R4 Model for Case-Based Reasoning and Its Application for Software Fault Prediction

Making R4 model effective and efficient I have introduced some new features, i.e., renovation of knowledgebase KBS and reducing the maintenance cost by removing the duplicate record from the KBS. Renovation of knowledgebase is the process of removing duplicate record stored in knowledgebase and adding world new problems along with world new solutions. This paper explores case-based reasoning and its applications for software quality improvement through early prediction of error patterns. It summarizes a variety of techniques for software quality prediction in the domain of software engineering. The system predicts the error level with respect to LOC and with respect to development time, and both affects the quality level. This paper also reviews four existing models of case-based reasoning CBR. The paper presents a work in which I have expanded our previous work Rashid et al., 2012. I have used different similarity measures to find the best method that increases reliability. The present work is also credited through introduction of some new terms like coefficient of efficiency, i.e., developer's ability.

[1]  Ekbal Rashid,et al.  A survey in the area of machine learning and its application for software quality prediction , 2012, SOEN.

[2]  Taghi M. Khoshgoftaar,et al.  An empirical study of the impact of count models predictions on module-order models , 2002, Proceedings Eighth IEEE Symposium on Software Metrics.

[3]  David L. Waltz,et al.  Applications of the Connection Machine , 1990, Computer.

[4]  Mario Piattini,et al.  Proceedings of the 7th ECOOP Workshop on Quantitative Approaches in Object-Oriented Software Engineering , 2003 .

[5]  Venkata U. B. Challagulla,et al.  Empirical assessment of machine learning based software defect prediction techniques , 2005, 10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems.

[6]  Taghi M. Khoshgoftaar,et al.  Unsupervised learning for expert-based software quality estimation , 2004, Eighth IEEE International Symposium on High Assurance Systems Engineering, 2004. Proceedings..

[7]  Mobyen Uddin Ahmed,et al.  Case-Based Reasoning Systems in the Health Sciences: A Survey of Recent Trends and Developments , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[8]  Barbara A. Kitchenham,et al.  An investigation of analysis techniques for software datasets , 1999, Proceedings Sixth International Software Metrics Symposium (Cat. No.PR00403).

[9]  Ekbal Rashid,et al.  Software Quality Estimation using Machine Learning: Case-based Reasoning Technique , 2012 .

[10]  Du Zhang,et al.  Advances in Machine Learning Applications in Software Engineering , 2007 .

[11]  David Leake,et al.  Case-Based Reasoning: Experiences, Lessons and Future Directions , 1996 .

[12]  Ekbal Rashid,et al.  Prediction of rate of improvement of software quality and development effort on the basis of Degreeof excellence with respect to number of lines of code , 2014, ArXiv.

[13]  John E. Hunt,et al.  Evolutionary Case Based Design , 1995, UK Workshop on Case-Based Reasoning.

[14]  Ivan Bratko,et al.  Machine Learning and Data Mining; Methods and Applications , 1998 .

[15]  Ekbal Rashid,et al.  Machine Learning and Software Quality Prediction: As an Expert System , 2014 .

[16]  Zhaohao Sun,et al.  R5 model for case-based reasoning , 2003, Knowl. Based Syst..

[17]  David L. Waltz,et al.  Toward memory-based reasoning , 1986, CACM.

[18]  Peter Kokol,et al.  Estimating Software Quality with Advanced Data Mining Techniques , 2006, 2006 International Conference on Software Engineering Advances (ICSEA'06).

[19]  Stefan Biffl,et al.  Optimal project feature weights in analogy-based cost estimation: improvement and limitations , 2006 .

[20]  Vandana Bhattacherjee.  The Soft Computing Approach to Program Development Time Estimation , 2006, 9th International Conference on Information Technology (ICIT'06).

[21]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[22]  Bradley P. Allen,et al.  Case-based reasoning: business applications , 1994, CACM.

[23]  Venkata U. B. Challagulla,et al.  A Unified Framework for Defect Data Analysis Using the MBR Technique , 2006, 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06).