Demystifying the Combination of Dynamic Slicing and Spectrum-based Fault Localization

Sofia Reis, Rui Abreu, Marcelo d'Amorim

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

Main track. Pages 4760-4766.

https://doi.org/10.24963/ijcai.2019/661

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Abstract

Several approaches have been proposed to reduce debugging costs through

automated software fault diagnosis. Dynamic Slicing (DS) and Spectrum-based

Fault Localization (SFL) are popular fault diagnosis techniques and normally

seen as complementary. This paper reports on a comprehensive

study to reassess the effects of combining DS with SFL. With this

combination, components that are often involved in failing but seldom in passing

test runs could be located and their suspiciousness reduced.

Results show that the DS-SFL combination, coined

as Tandem-FL, improves the diagnostic accuracy up

to 73.7% (13.4% on average). Furthermore, results

indicate that the risk of missing faulty statements,

which is a DS?s key limitation, is not high ? DS

misses faulty statements in 9% of the 260 cases. To

sum up, we found that the DS-SFL combination

was practical and effective and encourage new SFL

techniques to be evaluated against that optimization.

Keywords

  • Multidisciplinary Topics and Applications: Knowledge-based Software Engineering
  • Multidisciplinary Topics and Applications: Validation and Verification
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