Lisa Burnell and Eric Horvitz
To date, software engineers charged with debugging complex software packages have had few automated reasoning tools to assist them with identifying the sources of error and with prioritizing their effort. We describe methods, based on a synthesis of logical and probabilistic reasoning, that can be employed to identify the likely source and location of problems in complex software. The methods have been applied to diagnosing run-time errors in the Sabre system, the largest timeshared reservation system in the world. The results from our validation suggest that such methods can be of value in directing the attention of software engineers to program execution paths and program instructions that have the highest likelihood of harboring a programming error.
Publisher Association for Computing Machinery, Inc.
Copyright © 1995 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or email@example.com. The definitive version of this paper can be found at ACM’s Digital Library –http://www.acm.org/dl/.