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An Experimental Protocol for Analyzing the Accuracy of Software Error Impact Analysis

Vincenzo Musco 1 Martin Monperrus 2 Philippe Preux 1
1 SEQUEL - Sequential Learning
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
2 SPIRALS - Self-adaptation for distributed services and large software systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : In software engineering, error impact analysis consists in predicting the software elements (e.g. modules, classes, methods) potentially impacted by a change. Impact analysis is required to optimize the testing effort. In this paper we present a new protocol to analyze the accuracy of impact analysis. This protocol uses mutation testing to simulate changes that introduce errors. To this end, we introduce a variant of call graphs we name the "use graph" of a software which may be computed efficiently. We apply this protocol to two open-source projects and correctly predict the impact of 30% to 49% of changes.
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https://hal.inria.fr/hal-01120913
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Submitted on : Friday, February 27, 2015 - 5:17:02 PM
Last modification on : Wednesday, March 23, 2022 - 3:51:21 PM
Long-term archiving on: : Friday, May 29, 2015 - 11:15:58 AM

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Vincenzo Musco, Martin Monperrus, Philippe Preux. An Experimental Protocol for Analyzing the Accuracy of Software Error Impact Analysis. Tenth IEEE/ACM International Workshop on Automation of Software Test, May 2015, Florence, Italy. ⟨10.1109/AST.2015.20⟩. ⟨hal-01120913⟩

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