Approximation Algorithms for Software Component Selection Problem

Abstract

Today's software systems are more frequently composed from preexisting commercial or non-commercial components and connectors. These components provide complex and independent functionality and are engaged in complex interactions. Component-Based Software Engineering (CBSE) is concerned with composing, selecting and designing such components. As the popularity of this approach and hence number of commercially available software components grows, selecting a set of components to satisfy a set of requirements while minimizing cost is becoming more difficult. This problem necessitates the design of efficient algorithms to automate component selection for software developing organizations. We address this challenge through analysis of Component Selection, the NP-complete process of selecting a minimal cost set of components to satisfy a set of objectives. Due to the high order of computational complexity of this problem, we examine approximating solutions that make the component selection process practicable. We adapt a greedy approach and a genetic algorithm to approximate this problem. We examined the performance of studied algorithms on a set of selected ActiveX components. Comparing the results of these two algorithms with the choices made by a group of human experts shows that we obtain better results using these approximation algorithms.

Testing Component-Based Software: What It has to do with Design and Component Selection

“…One paper entitled "Determining criteria for Selecting Software Components: Lessons learned" [13] asserts that component selection relies on suitability and completeness of criteria used for evaluation. Another paper entitled "Approximation Algorithms for Software Component Selection Problem" [14] also make similar assertion that selecting a set of components to satisfy a set of requirements while minimizing cost is becoming more difficult. A work entitled "A reusable software component-based development process model" [7] proposes a spiral process model for CBS development.…”

A Framework for Component Selection Considering Dark Sides of Artificial Intelligence: A Case Study on Autonomous Vehicle

“…Various commercial OTS (COTS) approaches have been proposed in the literature, including [2][3][4][5]. In [2,3], the authors focused on COST selection and implementation by considering the business and functional criteria.…”

“…The requirements for engineering and CS methods are incorporated to achieve this goal. PORE and CRE are the two most notable examples of the second type of CS methods [5]. It is not realistic to anticipate a completed match between desired components and available components in any CS approach.…”