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pro vyhledávání: '"Jason R. Koenig"'
Publikováno v:
Proceedings of the ACM on Programming Languages. 6:1-29
Many invariant inference techniques reason simultaneously about states and predicates, and it is well-known that these two kinds of reasoning are in some sense dual to each other. We present a new formal duality between states and predicates, and use
Publikováno v:
PLDI
We consider the problem of program synthesis from input-output examples via stochastic search. We identify a robust feature of stochastic synthesis: The search often progresses through a series of discrete plateaus. We observe that the distribution o
Publikováno v:
PLDI
Quantified first-order formulas, often with quantifier alternations, are increasingly used in the verification of complex systems. While automated theorem provers for first-order logic are becoming more robust, invariant inference tools that handle q
Autor:
Jason R. Koenig, K. Rustan M. Leino
Publikováno v:
Electronic Proceedings in Theoretical Computer Science, Vol 209, Iss Proc. Refine 2015, Pp 87-106 (2016)
Refine@FM
Refine@FM
Algorithmic and data refinement are well studied topics that provide a mathematically rigorous approach to gradually introducing details in the implementation of software. Program refinements are performed in the context of some programming language,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc622c5da830a608c94fa704c54fe793
http://arxiv.org/abs/1606.02022
http://arxiv.org/abs/1606.02022
Autor:
Dana Fisman, Grigore Rosu
This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the Europea