Developing multithreaded techniques and improved constraint handling for the tool CAgen

Published

June 8, 2022

Author(s)

Michael Wagner, Manuel Leithner, Dimitris Simos, D. Richard Kuhn, Raghu N. Kacker

Abstract

CAgen is a state-of-the-art combinatorial test generation tool that is known for its execution speed. In addition, it supports an extensive list of features such as constraint handling, higher-index arrays, and import and export of models/test sets in various different formats. It is based on the FIPO algorithm, which can be considered an improved version of the widely used In-Parameter-Order strategy. In order to further speed up CAgen, this work first discusses how multithreading can be effectively used to optimally utilize available resources, particularly for large instances. We evaluate three different multithreaded variations of the horizontal extension and use the obtained insights to design the mFIPOG algorithm. In addition, we adopt methods that have previously been utilized to speed up constraint handling of CSP solvers in IPO algorithms into a forbidden tuple approach. In order to evaluate the performance of the improved tool, we provide results of benchmarks on the instances offered by the CT competition of IWCT 2022.

Proceedings Title

2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)

Conference Dates

April 4, 2022

Conference Location

Valencia, ES

Conference Title

11th International Workshop on Combinatorial Testing

Pub Type

Conferences

Download Paper

https://doi.org/10.1109/ICSTW55395.2022.00029

Local Download

Keywords

test generation , multithreading , in parameter order , combinatorial testing , constraints

Citation

Wagner, M. , Leithner, M. , Simos, D. , Kuhn, D. and Kacker, R. (2022), Developing multithreaded techniques and improved constraint handling for the tool CAgen, 2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), Valencia, ES, [online], https://doi.org/10.1109/ICSTW55395.2022.00029, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934229 (Accessed December 4, 2024)