SOM-FTS: A Hybrid Model for Software Reliability Prediction and MCDM-Based Evaluation


  • Ajay Kumar University School of Information, Communication, and Technology (USICT), Guru Gobind Singh Indraprastha University, New Delhi, India
  • Kamaldeep Kaur University School of Information, Communication, and Technology (USICT), Guru Gobind Singh Indraprastha University, New Delhi, India



software reliability, multi-criteria decision making, WSM, TOPSIS, EDAS


The objective of this study is to propose a hybrid model based on self-organized maps (SOM) and fuzzy time series (FTS) for predicting the reliability of software systems. The proposed SOM-FTS model is compared with eleven traditional machine learning-based models. The problem of selecting a suitable software reliability prediction model is represented as a multi-criteria decision-making (MCDM) problem. Twelve software reliability prediction models, including the proposed SOM-FTS model, are evaluated using three MCDM methods, four performance measures, and three software failure datasets. The results show that the proposed SOM-FTS model is the most suitable model among the twelve software reliability prediction models on the basis of MCDM ranking.

Author Biography

Kamaldeep Kaur, University School of Information, Communication, and Technology (USICT), Guru Gobind Singh Indraprastha University, New Delhi, India

Assistant Professor



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How to Cite

A. Kumar and K. Kaur, “SOM-FTS: A Hybrid Model for Software Reliability Prediction and MCDM-Based Evaluation”, Int. j. eng. technol. innov., vol. 12, no. 4, pp. 308–321, Oct. 2022.