Use of Data Mining in System Development Life Cycle - Data Mining: Theory, Methodology, Techniques, and Applications - page 106

software component testing and (2) software reuse and maintenance that includes
component discovery, reuse and maintenance.
There are also examples of complementing DM with the use of software
engineering (SE) principles. [7] utilised SE principles for the development of
clustering architecture implemented on the multi-stage DM process to reduce the
processing time. A SE methodology is also used to combine the application of
deductive logic for generating intelligence from a collection of SE data [13].

Project Management
Datbases (Risk
Management, Configuration
Mangement)

Software Modules
(Source code,
Libraries)

Project Documentation (Electronic
and Paper based), Problem
Reports, Conceptual Models (UML)

Data Integration & Selection

Pre-processing

Other machine learning
techniques

Clu stering D e cision & Rgression trees

Data Mining

As s ociation

Neural n etworks

Post-Processing

Manamgement Rules
Generation

Software
Component Reuse

Software
Component testing

Software Component
Discovery

Software Component
Maintenance

Fig. 1. A general framework showing steps of DM process in SDLC

2.1 Software Development Process

There exist several software development methodologies such as waterfall, incremental,
rapid, agile and object-oriented [18]. Usually developers choose a methodology based
on their previous experience or according to the managerial decisions. Every
organisation collects a meta-data about the applications being developed. A data set can
be created based on the methodology used, human resources involved, nature of the
application, etc, and finally whether the project has been successful or not. Results of
the DM analysis can be used in advising developers on the usage of a methodology
according to the nature of the future application, to warn developers about failure
stories, and to inform project mangers on human resources planning and scheduling.