Entropy based enhanced particle swarm optimization on multi‐objective software reliability modelling for optimal testing resources allocation

Rani, Pooja; Mahapatra, G. S.

doi:10.1002/stvr.1765

Cited by 4 publications

(2 citation statements)

References 61 publications

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“…Anand et al 9 discussed the optimal allocation of test resources for two versions considering the multiup gradation phenomenon. Nagarju et al Rani and Mahapatra 12 proposed a multiobjective software reliability model of testing resources using a generalized exponential reliability function to define dynamic allocation of total testing effort and expected cost. Das et al 13 presented a continuous time software reliability model for error generation in each fault based on the nonhomogeneous Poisson process (NHPP) assumption for periodic debugging, in which errors are rectified at prespecified debugging periods rather than at the time of detection.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Saxena

Kumar

Ram

2022

Quality & Reliability Eng

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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.

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Section: Literature Reviewmentioning

confidence: 99%

“…Rani and Mahapatra 12 proposed a multiobjective software reliability model of testing resources using a generalized exponential reliability function to define dynamic allocation of total testing effort and expected cost. Das et al 13 .…”

Section: Literature Reviewmentioning

confidence: 99%

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

Saxena

Kumar

Ram

2022

Quality & Reliability Eng

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On Estimating the Feasible Solution Space of Multi-Objective Testing Resource Allocation

Zhang,

Li,

et al. 2024

ACM Trans. Softw. Eng. Methodol.

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The multi-objective testing resource allocation problem (MOTRAP) is concerned on how to reasonably plan the testing time of software testers to save the cost and improve the reliability as much as possible. The feasible solution space of a MOTRAP is determined by its variables (i.e., the time invested in each component) and constraints (e.g., the pre-specified reliability, cost, or time). Although a variety of state-of-the-art constrained multi-objective optimisers can be used to find individual solutions in this space, their search remains inefficient and expensive due to the fact that this space is very tiny compare to the large search space. The decision maker may often suffer a prolonged but unsuccessful search that fails to return a feasible solution. In this work, we first formulate a heavily constrained MOTRAP on the basis of an architecture-based model, in which reliability, cost, and time are optimised under the pre-specified multiple constraints on reliability, cost, and time. Then, to estimate the feasible solution space of this specific MOTRAP, we develop theoretical and algorithmic approaches to deduce new tighter lower and upper bounds on variables from constraints. Importantly, our approach can help the decision maker identify whether their constraint settings are practicable, and meanwhile, the derived bounds can just enclose the tiny feasible solution space and help off-the-shelf constrained multi-objective optimisers make the search within the feasible solution space as much as possible. Additionally, to further make good use of these bounds, we propose a generalised bound constraint handling method that can be readily employed by constrained multi-objective optimisers to pull infeasible solutions back into the estimated space with theoretical guarantee. Finally, we evaluate our approach on application and empirical cases. Experimental results reveal that our approach significantly enhances the efficiency, effectiveness, and robustness of off-the-shelf constrained multi-objective optimisers and state-of-the-art bound constraint handling methods at finding high-quality solutions for the decision maker. These improvements may help the decision maker take the stress out of setting constraints and selecting constrained multi-objective optimisers and facilitate the testing planning more efficiently and effectively.

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Suggesting Exit Path in a Multi-Path in Case of an Emergency

Vignesh,

Kumar,

Mukhopadhyay

et al. 2024

2024 11th International Conference on Computing for Sustainable Global Development (INDIACom)

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Entropy based enhanced particle swarm optimization on multi‐objective software reliability modelling for optimal testing resources allocation

Cited by 4 publications

References 61 publications

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

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

On Estimating the Feasible Solution Space of Multi-Objective Testing Resource Allocation

Suggesting Exit Path in a Multi-Path in Case of an Emergency

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