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タイトルHigh-Level Data Races
本文(外部サイト)http://hdl.handle.net/2060/20030015242
著者(英)Artho, Cyrille; Koga, Dennis; Biere, Armin; Havelund, Klaus
著者所属(英)Eidgenoessische Technische Hochschule
発行日2003-01-01
言語eng
内容記述Data races are a common problem in concurrent and multi-threaded programming. They are hard to detect without proper tool support. Despite the successful application of these tools, experience shows that the notion of data race is not powerful enough to capture certain types of inconsistencies occurring in practice. In this paper we investigate data races on a higher abstraction layer. This enables us to detect inconsistent uses of shared variables, even if no classical race condition occurs. For example, a data structure representing a coordinate pair may have to be treated atomically. By lifting the meaning of a data race to a higher level, such problems can now be covered. The paper defines the concepts view and view consistency to give a notation for this novel kind of property. It describes what kinds of errors can be detected with this new definition, and where its limitations are. It also gives a formal guideline for using data structures in a multi-threading environment.
NASA分類Computer Programming and Software
権利Copyright, Distribution as joint owner in the copyright
URIhttps://repository.exst.jaxa.jp/dspace/handle/a-is/223689


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