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This paper proves correctness of Nöcker's method of strictness analysis, implemented in the Clean compiler, which is an effective way for strictness analysis in lazy functional languages based on their operational semantics. We improve upon the work of Clark, Hankin and Hunt did on the correctness of the abstract reduction rules. Our method fully considers the cycle detection rules, which are the main strength of Nöcker's strictness analysis. Our algorithm SAL is a reformulation of Nöcker's strictness analysis algorithm in a higher-order call-by-need lambda-calculus with case, constructors, letrec, and seq, extended by set constants like Top or Inf, denoting sets of expressions. It is also possible to define new set constants by recursive equations with a greatest fixpoint semantics. The operational semantics is a small-step semantics. Equality of expressions is defined by a contextual semantics that observes termination of expressions. Basically, SAL is a non-termination checker. The proof of its correctness and hence of Nöcker's strictness analysis is based mainly on an exact analysis of the lengths of normal order reduction sequences. The main measure being the number of 'essential' reductions in a normal order reduction sequence. Our tools and results provide new insights into call-by-need lambda-calculi, the role of sharing in functional programming languages, and into strictness analysis in general. The correctness result provides a foundation for Nöcker's strictness analysis in Clean, and also for its use in Haskell.
This paper proves correctness of Nocker s method of strictness analysis, implemented for Clean, which is an e ective way for strictness analysis in lazy functional languages based on their operational semantics. We improve upon the work of Clark, Hankin and Hunt, which addresses correctness of the abstract reduction rules. Our method also addresses the cycle detection rules, which are the main strength of Nocker s strictness analysis. We reformulate Nocker s strictness analysis algorithm in a higherorder lambda-calculus with case, constructors, letrec, and a nondeterministic choice operator used as a union operator. Furthermore, the calculus is expressive enough to represent abstract constants like Top or Inf. The operational semantics is a small-step semantics and equality of expressions is defined by a contextual semantics that observes termination of expressions. The correctness of several reductions is proved using a context lemma and complete sets of forking and commuting diagrams. The proof is based mainly on an exact analysis of the lengths of normal order reductions. However, there remains a small gap: Currently, the proof for correctness of strictness analysis requires the conjecture that our behavioral preorder is contained in the contextual preorder. The proof is valid without referring to the conjecture, if no abstract constants are used in the analysis.
Motivated by the question of correctness of a specific implementation of concurrent buffers in the lambda calculus with futures underlying Alice ML, we prove that concurrent buffers and handled futures can correctly encode each other. Correctness means that our encodings preserve and reflect the observations of may- and must-convergence. This also shows correctness wrt. program semantics, since the encodings are adequate translations wrt. contextual semantics. While these translations encode blocking into queuing and waiting, we also provide an adequate encoding of buffers in a calculus without handles, which is more low-level and uses busy-waiting instead of blocking. Furthermore we demonstrate that our correctness concept applies to the whole compilation process from high-level to low-level concurrent languages, by translating the calculus with buffers, handled futures and data constructors into a small core language without those constructs.
Various concurrency primitives have been added to sequential programming languages, in order to turn them concurrent. Prominent examples are concurrent buffers for Haskell, channels in Concurrent ML, joins in JoCaml, and handled futures in Alice ML. Even though one might conjecture that all these primitives provide the same expressiveness, proving this equivalence is an open challenge in the area of program semantics. In this paper, we establish a first instance of this conjecture. We show that concurrent buffers can be encoded in the lambda calculus with futures underlying Alice ML. Our correctness proof results from a systematic method, based on observational semantics with respect to may and must convergence.
Motivated by the question of correctness of a specific implementation of concurrent buffers in the lambda calculus with futures underlying Alice ML, we prove that concurrent buffers and handled futures can correctly encode each other. Correctness means that our encodings preserve and reflect the observations of may- and must-convergence, and as a consequence also yields soundness of the encodings with respect to a contextually defined notion of program equivalence. While these translations encode blocking into queuing and waiting, we also describe an adequate encoding of buffers in a calculus without handles, which is more low-level and uses busy-waiting instead of blocking. Furthermore we demonstrate that our correctness concept applies to the whole compilation process from high-level to low-level concurrent languages, by translating the calculus with buffers, handled futures and data constructors into a small core language without those constructs.
This paper describes context analysis, an extension to strictness analysis for lazy functional languages. In particular it extends Wadler's four point domain and permits in nitely many abstract values. A calculus is presented based on abstract reduction which given the abstract values for the result automatically finds the abstract values for the arguments. The results of the analysis are useful for veri fication purposes and can also be used in compilers which require strictness information.
The extraction of strictness information marks an indispensable element of an efficient compilation of lazy functional languages like Haskell. Based on the method of abstract reduction we have developed an e cient strictness analyser for a core language of Haskell. It is completely written in Haskell and compares favourably with known implementations. The implementation is based on the G#-machine, which is an extension of the G-machine that has been adapted to the needs of abstract reduction.