Proposed Method of Seeding and Constraint in One-Parameter-At-a- Time Approach for t-way Testing

Muazu, Aminu Aminu; Hashim, Ahmad Mustafa; Sarlan, Aliza; Maiwada, Umar Danjuma

doi:10.1109/icdi57181.2022.10007210

Cited by 2 publications

(1 citation statement)

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“…Consequently, test case generation stands out as the most dynamically advancing research area within combinatorial t-way testing, with the added complexity of being classified as NP-hard. In response to this challenge, researchers are increasingly focusing on the development of various pairwise strategies to tackle this issue, aiming to derive an optimal test suite solution [38]. The formulation for generating test cases in combinatorial interaction testing can be articulated as: F=K1×K2×K3×K4×K5 ... ×Kn.…”

Section: Pairwise Test Case Generationmentioning

confidence: 99%

Pairwise test case generation with harmony search, one-parameter-at-at-time, seeding, and constraint mechanism integration

Aminu Muazu,

Hashim,

Maiwada

et al. 2024

IJECE

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Pairwise testing is a method for identifying defects through combinatorial analysis. It involves testing all possible combinations of input parameters in pairs within a system, ensuring that each pair is tested at least once. The field of test case generation is highly active in the realm of combinatorial interaction testing. Research in this area is particularly encouraged, as it falls under the category of non-deterministic polynomial-time hardness. A big challenge in this field is the combinatorial explosion problem. It is about finding the best test suite that covers all possible combinations of interaction strength. In this paper, we present the task of discovering a pairwise test set as a search problem and introduce an innovative testing tool referred to as pairwise test case generation in harmony search algorithm with seeding and constraint mechanism (PHOSC). Experimental results show that PHOSC performs better compared to some existing pairwise strategies in terms of test suite size. Additionally, PHOSC provides a comprehensive framework and serves as a research platform for the generation of pairwise test sets employing the harmony search algorithm. It adopts an approach that focuses on one parameter at a time (OPAT) and incorporates seeding and constraint mechanisms at the same time, thereby enhancing the efficiency and effectiveness of the testing process.

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Section: Pairwise Test Case Generationmentioning

confidence: 99%