Achievement of Minimized Combinatorial Test Suite for Configuration-Aware Software Functional Testing Using the Cuckoo Search Algorithm
Bestoun S. Ahmed, Taib Sh. Abdulsamad, Moayad Y. Potrus

TL;DR
This paper introduces a novel cuckoo search-based method to generate minimized combinatorial test suites, improving fault detection efficiency in configuration-aware software testing.
Contribution
It proposes a new cuckoo search algorithm for constructing optimized combinatorial test suites, advancing the application of metaheuristics in software testing.
Findings
Test suites effectively detect faults in real-world case studies.
The proposed method outperforms traditional sampling techniques.
Generated test suites are resource-efficient and comprehensive.
Abstract
Context: Software has become an innovative solution nowadays for many applications and methods in science and engineering. Ensuring the quality and correctness of software is challenging because each program has different configurations and input domains. To ensure the quality of software, all possible configurations and input combinations need to be evaluated against their expected outputs. However, this exhaustive test is impractical because of time and resource constraints due to the large domain of input and configurations. Thus, different sampling techniques have been used to sample these input domains and configurations. Objective: Combinatorial testing can be used to effectively detect faults in software-under-test. This technique uses combinatorial optimization concepts to systematically minimize the number of test cases by considering the combinations of inputs. This paper…
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