Title: Deer-based chicken swarm optimisation algorithm: a hybrid optimisation algorithm for output domain testing

Authors: Ramgouda Patil; V. Chandraprakash

Addresses: Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India ' Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India

Abstract: An effective combinatorial test case generation framework is devised in this research using a hybrid optimisation algorithm, Deer-based Chicken Swarm Optimisation (DCSO) for generating test cases for output domain testing of embedded systems. The developed DCSO is the amalgamation of the Deer Hunting Optimisation Algorithm (DHOA) and Chicken Swarm Optimisation (CSO) algorithm. The three different worst-case resource usage scenarios are considered in this research as an objective. The worst-case resource usage scenario includes Worst-Case Execution Times (WCET), Worst-Case Suite Size (WCSS) and Worst-Case Stack Usage (WCSU). The developed DCSO algorithm is used for output domain testing of embedded systems by generating combinatorial test cases. Metrics, such as fitness and test suite size, are used for analysing the developed DCSO algorithm. The proposed DCSO algorithm obtained a minimum test suite size of 84 and minimum fitness of 3.66, respectively, on comparing with the existing test case generation methods.

Keywords: deer CSO; combinatorial testing; test case generation; embedded systems; output domain testing.

DOI: 10.1504/IJGUC.2023.135331

International Journal of Grid and Utility Computing, 2023 Vol.14 No.6, pp.654 - 666

Received: 12 Nov 2021
Received in revised form: 28 Nov 2022
Accepted: 28 Jan 2023
Published online: 05 Dec 2023 *

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