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Cooperative Bug Isolation [electronic resource] :Winning Thesis of the 2005 ACM Doctoral Dissertation Competition / by Ben Liblit.

by Liblit, Ben [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 4440Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.Description: XV, 101p. online resource.ISBN: 9783540718789.Subject(s): Computer science | Software engineering | Computer software | Logic design | Computer Science | Software Engineering | Logics and Meanings of Programs | Algorithm Analysis and Problem ComplexityDDC classification: 005.1 Online resources: Click here to access online
Contents:
Instrumentation Framework -- Practical Considerations -- Techniques for Statistical Debugging -- Related Work -- Conclusion.
In: Springer eBooksSummary: This monograph constitutes a thoroughly revised and extended version of the author's PhD thesis, which was selected as the winning thesis of the 2005 ACM Doctoral Dissertation Competition. Ben Liblit did his PhD work at the University of California, Berkeley, with Alexander Aiken as thesis adviser. This monograph reconsiders two common assumptions about how we should analyze software and arrives at some striking new results. This new approach makes use of some of the tools that biologists and economists use to understand their complicated systems by considering programs as statistical processes and using statistical techniques to understand software. The centerpiece of the monograph is an algorithm for isolating multiple bugs from sparsely sampled data taken from many thousands of program executions. This algorithm has unique properties that complement other program analysis techniques; in particular, it is potentially able to find the root cause of any program failure without first requiring an explicit specification of the property to check. The results Ben Liblit presents with his thesis represent a new and fundamental approach to software analysis and will provide a source of ideas and inspiration to the field for many years to come.
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Instrumentation Framework -- Practical Considerations -- Techniques for Statistical Debugging -- Related Work -- Conclusion.

This monograph constitutes a thoroughly revised and extended version of the author's PhD thesis, which was selected as the winning thesis of the 2005 ACM Doctoral Dissertation Competition. Ben Liblit did his PhD work at the University of California, Berkeley, with Alexander Aiken as thesis adviser. This monograph reconsiders two common assumptions about how we should analyze software and arrives at some striking new results. This new approach makes use of some of the tools that biologists and economists use to understand their complicated systems by considering programs as statistical processes and using statistical techniques to understand software. The centerpiece of the monograph is an algorithm for isolating multiple bugs from sparsely sampled data taken from many thousands of program executions. This algorithm has unique properties that complement other program analysis techniques; in particular, it is potentially able to find the root cause of any program failure without first requiring an explicit specification of the property to check. The results Ben Liblit presents with his thesis represent a new and fundamental approach to software analysis and will provide a source of ideas and inspiration to the field for many years to come.

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