A Fuzzy Case-Based Reasoning Model for Software Requirements Specifications Quality Assessment

Salama A. Mostafa, Saraswathy Shamini Gunasekaran, Shihab Hamad Khaleefah, Aida Mustapha, Mohammed Ahmed Jubair, Mustafa Hamid Hassan

Abstract


Different software Quality Assurance (SQA) audit techniques are applied in the literature to determine whether the required standards and procedures within the Software Requirements Specification (SRS) phase are adhered to. The inspection of the Software Requirements Specification (iSRS) system is an analytical assurance tool which is proposed to strengthen the ability to scrutinize how to optimally create high-quality SRSs. The iSRS utilizes a Case-Based Reasoning (CBR) model in carrying out the SRS quality analysis based on the experience of the previously analyzed cases. This paper presents the contribution of integrating fuzzy Logic technique in the CBR steps to form a Fuzzy Case-Based Reasoning (FCBR) model for improving the reasoning and accuracy of the iSRS system. Additionally, for efficient cases retrieval in the CBR, relevant cases selection and nearest cases selection heuristic search algorithms are used in the system. Basically, the input to the relevant cases algorithm is the available cases in the system case base and the output is the relevant cases. The input to the nearest cases algorithm is the relevant cases and the output is the nearest cases. The fuzzy Logic technique works on the selected nearest cases and it utilizes similarity measurement methods to classify the cases into no-match, partial-match and complete-match cases. The features matching results assist the revised step of the CBR to generate a new solution. The implementation of the new FCBR model shows that converting numerical representation to qualitative terms simplifies the matching process and improves the decision-making of the system.

Keywords


software requirements specifications; heuristic search; fuzzy logic; case-based reasoning; classification; similarity measurement.

Full Text:

PDF

References


D. Galin, Software Quality Assurance: From Theory to Implementation: Pearson Education Limited, 2004.

W. M. Wilson, L. H. Rosenberg, and L. E. Hyatt, “Automated analysis of requirement specifications,” In Proc. of the 19th international conference on Software engineering, ACM, 1997, pp. 161-171.

H. Mat Jani, and S. A. Mostafa, “Implementing Case-Based Reasoning Technique to Software Requirements Specifications Quality Analysis”, The International Journal of Advancements in Computing Technology, (IJACT), Vol. 3, No. 1, 2011, pp. 23-31.

A. A. Alshazly, A. M. Elfatatry and M. S. Abougabal, Detecting defects in software requirements specification. Alexandria Engineering Journal, 53(3), 513-527, 2014.

H. Mat Jani, “Applying Case-Based Reasoning to Software Requirements Specifications Quality Analysis System”, in The Proceeding of The 2nd International Conference of Software Engineering and Data Mining (SEDM 2010): IEEE/AICIT, Chengdu, China, pp 140-144, 2010.

M. A. Jubair, S. A. Mostafa, A. Mustapha and H. Hafit, “A Survey of Multi-agent Systems and Case-Based Reasoning Integration,” In 2018 International Symposium on Agent, Multi-Agent Systems and Robotics (ISAMSR), IEEE, pp. 1-6, Aug., 2018.

S. Nikolaidis, and C. Lazos, Fuzzy Case Identification in Case-Based Reasoning Systems, Computational Intelligence, Volume 15, Number 3, 2000.

P. P. Bonissone, and L. M. Ramon, F4.3 Fuzzy Case-Based Reasoning Systems: Citeseer, 2008 [online]. Available: http://www.mendeley.com/research/f4-3-fuzzy-casebased-reasoning-systems/.

K. P. Sankar, and C. K. Simon, Foundation of Soft Case-Based Reasoning: John Wiley & Sons, Inc., Hoboken. New Jersey, 2004.

S. A. Mostafa, M. S. Ahmad and M. Firdaus, A soft computing modeling to case-based reasoning implementation, International Journal of Computer Applications, 47(7), 14-21, 2012.

S. A. Mostafa, A. Mustapha, M. A. Mohammed, M. S. Ahmad and M. A. Mahmoud, A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application. International journal of medical informatics, 112, 173-184, 2018.

H. T. Nguyen, C. L. Walker and E. A. Walker, A first course in fuzzy logic. CRC Press, 2018.

S. A. Mostafa, R. Darman, S. H. Khaleefah, A. Mustapha, N. Abdullah and H. Hafit, A general framework for formulating adjustable autonomy of multi-agent systems by fuzzy logic. In KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications, Springer, Cham, pp. 23-33, Jun. 2018.

M. K. A. Ghani, M. A. Mohammed, M. S. Ibrahim, S. A. Mostafa and D. A. Ibrahim, Implementing an Efficient Expert System for Services Center Management by Fuzzy Logic Controller. Journal of Theoretical & Applied Information Technology, vol 95,13, 2017.

M. A. Mohammed, M. K. A. Ghani, N. A. Arunkumar, O. I. Obaid, S. A. Mostafa, M. M. Jaber and D. A. Ibrahim, Genetic case-based reasoning for improved mobile phone faults diagnosis. Computers & Electrical Engineering, 71, 212-222, 2018.

R. Elaine, K. Kevin, and B. Shivshankar, Artificial Intelligence (3nd Edition): McGraw-Hill Education, India, 2009.

Firesmith, D. (2003). Specifying good requirements. Journal of Object Technology, 2(4), 77-87.

J. D. Blaine and J. Huang, Software quality requirements: how to balance competing priorities. IEEE Software, 25(2):22–24, 2008.




DOI: http://dx.doi.org/10.18517/ijaseit.9.6.9957

Refbacks

  • There are currently no refbacks.


Published by INSIGHT - Indonesian Society for Knowledge and Human Development