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Advances in Computing and Information — ICCI '90: by S. G. Akl, F. Fiala, W. W. Koczkodaj (eds.)

By S. G. Akl, F. Fiala, W. W. Koczkodaj (eds.)

This quantity comprises chosen and invited papers awarded on the overseas convention on Computing and knowledge, ICCI '90, Niagara Falls, Ontario, Canada, may perhaps 23-26, 1990. ICCI meetings supply a world discussion board for offering new leads to study, improvement and purposes in computing and knowledge. Their basic objective is to advertise an interchange of principles and cooperation among practitioners and theorists within the interdisciplinary fields of computing, verbal exchange and knowledge concept. The 4 major subject components of ICCI '90 are: - details and coding concept, statistics and likelihood, - Foundations of desktop technological know-how, concept of algorithms and programming, - Concurrency, parallelism, communications, networking, computing device structure and VLSI, - info and software program engineering, databases, specialist platforms, info structures, selection making, and AI methodologies.

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4] Leendert van Doorn, Mart´ın Abadi, Mike Burrows, and Edward Wobber. Secure network objects. In Proceedings of the 1996 IEEE Symposium on Security and Privacy, pages 211–221, May 1996. L. ): ECOOP 2003, LNCS 2743, p. 1, 2003. ca Abstract. Modeling four aspect-oriented programming mechanisms shows the way in which each supports modular crosscutting. Comparing the models produces a clear three part characterization of what is required to support crosscutting structure: a common frame of reference that two (or more) programs can use to connect with each other and each provide their semantic contribution.

The programs are analogous to our specifications in that our specifications are high-level descriptions of examples. Algorithmic program debugging [42] is similar to automatic programming and uses an inductive inference procedure to test side-effect and loop-free programs based on input output examples and then helps users to interactively correct the bugs in the program. Unlike the above techniques whose goals are to generate programs or find bugs, the goal of our system is to generate formal specifications (which could, of course, be used to generate programs or find bugs).

The programs are analogous to our specifications in that our specifications are high-level descriptions of examples. Algorithmic program debugging [42] is similar to automatic programming and uses an inductive inference procedure to test side-effect and loop-free programs based on input output examples and then helps users to interactively correct the bugs in the program. Unlike the above techniques whose goals are to generate programs or find bugs, the goal of our system is to generate formal specifications (which could, of course, be used to generate programs or find bugs).

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