Yuri Gurevich – författare

This is the most comprehensive treatment available in book form of the classical decision problem of mathematical logic and of the role of the classical decision problem in modern computer science. A revealing analysis of the natural order of decidable and undecidable cases is given. The complete classification of the solvable and unsolvable standard cases of the classical decision problem will be of particular interest to the reader. The classification comes complete with the complexity analysis of the solvable cases, with the comprehensive treatment of the reduction method, and with the model-theoretical analysis of solvable cases. Many cases are treated here for the first time, and a great number of simple proofs and exercises have been included. The results and methods of the book are extensively used in logic, computer science and artificial intelligence.

This volume contains the final versions of a collection of papers presented at the Annual Conference of the European Association for Computer Science Logic, CSL '93, held at Swansea, UK in September 1993.The 21 full papers included were selected from a total of 62 submissions and essentially contribute to the whole area of computer science logic research. They are devoted to such topics as set constraints, lambda calculi, process algebras, program semantics, intuitionistic logics, fixed-point logics, the equivalence problem, Horn clauses, quantifiers, and proof tranformations.

This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Abstract State Machines, ASM 2000, held in Monte Verita, Switzerland in March 2000. The 12 revised full papers presented were carefully reviewed and selected from 30 submissions. Also included are an introductory overview, two reports on industrial ASM applications, as well as six contributions based on invited talks. All in all, the volume competently presents the state of the art in research and applications of abstract state machines.

To prove the correctness of a program is to demonstrate, through impeccable mathematical techniques, that it has no bugs. To test a program is to run it with the expectation of discovering bugs. These two paths to software reliability seem to diverge from the very start: if you have proved your program correct, it is fruitless to comb it for bugs; and if you are testing it, that surely must be a sign that you have given up on any hope to prove its correctness. Accordingly, proofs and tests have, since the onset of software engineering research, been pursued by distinct communities using different kinds of techniques and tools. Dijkstra’s famous pronouncement that tests can only show the presence of errors — in retrospect, perhaps one of the best advertisements one can imagine for testing, as if “only” finding bugs were not already a momentous achievement! — didn’t help make testing popular with provers, or proofs attractive to testers. And yet the development of both approaches leads to the discovery of common issues and to the realization that each may need the other. The emergence of model checking was one of the first signs that apparent contradiction may yield to complementarity; in the past few years an increasing number of research efforts have encountered the need for combining proofs and tests, dropping earlier dogmatic views of incompatibility and taking instead the best of what each of these software engineering domains has to offer.