Determination of parameters for test case optimization in adaptive cuckoo search technique: a fuzzy Delphi analysis

James Maina Mburu, John Gichuki Ndia, Samson Wanjala Munialo

Abstract


Cuckoo Search Algorithm (CSA) is one of the metaheuristic approaches applied by existing studies in test case optimization due to its simplicity and ease of implementation.  However, the current studies lack systematic documentation and empirical validation of parameters thus limiting optimization efficiency and reproducibility. To solve this gap, the study introduces expert consensus on vital parameters for designing the Enhanced Adaptive Cuckoo Search Technique (EACST) through a planned Parameter Selection and Validation Framework. The study conducted an expert opinion survey involving 56 software testing professionals, where parameters were identified through an extensive literature review and polished using expert responses. These responses were analyzed using the Fuzzy Delphi Method which incorporates a consensus thresholds  and defuzzification to assess agreement and rank parameters. The findings indicate that all parameters identified satisfy the threshold condition and attained consensus levels above 75%, with an overall agreement of 91%, indicating strong expert consensus. All parameters were accepted (α-cut ≥ 0.5), demonstrating their suitability for inclusion in the proposed technique. These results provide a structured and reproducible framework for selecting parameters, which supports an enhanced balance between exploration and exploitation in test case optimization. Nevertheless, the study is constrained to expert-based evaluation and needs further experimental validation through implementation and evaluation. The framework is worth of configuring adaptive metaheuristic techniques and represents a new integration of literature-based parameter selection with Fuzzy Delphi analysis, bridging the gap between theoretical identification and practical implementation.

 

Received 09 April 2026

Accepted 01 June 2026

Published 07 June 2026


Keywords


Enhanced Adaptive Cuckoo Search Technique (EACST);Expert Consensus;Exploration–Exploitation Balance;Fuzzy Delphi Method; Model-Based Testing;Parameter Selection;Software Testing;Test Case Optimization.

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References


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DOI: https://dx.doi.org/10.21622/ACE.2026.06.1.2069

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Copyright (c) 2026 James Maina Mburu, John Gichuki Ndia, Samson Wanjala Munialo

Advances in Computing and Engineering

E-ISSN: 2735-5985

P-ISSN: 2735-5977

 

Published by:

Academy Publishing Center (APC)

Arab Academy for Science, Technology and Maritime Transport (AASTMT)

Alexandria, Egypt

ace@aast.edu