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Comparison of concurrent programming languages and correctness of program transformations in concurrency are the focus of this research. As criterion we use contextual semantics adapted to concurrency, where may -- as well as should -- convergence are observed. We investigate the relation between the synchronous pi-calculus and a core language of Concurrent Haskell (CH). The contextual semantics is on the one hand forgiving with respect to the details of the operational semantics, and on the other hand implies strong requirements for the interplay between the processes after translation. Our result is that CH embraces the synchronous pi-calculus. Our main task is to find and prove correctness of encodings of pi-calculus channels by CH's concurrency primitives, which are MVars. They behave like (blocking) 1-place buffers modelling the shared-memory. The first developed translation uses an extra private MVar for every communication.We also automatically generate and check potentially correct translations that reuse the MVars where one MVar contains the message and two additional MVars for synchronization are used to model the synchronized communication of a single channel in the pi-calculus.Our automated experimental results lead to the conjecture that one additional MVar is insufficient., Comment: In Proceedings EXPRESS/SOS 2020, arXiv:2008.12414

This paper is a contribution to exploring and analyzing space-improvements in concurrent programming languages, in particular in the functional process-calculus CHF. Space-improvements are defined as a generalization of the corresponding notion in deterministic pure functional languages. The main part of the paper is the O(n*log n) algorithm SpOptN for offline space optimization of several parallel independent processes. Applications of this algorithm are: (i) affirmation of space improving transformations for particular classes of program transformations; (ii) support of an interpreter-based method for refuting space-improvements; and (iii) as a stand-alone offline-optimizer for space (or similar resources) of parallel processes., Comment: In Proceedings WPTE 2018, arXiv:1902.07818

We explore space improvements in LRP, a polymorphically typed call-by-need functional core language. A relaxed space measure is chosen for the maximal size usage during an evaluation. It abstracts from the details of the implementation via abstract machines, but it takes garbage collection into account and thus can be seen as a realistic approximation of space usage. The results are: a context lemma for space improving translations and for space equivalences, all but one reduction rule of the calculus are shown to be space improvements, and for the exceptional one we show bounds on the space increase. Several further program transformations are shown to be space improvements or space equivalences in particular the translation into machine expressions is a space equivalence. We also classify certain space-worsening transformations as space-leaks or as space-safe. These results are a step forward in making predictions about the change in runtime space behavior of optimizing transformations in call-by-need functional languages., Comment: In Proceedings WPTE 2017, arXiv:1802.05862

We present an implementation of an interpreter LRPi for the call-by-need calculus LRP, based on a variant of Sestoft's abstract machine Mark 1, extended with an eager garbage collector. It is used as a tool for exact space usage analyses as a support for our investigations into space improvements of call-by-need calculi., Comment: In Proceedings WPTE 2016, arXiv:1701.00233

A sound and complete algorithm for nominal unification of higher-order expressions with a recursive let is described, and shown to run in non-deterministic polynomial time. We also explore specializations like nominal letrec-matching for plain expressions and for DAGs and determine the complexity of corresponding unification problems., Comment: Pre-proceedings paper presented at the 26th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2016), Edinburgh, Scotland UK, 6-8 September 2016 (arXiv:1608.02534)

Correctness of program transformations in extended lambda calculi with a contextual semantics is usually based on reasoning about the operational semantics which is a rewrite semantics. A successful approach to proving correctness is the combination of a context lemma with the computation of overlaps between program transformations and the reduction rules, and then of so-called complete sets of diagrams. The method is similar to the computation of critical pairs for the completion of term rewriting systems. We explore cases where the computation of these overlaps can be done in a first order way by variants of critical pair computation that use unification algorithms. As a case study we apply the method to a lambda calculus with recursive let-expressions and describe an effective unification algorithm to determine all overlaps of a set of transformations with all reduction rules. The unification algorithm employs many-sorted terms, the equational theory of left-commutativity modelling multi-sets, context variables of different kinds and a mechanism for compactly representing binding chains in recursive let-expressions., Comment: In Proceedings UNIF 2010, arXiv:1012.4554

A non-deterministic call-by-need lambda-calculus \calc with case, constructors, letrec and a (non-deterministic) erratic choice, based on rewriting rules is investigated. A standard reduction is defined as a variant of left-most outermost reduction. The semantics is defined by contextual equivalence of expressions instead of using $\alpha\beta(\eta)$-equivalence. It is shown that several program transformations are correct, for example all (deterministic) rules of the calculus, and in addition the rules for garbage collection, removing indirections and unique copy. This shows that the combination of a context lemma and a meta-rewriting on reductions using complete sets of commuting (forking, resp.) diagrams is a useful and successful method for providing a semantics of a functional programming language and proving correctness of program transformations.