An association rule mining method for estimating the impact of project management policies on software quality, development time and effort
Accurate and early estimations are essential for effective decision making in software project management. Nowadays, classical estimation models are being replaced by data mining models due to their application simplicity and the rapid production of profitable results. In this work, a method for min...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión enviada para evaluación y publicación |
| Fecha de publicación: | 2008 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/59115 |
| Acceso en línea: | http://hdl.handle.net/11441/59115 https://doi.org/10.1016/j.eswa.2006.09.022 |
| Access Level: | acceso abierto |
| Palabra clave: | Association rules Data mining Software estimation Project management Simulation |
| Sumario: | Accurate and early estimations are essential for effective decision making in software project management. Nowadays, classical estimation models are being replaced by data mining models due to their application simplicity and the rapid production of profitable results. In this work, a method for mining association rules that relate project attributes is proposed. It deals with the problem of discretizing continuous data in order to generate a manageable number of high confident association rules. The method was validated by applying it to data from a Software Project Simulator. The association model obtained allows us to estimate the influence of certain management policy factors on various software project attributes simultaneously. |
|---|