Improving Decision Support for Software Component Selection through Systematic Cross-Referencing and Analysis of Multiple Decision Criteria

This article discusses opport unities for leveraging scale in cases of recurring scenarios of comparable decisions with multiple objectives in well-defined domains. Based on a softwa re component ranking and selection method that uses utility analysis to separate objective information gathering and subjective assessment, we discus s challenges of decision making such as criterion complexity and evaluation effort. We show that by systematically identifying criteria across cases, it becomes fea sible to employ cross- referencing and quantita tive assessment of decision criteria and criteria sets across scenarios and organizations to impro ve decision making efficiency and effectiveness. We present a method and tool that allows referencing decision criteria across cases and employs a set of impact fact ors for decision criteria and sets of criteria. We discu ss the results of analyzing a series of real-world ca se studies in software component selection. We analyze the applications and implications of the method and its potential to improve decision making effectiveness and efficiency.