Fission for Program Comprehension

Gibbons, Jeremy

doi:10.1007/11783596_12

Cited by 8 publications

(8 citation statements)

References 19 publications

(15 reference statements)

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“…Throughout the formalisation we operate on elements inside lattices of partial expressions (↓a, ↓b, commands (↓c) or states (↓µ). We represent values in a lattice with an inductive data type prefix 6 (PrefixSets.v: prefix) indexed by the top element of the lattice and the ordering relation 7 . Values of prefix data type store an element from a lattice together with the evidence that it is in the ordering relation with the top element.…”

Section: Lattices and Galois Connectionsmentioning

confidence: 99%

“…So a prefix set of a top element of a lattice denotes a set of all elements in that (complete) lattice. 7 In order to make the code snippets in the paper easier to read we omit the ordering relation when indexing prefix.…”

Section: Imp Syntax and Semanticsmentioning

confidence: 99%

“…Mechanised proofs of correctness of calculational reasoning has been considered in the Algebra of Programming in Agda (AOPA) system [11], and subsequently extended to include derivation of greedy algorithms using Galois connections [5]. Another interesting, complementary approach to program comprehension is Gibbons' program fission [7], in which the fusion law is applied "in reverse" to an optimized, existing program in order to attempt to discover a rationale for its behavior: for example by decomposing an optimized word-counting program into a "reforested" version that decomposes its behavior into "construct a list of all the words" and "take the length of the list". We conjecture that the traces that seem to arise as a natural intermediate structure in program slicing might be viewed as an extreme example of fission.…”

Section: Related and Future Workmentioning

confidence: 99%

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Verified Self-Explaining Computation

Stolarek

Cheney

2019

Lecture Notes in Computer Science

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Common programming tools, like compilers, debuggers, and IDEs, crucially rely on the ability to analyse program code to reason about its behaviour and properties. There has been a great deal of work on verifying compilers and static analyses, but far less on verifying dynamic analyses such as program slicing. Recently, a new mathematical framework for slicing was introduced in which forward and backward slicing are dual in the sense that they constitute a Galois connection. This paper formalises forward and backward dynamic slicing algorithms for a simple imperative programming language, and formally verifies their duality using the Coq proof assistant.

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Section: Lattices and Galois Connectionsmentioning

confidence: 99%

Section: Imp Syntax and Semanticsmentioning

confidence: 99%

Section: Related and Future Workmentioning

confidence: 99%

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Verified Self-Explaining Computation

Stolarek

Cheney

2019

Lecture Notes in Computer Science

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“…One approach to solving this problem is to simply apply fusion. Even though this property is normally viewed as being concerned with combining a function with a fold, it can also be viewed in the opposite direction as providing a sufficient condition for the factorisation, or fission (Gibbons, 2006), of a fold:…”

Section: Worker/wrapper For Foldsmentioning

confidence: 99%

Factorising folds for faster functions

Hutton¹,

Jaskelioff²,

Gill³

2010

J. Funct. Prog.

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The worker/wrapper transformation is a general technique for improving the performance of recursive programs by changing their types. The previous formalisation (A. Gill & G. Hutton, J. Funct. Program., vol. 19, 2009, pp. 227–251) was based upon a simple fixed-point semantics of recursion. In this paper, we develop a more structured approach, based upon initial-algebra semantics. In particular, we show how the worker/wrapper transformation can be applied to programs defined using the structured pattern of recursion captured by fold operators, and illustrate our new technique with a number of examples.

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“…Function wc is a paramorphism. It is inspired in one of the word counting algorithms described in [7]. This function adds one each time the end of a word is detected, and for this it uses the current character c and the next one d (except at the end).…”

Section: Proposition 34 (Para-fold Fusion)mentioning

confidence: 99%

Program Fusion with Paramorphisms

Domínguez

Pardo

2006

Electronic Workshops in Computing

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The design of programs as the composition of smaller ones is a wide spread approach to programming. In functional programming, this approach raises the necessity of creating a good amount of intermediate data structures with the only aim of passing data from one function to another. Using program fusion techniques, it is possible to eliminate many of those intermediate data structures by an appropriate combination of the codes of the involved functions. In the standard case, no mention to the eliminated data structure remains in the code obtained from fusion. However, there are situations in which parts of that data structure becomes an internal value manipulated by the fused program. This happens, for example, when primitive recursive functions (socalled paramorphisms) are involved. We show, for example, that the result of fusing a primitive recursive function p with another function f may give as result a function that contains calls to f. Moreover, we show that in some cases the result of fusion may be less efficient than the original composition. We also investigate a general recursive version of paramorphism. This study is strongly motivated by the development of a fusion tool for Haskell programs called HFUSION.

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Fission for Program Comprehension

Cited by 8 publications

References 19 publications

Verified Self-Explaining Computation

Verified Self-Explaining Computation

Factorising folds for faster functions

Program Fusion with Paramorphisms

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