A Comprehensive Study of Pseudo-tested Methods

Vera-Pérez, Oscar Luis; Danglot, Benjamin; Monperrus, Martin; Baudry, Benoit

Type de document :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1007/s10664-018-9653-2

Titre :

A Comprehensive Study of Pseudo-tested Methods

Auteur(s) :

Vera-Pérez, Oscar Luis [Auteur correspondant]
Diversity-centric Software Engineering [DiverSe]
Danglot, Benjamin [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Monperrus, Martin [Auteur]
KTH Royal Institute of Technology [Stockholm] [KTH]
Baudry, Benoit [Auteur]
KTH Royal Institute of Technology [Stockholm] [KTH]

Titre de la revue :

Empirical Software Engineering

Pagination :

1-33

Éditeur :

Springer Verlag

Date de publication :

2018

ISSN :

1382-3256

Discipline(s) HAL :

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

Résumé en anglais : [en]

Pseudo-tested methods are defined as follows: they are covered by the test suite, yet no test case fails when the method body is removed, i.e., when all the effects of this method are suppressed. This intriguing concept ...
Lire la suite >Pseudo-tested methods are defined as follows: they are covered by the test suite, yet no test case fails when the method body is removed, i.e., when all the effects of this method are suppressed. This intriguing concept was coined in 2016, by Niedermayr and colleagues, who showed that such methods are systematically present, even in well-tested projects with high statement coverage. This work presents a novel analysis of pseudo-tested methods. First, we run a replication of Niedermayr's study with 28K+ methods, enhancing its external validity thanks to the use of new tools and new study subjects. Second, we perform a systematic characterization of these methods, both quantitatively and qualitatively with an extensive manual analysis of 101 pseudo-tested methods. The first part of the study confirms Niedermayr's results: pseudo-tested methods exist in all our subjects. Our in-depth characterization of pseudo-tested methods leads to two key insights: pseudo-tested methods are significantly less tested than the other methods; yet, for most of them, the developers would not pay the testing price to fix this situation. This calls for future work on targeted test generation to specify those pseudo-tested methods without spending developer time.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :