From Automated Software Testing to Likely Program Invariant Generation
Koushik Sen

Citation
Koushik Sen. "From Automated Software Testing to Likely Program Invariant Generation". Talk or presentation, 18, March, 2008.

Abstract
Testing with manually generated test cases is the primary technique used in industry to improve reliability of software--in fact, such testing is reported to account for over half of the typical cost of software development. I will describe Concolic Testing, a systematic and efficient method which combines random and symbolic testing. Concolic testing enables automatic and systematic testing of large programs, avoids redundant test cases and does not generate false warnings. Experiments on real-world software show that concolic testing can be used to effectively catch generic errors such as assertion violations, memory leaks, uncaught exceptions, and segmentation faults. In the second part of my talk, I will present a novel application of concolic testing to generate likely data structure invariants.

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• HTML

  Koushik Sen. <a
  href="http://chess.eecs.berkeley.edu/pubs/406.html"
  ><i>From Automated Software Testing to Likely
  Program Invariant Generation</i></a>, Talk or
  presentation,  18, March, 2008.

• Plain text

  Koushik Sen. "From Automated Software Testing to Likely
  Program Invariant Generation". Talk or presentation, 
  18, March, 2008.

• BibTeX

  @presentation{Sen08_FromAutomatedSoftwareTestingToLikelyProgramInvariant,
      author = {Koushik Sen},
      title = {From Automated Software Testing to Likely Program
                Invariant Generation},
      day = {18},
      month = {March},
      year = {2008},
      abstract = {Testing with manually generated test cases is the
                primary technique used in industry to improve
                reliability of software--in fact, such testing is
                reported to account for over half of the typical
                cost of software development. I will describe
                Concolic Testing, a systematic and efficient
                method which combines random and symbolic testing.
                Concolic testing enables automatic and systematic
                testing of large programs, avoids redundant test
                cases and does not generate false warnings.
                Experiments on real-world software show that
                concolic testing can be used to effectively catch
                generic errors such as assertion violations,
                memory leaks, uncaught exceptions, and
                segmentation faults. In the second part of my
                talk, I will present a novel application of
                concolic testing to generate likely data structure
                invariants.},
      URL = {http://chess.eecs.berkeley.edu/pubs/406.html}
  }
  

Posted by Douglas Densmore on 17 Mar 2008.
Groups: chess
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