Maintainability plays a fundamental role for achieving success in software system and it is con-sidered as an important quality characteristics. Maintainability may be predicted efficiently by us-ing soft computing techniques as they provide good results. In this paper similarity- based ap-proach is used with the contribution of fuzzy Analytical Hierarchical Process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) at 2-level hierarchy. Here similarity- based approach illustrates the combine approach of fuzzy AHP and fuzzy TOPSIS. This approach is used to provide the rank of software to select the best one for maintainability estimation. Also, several factors are presented that influence the software maintainability. These factors are taken as criterion and three software products are taken as alternatives.
Component-based software system (CBSS) development technique is an emerging discipline that promises to take software development into a new era. As hardware systems are presently being constructed from kits of parts, software systems may also be assembled from components. It is more reliable to reuse software than to create. It is the glue code and individual components reliability that contribute to the reliability of the overall system. Every component contributes to overall system reliability according to the number of times it is being used, some components are of critical usage, known as usage frequency of component. The usage frequency decides the weight of each component. According to their weights, each component contributes to the overall reliability of the system. Therefore, ranking of components may be obtained by analyzing their reliability impacts on overall application. In this paper, we propose the application of fuzzy multi-objective optimization on the basis of ratio analysis, Fuzzy-MOORA. The method helps us find the best suitable alternative, software component, from a set of available feasible alternatives named software components. It is an accurate and easy to understand tool for solving multi-criteria decision making problems that have imprecise and vague evaluation data. By the use of ratio analysis, the proposed method determines the most suitable alternative among all possible alternatives, and dimensionless measurement will realize the job of ranking of components for estimating CBSS reliability in a non-subjective way. Finally, three case studies are shown to illustrate the use of the proposed technique.