A Model for Spectra-based Software Diagnosis

Lee Naish, Hua Jie Lee, Kotagiri Ramamohanarao

This paper presents an improved approach to assist diagnosis of failures in software (fault localisation) by ranking program statements or blocks according to how likely they are to be buggy. We present a very simple single-bug program to model the problem. By examining different possible execution paths through this model program over a number of test cases, the effectiveness of different proposed spectral ranking methods can be evaluated in idealised conditions. The results are remarkably consistent to those arrived at empirically using the Siemens test suite and Space benchmarks. The model also helps identify groups of metrics which are equivalent for ranking. Due to the simplicity of the model, an optimal ranking method can be devised. This new method out-performs previously proposed methods for the model program, the Siemens test suite and Space. It also helps provide insight into other ranking methods.

The paper: PDF version
Note, the definitive version has appeared in ACM Transactions on Software Engineering and Methodology. It is substantially the same as the version here, though there are several minor corrections/improvements.
Related work: Spectral debugging with weights and incremental ranking , Statements versus predicates in spectral bug localization , Spectral debugging: How much better can we do? , Duals in Spectral Fault Localization , Jason's Thesis

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