research-article

Research on a Method of Software Reliability Prediction Model

Authors:

Kun Han,

Fei GaoAuthors Info & Claims

CSAI '18: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence

Pages 163 - 167

https://doi.org/10.1145/3297156.3297257

Published: 08 December 2018 Publication History

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Abstract

Software defects seriously affect software reliability. Software reliability is accurately predicted, which can guarantee normal use of software. For the prediction of software reliability, a software reliability prediction model based on support vector regression is constructed. Firstly, software metrics are extracted. Then data is preprocessed by the method of normalization and random sequence, and it is divided into training sets and testing sets for regression prediction; Secondly, the grid search method is introduced to optimize parameters in the support vector regression model; Finally, through experimental comparison and analysis, it is proved that this prediction method can indeed greatly improve the prediction accuracy of software reliability.

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Cited By

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Habtemariam GMohapatra SSeid HMishra D(2022)A Systematic Literature Review of Predicting Software Reliability Using Machine Learning TechniquesOptimization of Automated Software Testing Using Meta-Heuristic Techniques10.1007/978-3-031-07297-0_6(77-90)Online publication date: 27-Sep-2022
https://doi.org/10.1007/978-3-031-07297-0_6

Index Terms

Research on a Method of Software Reliability Prediction Model
1. Security and privacy
  1. Software and application security
    1. Software security engineering

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Published In

CSAI '18: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence

December 2018

641 pages

ISBN:9781450366069

DOI:10.1145/3297156

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shenzhen University: Shenzhen University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 December 2018

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CSAI '18

CSAI '18: 2018 2nd International Conference on Computer Science and Artificial Intelligence

December 8 - 10, 2018

Shenzhen, China

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Habtemariam GMohapatra SSeid HMishra D(2022)A Systematic Literature Review of Predicting Software Reliability Using Machine Learning TechniquesOptimization of Automated Software Testing Using Meta-Heuristic Techniques10.1007/978-3-031-07297-0_6(77-90)Online publication date: 27-Sep-2022
https://doi.org/10.1007/978-3-031-07297-0_6

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Software Reliability Prediction Based on Optimized Support Vector Regression