A synthesis of logical and probabilistic reasoning for program understanding and debugging

Authors:
Lisa J. Burnell;Eric J. Horvitz
Affiliations:
Computer Science Engineering, The University of Texas at Arlington and American Airlines Knowledge Systems, TX;Decision Theory Group, Microsoft Research Labs, Palo Alto Laboratory, Rockwell International Science Center, Palo Alto, CA
Venue:
UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence
Year:
1993

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Abstract

We describe the integration of logical and uncertain reasoning methods to identify the likely source and location of software problems. To date, software engineers have had few tools for identifying the sources of error in complex software packages. We describe a method for diagnosing software problems through combining logical and uncertain-reasoning analyses. Our preliminary results suggest that such methods can be of value in directing the attention of software engineers to paths of an algorithm that have the highest likelihood of harboring a programming error.