A Comprehensive Study of Pseudo-tested Methods

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

Document type :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1007/s10664-018-9653-2

Title :

A Comprehensive Study of Pseudo-tested Methods

Author(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]

Journal title :

Empirical Software Engineering

Pages :

1-33

Publisher :

Springer Verlag

Publication date :

2018

ISSN :

1382-3256

HAL domain(s) :

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

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Popular science :

Non

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