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This paper proves several generic variants of context lemmas and thus contributes to improving the tools to develop observational semantics that is based on a reduction semantics for a language. The context lemmas are provided for may- as well as two variants of mustconvergence and a wide class of extended lambda calculi, which satisfy certain abstract conditions. The calculi must have a form of node sharing, e.g. plain beta reduction is not permitted. There are two variants, weakly sharing calculi, where the beta-reduction is only permitted for arguments that are variables, and strongly sharing calculi, which roughly correspond to call-by-need calculi, where beta-reduction is completely replaced by a sharing variant. The calculi must obey three abstract assumptions, which are in general easily recognizable given the syntax and the reduction rules. The generic context lemmas have as instances several context lemmas already proved in the literature for specific lambda calculi with sharing. The scope of the generic context lemmas comprises not only call-by-need calculi, but also call-by-value calculi with a form of built-in sharing. Investigations in other, new variants of extended lambda-calculi with sharing, where the language or the reduction rules and/or strategy varies, will be simplified by our result, since specific context lemmas are immediately derivable from the generic context lemma, provided our abstract conditions are met.
We propose a model for measuring the runtime of concurrent programs by the minimal number of evaluation steps. The focus of this paper are improvements, which are program transformations that improve this number in every context, where we distinguish between sequential and parallel improvements, for one or more processors, respectively. We apply the methods to CHF, a model of Concurrent Haskell extended by futures. The language CHF is a typed higher-order functional language with concurrent threads, monadic IO and MVars as synchronizing variables. We show that all deterministic reduction rules and 15 further program transformations are sequential and parallel improvements. We also show that introduction of deterministic parallelism is a parallel improvement, and its inverse a sequential improvement, provided it is applicable. This is a step towards more automated precomputation of concurrent programs during compile time, which is also formally proven to be correctly optimizing.
Reasoning about the correctness of program transformations requires a notion of program equivalence. We present an observational semantics for the concurrent lambda calculus with futures Lambda(fut), which formalizes the operational semantics of the programming language Alice ML. We show that natural program optimizations, as well as partial evaluation with respect to deterministic rules, are correct for Lambda(fut). This relies on a number of fundamental properties that we establish for our observational semantics.
We present a higher-order call-by-need lambda calculus enriched with constructors, case-expressions, recursive letrec-expressions, a seq-operator for sequential evaluation and a non-deterministic operator amb, which is locally bottom-avoiding. We use a small-step operational semantics in form of a normal order reduction. As equational theory we use contextual equivalence, i.e. terms are equal if plugged into an arbitrary program context their termination behaviour is the same. We use a combination of may- as well as must-convergence, which is appropriate for non-deterministic computations. We evolve different proof tools for proving correctness of program transformations. We provide a context lemma for may- as well as must- convergence which restricts the number of contexts that need to be examined for proving contextual equivalence. In combination with so-called complete sets of commuting and forking diagrams we show that all the deterministic reduction rules and also some additional transformations keep contextual equivalence. In contrast to other approaches our syntax as well as semantics does not make use of a heap for sharing expressions. Instead we represent these expressions explicitely via letrec-bindings.