Abstract
Recently, the concern of software quality increases rapidly. Although there have been many efforts to establish standards for software quality, such as ISO/IEC 9126, they provide only a framework for quality characteristics and evaluation process. They do not provide practical guidance for deriving reasonable weight value criteria for quality evaluation. This paper presents a method to draw the quantitative weight values from evaluator’s subjective data in software evaluation in compliance with ISO/IEC 9126 standard. To eliminate evaluators’ subjectiveness and uncertainty, the Dempster-Shafer (D-S) theory is improvised and utilized. The D-S theory is improved with merge rule to reduce the bias of weight value when they are merged with other evaluator’s weight value. The proposed merge rule has been tested for it’s effectiveness with actual evaluation data.
Chapter PDF
Similar content being viewed by others
References
Software Quality Characteristics and Metrics - Part 1: Quality Characteristics & Sub- Characteristics, TTAS.IS-9126.1 (October 1998)
Evaluation of Sotfware Product - Part 5: Process for Evaluators, TTAS.IS-14598.5 (October 1998)
Yang, H.S., Lee, H.Y.: Design and Implementation of Quality Evaluation Toolkit in Design Phase. Korea Information Science Society Journal (C) 3(3), 262–274 (1997)
Yang, H.S., Lee, Y.G.: Design and Implementation of Quality Evaluation supporting Tool for Software Specification. Information Science Society Journal (C) 3(2), 152–163 (1997)
Yang, H.S., Kwon, K.H., Lee, H.Y., Jo, Y.S., Lee, Y.G., Park, J.H., Heo, T.G.: Design and Implementation of Software Quality Evaluation Toolkit. Korea Information Processing Society Journal 2(2), 185–198 (1995)
Murphy, C.K.: Combining belief function when evidence conflicts. Decision Support System 29, 1–9 (2000)
Zadeh, L.A.: Review of Mathematical theory of evidence, by G Shafer. AI Magazine 5(3), 81–83 (1984)
Giarratano, J., Riley, G.: Expert Systems. PWS Publishing Company (1994)
We, K.S.: Design of an Expert System for Software Quality Evaluation with Easy Weighting of Quality Element, Graduate School of Dongguk University Computer Engineering, Doctoral Dissertation (December 1995)
We, K.S., Lee, K.S.: Design of an Expert System for Software Quality Evaluation. Information Science Society Journal (B) 22(10), 1434–1444 (1995)
Do, Y.T., Kim II, G., Kim, J.W., Park, C.H.: Artificial Intelligence Concept and Application, pp. 77–96. SciTech Press (2001)
Kim, H.S.: Artificial Intelligence and Application, pp. 199–216. Saengnung Press (1994)
Kim, J.H., Park, S.S., Paek, E.O., Seo, J.Y., Lee Il, B.: Artificial Intelligence Theory and Practice, pp. 373–384. SciTech Press (1998)
Wong, S.K.M., Lingras, P.: Representation of Qualitative User Preference by Quantitative Belief Functions. IEEE Transaction on Knowledge and Data Engineering 6(1), 72–78 (1994)
Lee, G.S.: An Efficient Dempster-Shafer Evidence Combination Scheme for Uncertainty Handling. Korea Information Processing Society Journal 3(4), 908–914 (1996)
Lee, G.S.: An Approximate Evidence Combination Scheme for Increased Efficiency. Korea Information Processing Society Journal(B) 9-B(1), 17–22 (2002)
Lee, J.M., Jung, H.W.: An Application of Qualitative Preference to Software Quality Evaluation. Korea Operation Research and Management Science Society Journal 25(3), 109–124 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yoo, J.H., Lee, B.G., Han, H.S. (2004). Determination and Combination of Quantitative Weight Value from Multiple Preference Information. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science - ICCS 2004. ICCS 2004. Lecture Notes in Computer Science, vol 3038. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24688-6_36
Download citation
DOI: https://doi.org/10.1007/978-3-540-24688-6_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22116-6
Online ISBN: 978-3-540-24688-6
eBook Packages: Springer Book Archive