Edsger W. Dijkstra: Difference between revisions
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One specific complaint that Dijkstra levels at APL is its use of an expanded set of operations relative to the typical set used in computer science research. It's true that APL dedicates much of its functionality to working with arrays, but this shouldn't be taken as a theoretical weakness. In fact, APLs array operators are much like structured programming, which eliminates a single construct, Go to, in favor of several branching and looping constructs like ''if'' and ''while''. Moving from scalar processing to array processing requires new operations in exchange for, not at the expense of, improved theoretical properties. Nonetheless, language designers such as [[Arthur Whitney]] put considerable effort into reducing the number of symbols needed in the language in order to express ideas. Indeed, [[Fred Brooks]] praised [[Ken Iverson|Iverson]] for a "fierce determination not to invent any new constructs, until you have to."<ref>Brooks, Fred. ''A Celebration of Kenneth Iverson'' ([https://www.jsoftware.com/papers/KEIQA.htm#touchstone excerpt])</ref> | One specific complaint that Dijkstra levels at APL is its use of an expanded set of operations relative to the typical set used in computer science research. It's true that APL dedicates much of its functionality to working with arrays, but this shouldn't be taken as a theoretical weakness. In fact, APLs array operators are much like structured programming, which eliminates a single construct, Go to, in favor of several branching and looping constructs like ''if'' and ''while''. Moving from scalar processing to array processing requires new operations in exchange for, not at the expense of, improved theoretical properties. Nonetheless, language designers such as [[Arthur Whitney]] put considerable effort into reducing the number of symbols needed in the language in order to express ideas. Indeed, [[Fred Brooks]] praised [[Ken Iverson|Iverson]] for a "fierce determination not to invent any new constructs, until you have to."<ref>Brooks, Fred. ''A Celebration of Kenneth Iverson'' ([https://www.jsoftware.com/papers/KEIQA.htm#touchstone excerpt])</ref> | ||
Dijkstra pointed out that APL is not used in practice for theoretical computer science applications. This is likely to be cultural: because of the requirement that published papers be readable by most practicing theorists, computer scientists tend to use languages or [[wikipedia:Psuedocode|pseudocode]] which is kept deliberately simple and uses only the well-known programming features. Nonetheless there are array languages or languages with array influence aimed at theoretical work, such as [[FP]], [[FL]], [[Nial]], and [[Futhark]]. APL concepts such as the [[Scan | Dijkstra pointed out that APL is not used in practice for theoretical computer science applications. This is likely to be cultural: because of the requirement that published papers be readable by most practicing theorists, computer scientists tend to use languages or [[wikipedia:Psuedocode|pseudocode]] which is kept deliberately simple and uses only the well-known programming features. Nonetheless there are array languages or languages with array influence aimed at theoretical work, such as [[FP]], [[FL]], [[Nial]], and [[Futhark]]. APL concepts such as the [[Scan]] operator have also been adopted in the study of parallel programming.<ref>Blelloch, G.E. [https://ieeexplore.ieee.org/document/42122 "Scans as primitive parallel operations"] </ref> [[Aaron Hsu]] has made heavy use of APL in studying parallel algorithms in [[Co-dfns]], and emphasizes its transparent performance characteristics: time and space complexity can usually be obtained directly from an APL expression with little effort. | ||
Dijkstra claims that APL is a "bag of tricks" which encourages the programmer to think of problems as merely puzzles which require them to find the correct trick rather than to approach them by trying to express their ideas elegantly. An APLer would probably conclude that he has fallen into the trap of thinking of APL as a [[domain-specific language]] which just happens to have the right solution for the particular problem under consideration. Iverson thought instead that APLs tricks are carefully selected tools which guide programmers to more elegant solutions, and elegance is a primary concern for APL programmers today. This comment may also reflect a lack of introspection by Dijkstra into his own working methods and those of other mathematicians: mathematicians work by applying high-level concepts, techniques, or tricks, and write proofs by translating these tricks into mathematical language. APL aids a mathematician's thinking by supplying a well-considered set of techniques, and eases reading by making the "tricks" explicit rather than forcing the reader to extract them from a low-level notation. | Dijkstra claims that APL is a "bag of tricks" which encourages the programmer to think of problems as merely puzzles which require them to find the correct trick rather than to approach them by trying to express their ideas elegantly. An APLer would probably conclude that he has fallen into the trap of thinking of APL as a [[domain-specific language]] which just happens to have the right solution for the particular problem under consideration. Iverson thought instead that APLs tricks are carefully selected tools which guide programmers to more elegant solutions, and elegance is a primary concern for APL programmers today. This comment may also reflect a lack of introspection by Dijkstra into his own working methods and those of other mathematicians: mathematicians work by applying high-level concepts, techniques, or tricks, and write proofs by translating these tricks into mathematical language. APL aids a mathematician's thinking by supplying a well-considered set of techniques, and eases reading by making the "tricks" explicit rather than forcing the reader to extract them from a low-level notation. | ||