execution, then we know that y is true when E finishes. Then my quoted paragraph above says that from these: [x] E [y]

[x] F [y] we can conclude this: [x] if (q) {E} else {F} [y] But actually we can make a somewhat stronger statement. We can make the same conclusion from weaker assumptions. If we believe these: [x and q] E [y]

[x and not q] F [y] then we can conclude this: [x] if (q) {E} else {F} [y] In fact this precisely expresses the complete semantics of the if-else construction. Why do we use if-else blocks anyway? This is the reason: we want to be able to write code to guarantee something like this: [x] BLAH [y] but we only know how to guarantee [x and q] FOO [y] and [x and not q] BAR [y] for some q. So we write two blocks of code, each of which accomplishes y under some circumstances, and use if-else to make sure that the right one is selected under the right circumstances. Similar to break (but worse), in the presence of goto you are on very shaky ground in trying to conclude anything about whether the program is correct. Suppose you know that C is correct if its precondition (an array of URLs) is satisfied. And you know that B will set up that precondition (that is, the array) if its precondition is satisfied, so it seems like you are all right. But no, because block W somewhere else might have goto C; and transfer control to C without setting up the precondition, and then C could cause winged demons to fly out of your nose. Further reading For a quick overview, see the Wikipedia article on Hoare logic. Hoare logic is the [ x ] E [ y ] notation I used above, and a set of rules saying how to reason with claims of that form. For example, one rule of Hoare logic defines the meaning of the null statement: if ; is the null statement, then [ p ] ; [ p ] for all conditions p . Hoare logic was invented by Tony Hoare, who also invented the Quicksort algorithm. Order

A Discipline of Programming



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no kickback

] E [ ] notation I used above, and a set of rules saying how to reason with claims of that form. For example, one rule of Hoare logic defines the meaning of the null statement: if is the null statement, then [ ] ; [ ] for all conditions . For further details, see Dijkstra's book "A Discipline of Programming". Dijkstra introduces a function called wp for "weakest precondition". Given a piece of code C and a desired postcondition q , wp ( C , q ) is the weakest precondition that is sufficient for code C to accomplish q . That is, it's the minimum prerequisite for C to accomplish q . Most of the book is about how to figure out what these weakest preconditions are, and, once you know them, how they can guide you to through the implementation of your program. I have an idea that the Dijkstra book might be easier to follow after having read this introduction than without it.

for "weakest precondition". Given a piece of code and a desired postcondition , ( , ) is the weakest precondition that is sufficient for code to accomplish . That is, it's the minimum prerequisite for to accomplish . Most of the book is about how to figure out what these weakest preconditions are, and, once you know them, how they can guide you to through the implementation of your program. No discussion of structured programming and goto is complete without a mention of Donald Knuth's wonderful paper Stuctured Programming with go to Statements . This is my single all-time favorite computer science paper. Download it here.

Order

Software Tools in Pascal



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is complete without a mention of Donald Knuth's wonderful paper . This is my single all-time favorite computer science paper. Download it here. Software Tools in Pascal is a book by Kernighan and Plauger that tries to translate the tool suite of their earlier Software Tools book into Pascal. They were repeatedly screwed by deficiencies in the Pascal language, and this was the inspiration for Kernighan's famous "Why Pascal is not my Favorite Programming Language" paper. In effect, Software Tools in Pascal is a book-length case study of the deficiencies of Pascal for practical programming tasks.

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