Title :

A Learning Algorithm for Change Impact Prediction

Author(s) :

Musco, Vincenzo [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Carette, Antonin [Auteur]
Université de Lille, Sciences et Technologies
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]

Conference title :

5th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering

City :

Austin

Country :

Etats-Unis d'Amérique

Start date of the conference :

2016-05-17

HAL domain(s) :

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

English abstract : [en]

Change impact analysis (CIA) consists in predicting the impact of a code change in a software application. In this paper, the artifacts that are considered for CIA are methods of object-oriented software; the change under ...
Show more >Change impact analysis (CIA) consists in predicting the impact of a code change in a software application. In this paper, the artifacts that are considered for CIA are methods of object-oriented software; the change under study is a change in the code of the method, the impact is the test methods that fail because of the change that has been performed. We propose LCIP, a learning algorithm that learns from past impacts to predict future impacts. To evaluate LCIP, we consider Java software applications that are strongly tested. We simulate 6000 changes and their actual impact through code mutations, as done in mutation testing. We find that LCIP can predict the impact with a precision of 74%, a recall of 85%, corresponding to a F-score of 64%. This shows that taking a learning perspective on change impact analysis let us achieve good precision and recall in change impact analysis.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