Authors:
Jacinto Mata
1
;
José Luis Álvarez
1
;
José Cristóbal Riquelme
2
and
Isabel Ramos
2
Affiliations:
1
Universidad de Huelva, Spain
;
2
Universidad de Sevilla, Spain
Keyword(s):
Software Development Project, Knowledge Discovery in Databases, Association Rules.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Strategic Decision Support Systems
;
Web Information Systems and Technologies
Abstract:
One of the main challenges that the project managers have during the building process of a software development project (SDP) is to optimise the values of the parameters that measure the viability of the final process. The accomplishment of this task, something that was not easy at the beginning, was helped with the appearance of dynamic models and simulation environments. The application of data mining techniques to the managing of Software Development Projects (SDP) is not an uncommon phenomenon, as in any other productive process that generates information in the way of input data and output variables. In this paper, we present and analyze the results obtained from a tool, developed by the authors, based on a Knowledge Discovery in Databases (KDD) technique. One of the most important contributions of these techniques to the software engineering field is the possibility of improving the management process of an SDP. The purpose is to provide accurate decision rules in order to help
the project manager to take decisions during the development.
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