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Prediction of Software Reliability Using Particle Swarm Optimization

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Innovations in Intelligent Computing and Communication (ICIICC 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1737))

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Abstract

The quality of Software comprises many features constituting of software reliability. Estimating of software reliability in the initial stage of platform establishment will allow a software professional in originating tables well as defect long-suffering software. Testing and maintaining Software is terribly exorbitant and strenuous, and it has been predicted that about half of software establishment expenses are designated to validating of the software. In view of this we propose nature inspires methods of Particle Swarm Optimization (PSO) based model to predict software failure. The proposed model is compared with some existing benchmark techniques like Neural Networks (NN), Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbour (KNN), Random Forest, and genetic algorithm (GA). The dataset considered for experiments are taken from NASA Promise Software Engineering Repository projects. The prediction generated by PSO is more accurate as compared with other benchmark techniques.

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Authors and Affiliations

  1. Addis Ababa Science and Technology University Addis Ababa, Addis Ababa, Ethiopia

    Getachew Mekuria Habtemariam & Hussien Worku Seid

  2. Sri Sri University, Cuttack, Odisha, India

    Sudhir Kumar Mohapatra

Authors
  1. Getachew Mekuria Habtemariam
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  2. Sudhir Kumar Mohapatra
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  3. Hussien Worku Seid
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Corresponding author

Correspondence to Sudhir Kumar Mohapatra .

Editor information

Editors and Affiliations

  1. Utkal University, Bhubaneswar, Odisha, India

    Mrutyunjaya Panda

  2. Fakir Mohan University, Balasore, Odisha, India

    Satchidananda Dehuri

  3. Berhampur University, Berhampur, Odisha, India

    Manas Ranjan Patra

  4. Utkal University, Bhubaneswar, Odisha, India

    Prafulla Kumar Behera

  5. University of Piraeus, Piraeus, Greece

    George A. Tsihrintzis

  6. Yonsei University, Seoul, Korea (Republic of)

    Sung-Bae Cho

  7. CINVESTAV-IPN, Mexico City, Mexico

    Carlos A. Coello Coello

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Habtemariam, G.M., Mohapatra, S.K., Seid, H.W. (2022). Prediction of Software Reliability Using Particle Swarm Optimization. In: Panda, M., et al. Innovations in Intelligent Computing and Communication. ICIICC 2022. Communications in Computer and Information Science, vol 1737. Springer, Cham. https://doi.org/10.1007/978-3-031-23233-6_11

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  • DOI: https://doi.org/10.1007/978-3-031-23233-6_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23232-9

  • Online ISBN: 978-3-031-23233-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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