A Data Mining Method to Support Decision Making in Software Development Projects

Abstract

In this paper, we present a strategy to induce knowledge as support decision making in Software Development Projects (SDP). The motive of this work is to reduce the great quantity of SDP do not meet the initial cost requirements, delivery date and the quality of the final product. The main objective of this strategy is to support the manager in the decision taking to establish the policies from management when beginning a software project. Thus, we apply a data mining tool, called ELLIPSES, on databases of SDP. The databases are generated by means of the simulation of a dynamic model for the management of SDP. ELLIPSES tool is a new method oriented to discover knowledge according to the expert’s needs, by the detection of the most significant regions. The method essence is found in an evolutionary algorithm that finds these regions one after another. The expert decides which regions are significant and determines the stop criterion. The extracted knowledge is offered through two types of rules: quantitative and qualitative models. The tool also offers a visualization of each rule by parallel coordinate systems. In order to present this strategy, ELLIPSES is applied to a database which has already been obtained by means of the simulation of a dynamic model on a project concluded.