A Large-scale Study of Call Graph-based Impact Prediction using Mutation Testing

Musco, Vincenzo; Monperrus, Martin; Preux, Philippe

Document type :

Article dans une revue scientifique: Article original

DOI :

10.1007/s11219-016-9332-8

Title :

A Large-scale Study of Call Graph-based Impact Prediction using Mutation Testing

Author(s) :

Musco, Vincenzo [Auteur]
Sequential Learning [SEQUEL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université de Lille, Sciences et Technologies
Self-adaptation for distributed services and large software systems [SPIRALS]
Monperrus, Martin [Auteur]
Université de Lille, Sciences et Technologies
Self-adaptation for distributed services and large software systems [SPIRALS]
Preux, Philippe [Auteur]

Sequential Learning [SEQUEL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Journal title :

Software Quality Journal

Pages :

921–950

Publisher :

Springer Verlag

Publication date :

2017-09

ISSN :

0963-9314

English keyword(s) :

Mutation Testing
Change Impact Analysis
Call Graphs

HAL domain(s) :

Informatique [cs]
Informatique [cs]/Génie logiciel [cs.SE]

English abstract : [en]

In software engineering, impact analysis consists in predicting the software elements (e.g. modules, classes, methods) potentially impacted by a change in the source code. Impact analysis is required to optimize the testing ...
Show more >In software engineering, impact analysis consists in predicting the software elements (e.g. modules, classes, methods) potentially impacted by a change in the source code. Impact analysis is required to optimize the testing effort. In this paper, we propose a framework to predict error propagation. Based on 10 open-source Java projects and 5 classical mutation operators, we create 17000 mutants and study how the error they introduce propagates. This framework enables us to analyze impact prediction based on four types of call graph. Our results show that the sophistication indeed increases completeness of impact prediction. However, and surprisingly to us, the most basic call graph gives the highest trade-off between precision and recall for impact prediction.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

Files

https://hal.inria.fr/hal-01346046/document
Open access
Access the document

http://arxiv.org/pdf/1812.06286
Open access
Access the document

https://hal.inria.fr/hal-01346046/document
Open access
Access the document

https://hal.inria.fr/hal-01346046/document
Open access
Access the document

papersqj.pdf
Open access
Access the document

1812.06286
Open access
Access the document

document
Open access
Access the document

document
Open access
Access the document

papersqj.pdf
Open access
Access the document

A Large-scale Study of Call Graph-based ... BibTeX CSV Excel RIS

Files

A Large-scale Study of Call Graph-based ...

BibTeX

CSV

Excel

RIS