A novel CRITIC‐TOPSIS approach for optimal selection of software reliability growth model (SRGM)

Abstract

Various Software Reliability Growth Models (SRGMs) have been developed over last five decades to estimate the failure rate, software reliability and remaining number of faults in the software during testing phase of software development life cycle. There are numerous SRGMs available in the research literature and in the presence of numerous SRGM, appropriate selection is a staggering task for the software testing professionals. In the software reliability area, researchers have always been interested to select the optimal SRGM to use in a particular situation. In this study, we have developed an integrated technique based on Criteria Importance Through Inter Criteria Correlation (CRITIC) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to select the optimal SRGM. The weights of criteria are obtained by the CRITIC method and SRGMs are ranked by order using TOPSIS method. The working of proposed integrated CRITIC‐TOPSIS approach is illustrated on the two real‐time failure data sets. Furthermore, the methodology validation idea supports the current study by comparing the results obtained with the previous multi‐criteria decision making (MCDM) methodologies namely Additive Ratio Assessment (ARAS). The study revealed that the ranking of SRGMs can be solved effectively using the integration of CRITIC and TOPSIS. The result of this study plays a significant role to take decisions and to evaluate the feasibility of SRGM.

A Software Reliability Model Considering a Scale Parameter of the Uncertainty and a New Criterion

“…In MCDM, the most important issue is determining weights based on these criteria. Singh [27] recommended an approach using Monte Carlo simulation, and Saxena et al [28], Kumar et al [29], and Grag et al [30] used the entropy method to determine the criteria weights, and a technique for order preference by similarity to an ideal solution (TOPSIS) method was used to rank the criteria of SRMs. Our proposed integrated MCDMR reflects the ranking of each suitability among the methods to determine the weights.…”

T-Spherical Fuzzy-CRITIC-WASPAS Model for the Evaluation of Cooperative Intelligent Transportation System Scenarios

“…CRITIC's integration with the grey relational analysis for investment portfolio selection [43] and its implementation in the virtual reality metaverse for customer requirements ranking [44] demonstrated CRITIC's adaptability to different decision-making contexts. Saxena et al [45] demonstrated the importance of CRITIC in software engineering, particularly in the best selection of reliability growth models. Vadivel et al [46] emphasized the importance of CRITIC in sustainable supply chain management; i.e.…”

Modeling Software Release Time and Software Patch Release Time Based on Testing Effort and Warranty

“…Lee, Chang, and Pham (2020) presented a new SRGM including software failures that are interdependent. Few researchers have also used Multi-criteria decision making (MCDM) in SRGMs for the ranking of models (Bibyan and Anand 2022; Kumar, Saxena and Garg 2021;Saxena, Kumar and Ram 2022;Saxena, Kumar and Ram 2021).…”