article

Comparing case-based reasoning classifiers for predicting high risk software components

Authors:

Khaled El Emam,

Saida Benlarbi,

Nishith Goel,

Shesh N. RaiAuthors Info & Claims

Journal of Systems and Software, Volume 55, Issue 3

Pages 301 - 320

https://doi.org/10.1016/S0164-1212(00)00079-0

Published: 15 January 2001 Publication History

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Cited By

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Hussain SIbrahim N(2022)Empirical Investigation of role of Meta-learning approaches for the Improvement of Software Development Process via Software Fault PredictionProceedings of the 26th International Conference on Evaluation and Assessment in Software Engineering10.1145/3530019.3531333(413-420)Online publication date: 13-Jun-2022
https://dl.acm.org/doi/10.1145/3530019.3531333
Wu DLi JBao C(2018)Case-based reasoning with optimized weight derived by particle swarm optimization for software effort estimationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-017-2985-922:16(5299-5310)Online publication date: 1-Aug-2018
https://dl.acm.org/doi/10.1007/s00500-017-2985-9
Mala D(2017)Investigating the Effect of Sensitivity and Severity Analysis on Fault Proneness in Open Source SoftwareInternational Journal of Open Source Software and Processes10.4018/IJOSSP.20170101038:1(42-66)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.4018/IJOSSP.2017010103
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Index Terms

Comparing case-based reasoning classifiers for predicting high risk software components
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Project and people management
      2. Software management
        Software maintenance
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
    2. Software post-development issues
  2. Software notations and tools
    1. Software configuration management and version control systems

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cover image Journal of Systems and Software

Journal of Systems and Software Volume 55, Issue 3

Jan.15.2001

99 pages

ISSN:0164-1212

Editor:
Robert L. Glass
Computing Trends, Bloomington, IN

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Elsevier Science Inc.

United States

Publication History

Published: 15 January 2001

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Hussain SIbrahim N(2022)Empirical Investigation of role of Meta-learning approaches for the Improvement of Software Development Process via Software Fault PredictionProceedings of the 26th International Conference on Evaluation and Assessment in Software Engineering10.1145/3530019.3531333(413-420)Online publication date: 13-Jun-2022
https://dl.acm.org/doi/10.1145/3530019.3531333
Wu DLi JBao C(2018)Case-based reasoning with optimized weight derived by particle swarm optimization for software effort estimationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-017-2985-922:16(5299-5310)Online publication date: 1-Aug-2018
https://dl.acm.org/doi/10.1007/s00500-017-2985-9
Mala D(2017)Investigating the Effect of Sensitivity and Severity Analysis on Fault Proneness in Open Source SoftwareInternational Journal of Open Source Software and Processes10.4018/IJOSSP.20170101038:1(42-66)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.4018/IJOSSP.2017010103
das Dôres SAlves LRuiz DBarros ROssowski S(2016)A meta-learning framework for algorithm recommendation in software fault predictionProceedings of the 31st Annual ACM Symposium on Applied Computing10.1145/2851613.2851788(1486-1491)Online publication date: 4-Apr-2016
https://dl.acm.org/doi/10.1145/2851613.2851788
Abaei GMashinchi MSelamat A(2015)Software fault prediction using BP-based crisp artificial neural networksInternational Journal of Intelligent Information and Database Systems10.1504/IJIIDS.2015.0708259:1(15-31)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1504/IJIIDS.2015.070825
Xuan XLo DXia XTian YWainwright RCorchado JBechini AHong J(2015)Evaluating defect prediction approaches using a massive set of metricsProceedings of the 30th Annual ACM Symposium on Applied Computing10.1145/2695664.2695959(1644-1647)Online publication date: 13-Apr-2015
https://dl.acm.org/doi/10.1145/2695664.2695959
Arar ÖAyan K(2015)Software defect prediction using cost-sensitive neural networkApplied Soft Computing10.1016/j.asoc.2015.04.04533:C(263-277)Online publication date: 1-Aug-2015
https://dl.acm.org/doi/10.1016/j.asoc.2015.04.045
Mishra BShukla K(2014)Software Defect Prediction Based on GUHA Data Mining Procedure and Multi-Objective Pareto Efficient Rule SelectionInternational Journal of Software Science and Computational Intelligence10.4018/ijssci.20140401016:2(1-29)Online publication date: 1-Apr-2014
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Abaei GSelamat A(2014)A survey on software fault detection based on different prediction approachesVietnam Journal of Computer Science10.1007/s40595-013-0008-z1:2(79-95)Online publication date: 1-May-2014
https://dl.acm.org/doi/10.1007/s40595-013-0008-z
Rezvan MZeinal Hamadani AShalbafzadeh A(2013)Case-based reasoning for classification in the mixed data sets employing the compound distance methodsEngineering Applications of Artificial Intelligence10.1016/j.engappai.2013.07.01426:9(2001-2009)Online publication date: 1-Oct-2013
https://dl.acm.org/doi/10.1016/j.engappai.2013.07.014
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Abductive case-based reasoning: Research Articles

Predicting business failure using forward ranking-order case-based reasoning

Predicting Fault-Prone Modules with Case-Based Reasoning

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