Modified Harris Hawks Optimization Based Test Case Prioritization for Software Testing

Abstract

Generally, software testing is considered as a proficient technique to achieve improvement in quality and reliability of the software. But, the quality of test cases has a considerable influence on fault revealing capability of software testing activity. Test Case Prioritization (TCP) remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected (APFD) and time spent upon execution results. TCP is mainly intended to design a collection of test cases that can accomplish early optimization using preferred characteristics. The studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection rate during software testing. In this aspect, the current study designs a Modified Harris Hawks Optimization based TCP (MHHO-TCP) technique for software testing. The aim of the proposed MHHO-TCP technique is to maximize APFD and minimize the overall execution time. In addition, MHHO algorithm is designed to boost the exploration and exploitation abilities of conventional HHO algorithm. In order to validate the enhanced efficiency of MHHO-TCP technique, a wide range of simulations was conducted on different benchmark programs and the results were examined under several aspects. The experimental outcomes highlight the improved efficiency of MHHO-TCP technique over recent approaches under different measures.

Directed Search Based on Improved Whale Optimization Algorithm for Test Case Prioritization

“…Anu and Sangwan [24] use the bat algorithm to research the TCP problem, and their results are greatly improved compared to traditional methods. Manar et al [25] designed an improved Harris Hawk optimization algorithm to improve prioritizing efficiency in many ways. Bajaj et al [26] used the discrete cuckoo search algorithm and introduced the adaptive strategy of asexual reproduction to reasonably improve the solutions.…”

A mixed Harris hawks optimization algorithm based on the pinhole imaging strategy for solving numerical optimization problems

“…The multi-strategy Harris hawks optimization algorithm proposed by Abbasi et al [27] was used to solve the tapered roller bearing design problem, which confirmed the effectiveness of the algorithm under complex and variable constraints. The improved HHO algorithm proposed by Hamza et al [28] was used to optimize the prioritization of software testing, and the experimental results highlighted the high efficiency of the MHHO-TCP technique. The improved gradient-based HHO algorithm proposed by Abailigah et al [29] solves practical engineering problems, and uses the sine and cosine function to improve the convergence speed of the HHO algorithm, so that the improved algorithm can maintain excellent search ability in iterations.…”