Carbon-Box Testing

Sangharatna Godboley, G. Monika Rani, Sindhu Nenavath

2023

Abstract

Combinatorial testing tools can be used to generate test cases automatically. The existing methodologies such as Random Testing etc. have always the scope of achieving better branch coverage. This is because most of the time the boundary values which are corner cases have been ignored to consider, as a result, we achieve low branch coverage. In this paper, we present a new type of testing type named Carbon-Box Testing. This Carbon name justifies the influence of Black-Box testing techniques we use with a lightweight White-Box testing technique. We show the strength of our proposed method i.e. Dictionary Testing to enhance the branch coverage. In Dictionary Testing, we trace the input variables and their dependent values statically and use them as test inputs. This is a fact that utilizing the statically extracted values is insufficient for achieving the maximal Branch coverage, hence we consider Random Testing to generate the test inputs. The initial values are the real-time Linux process ids, and then we perform mini-fuzzing with basic arithmetic operations to produce more test inputs. Pairwise testing or 2-way testing in Combinatorial testing is a well-known black-box testing technique. It requires a set of test inputs so that it can apply the mechanism to produce new test inputs. Our main proposed approach involves the generation of test inputs for achieving Branch coverage from Random testing values, Dictionary testing values, and a combination of both Random as well as Dictionary values with and without pairwise testing values. We have evaluated the effectiveness of our proposed approach using several experimental studies with baselines. The experimental results, on average, show that among all the approaches, the fusion of Random and Dictionary tests with Pairwise testing has superior results. Hence, this paper shows a new technique which is a healthy combination of two black-box and one white-box testing techniques which leads to Carbon-Box Testing.

Paper Citation

in Harvard Style

Godboley S., Monika Rani G. and Nenavath S. (2023). Carbon-Box Testing. In Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-647-7, SciTePress, pages 314-321. DOI: 10.5220/0011768900003464

in Bibtex Style

@conference{enase23,
author={Sangharatna Godboley and G. Monika Rani and Sindhu Nenavath},
title={Carbon-Box Testing},
booktitle={Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2023},
pages={314-321},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011768900003464},
isbn={978-989-758-647-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Carbon-Box Testing
SN - 978-989-758-647-7
AU - Godboley S.
AU - Monika Rani G.
AU - Nenavath S.
PY - 2023
SP - 314
EP - 321
DO - 10.5220/0011768900003464
PB - SciTePress