Hidden Bibliographic Details
| Other authors / contributors: | Association for Computing Machinery.
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| ISBN: | 9783540718789
3540718788
354071877X
9783540718772
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| Notes: | Includes bibliographical references (pages 97-101).
Print version record.
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| Summary: | 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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| Other form: | Print version: Liblit, Ben. Cooperative bug isolation. Berlin ; New York : Springer, ©2007 9783540718772 354071877X
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| Standard no.: | 10.1007/978-3-540-71878-9
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