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Enabling Program Analysis Through Deterministic Replay and Optimistic Hybrid Analysis

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서명/저자사항Enabling Program Analysis Through Deterministic Replay and Optimistic Hybrid Analysis.
개인저자Devecsery, David.
단체저자명University of Michigan. Computer Science & Engineering.
발행사항[S.l.]: University of Michigan., 2018.
발행사항Ann Arbor: ProQuest Dissertations & Theses, 2018.
형태사항115 p.
기본자료 저록Dissertation Abstracts International 79-12B(E).
Dissertation Abstract International
ISBN9780438126992
학위논문주기Thesis (Ph.D.)--University of Michigan, 2018.
일반주기 Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Peter M. Chen.
요약As software continues to evolve, software systems increase in complexity. With software systems composed of many distinct but interacting components, today's system programmers, users, and administrators find themselves requiring automated ways
요약In this thesis I focus on enabling practical entire-system retroactive analysis, allowing programmers, users, and system administrators to diagnose and understand the impact of these devastating mishaps. I focus primarly on two techniques. First
요약Record and replay systems greatly aid in solving a variety of problems, such as fault tolerance, forensic analysis, and information providence. These solutions, however, assume ubiquitous recording of any application which may have a problem. Cu
요약Dynamic analysis is used to retroactively identify and address many forms of system mis-behaviors including: programming errors, data-races, private information leakage, and memory errors. Unfortunately, the runtime overhead of dynamic analysis
요약In this thesis I demonstrate that Arnold's ability to record and replay entire computer systems, combined with optimistic hybrid analysis's ability to quickly analyze prior computation, enable a practical and useful entire system retroactive ana
일반주제명Computer science.
언어영어
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