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Improving Continuous Integration with Similarity-based Test Case Selection

Fulltext:


Authors:

Francisco Gomes de Oliveira Neto , Azeem Ahmad , Ola Leifler , Kristian Sandhal , Eduard Paul Enoiu

Research groups:

Software Testing Laboratory
Formal Modelling and Analysis of Embedded Systems

Publication Type:

Conference/Workshop Paper

Venue:

13th IEEE/ACM International Workshop on Automation of Software Test

Abstract

Automated testing is an essential component of Continuous Integration (CI) and Delivery (CD), such as scheduling automated test sessions on overnight builds. That allows stakeholders to execute entire test suites and achieve exhaustive test coverage, since running all tests is often infeasible during work hours, i.e., in parallel to development activities. On the other hand, developers also need test feedback from CI servers when pushing changes, even if not all test cases are executed. In this paper we evaluate similarity-based test case selection (SBTCS) on integration-level tests executed on continuous integration pipelines of two companies. We select test cases that maximise diversity of test coverage and reduce feedback time to developers. Our results confirm existing evidence that SBTCS is a strong candidate for test optimisation, by reducing feedback time (up to 92% faster in our case studies) while achieving full test coverage using only information from test artefacts themselves.

Bibtex

@inproceedings{de Oliveira Neto5076,
author = {Francisco Gomes de Oliveira Neto and Azeem Ahmad and Ola Leifler and Kristian Sandhal and Eduard Paul Enoiu},
title = {Improving Continuous Integration with Similarity-based Test Case Selection},
month = {March},
year = {2018},
booktitle = {13th IEEE/ACM International Workshop on Automation of Software Test},
url = {http://www.es.mdu.se/publications/5076-}
}