From symptom to cause

Author:

Ball Thomas1,Naik Mayur2,Rajamani Sriram K.1

Affiliation:

1. Microsoft Research

2. Purdue University

Abstract

There is significant room for improving users' experiences with model checking tools. An error trace produced by a model checker can be lengthy and is indicative of a symptom of an error. As a result, users can spend considerable time examining an error trace in order to understand the cause of the error. Moreover, even state-of-the-art model checkers provide an experience akin to that provided by parsers before syntactic error recovery was invented: they report a single error trace per run. The user has to fix the error and run the model checker again to find more error traces.We present an algorithm that exploits the existence of correct traces in order to localize the error cause in an error trace, report a single error trace per error cause, and generate multiple error traces having independent causes. We have implemented this algorithm in the context of slam , a software model checker that automatically verifies temporal safety properties of C programs, and report on our experience using it to find and localize errors in device drivers. The algorithm typically narrows the location of a cause down to a few lines, even in traces consisting of hundreds of statements.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

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2. Counterexample classification;Software and Systems Modeling;2023-07-26

3. MC-FLoc: Learning from Traces to Locate Fault in Petri Net Model Checking;2022 IEEE 33rd International Symposium on Software Reliability Engineering (ISSRE);2022-10

4. A Debugging Game for Probabilistic Models;Formal Aspects of Computing;2022-06-30

5. Theoretical Analysis and Empirical Study on the Impact of Coincidental Correct Test Cases in Multiple Fault Localization;IEEE Transactions on Reliability;2022-06

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