Creat membership Creat membership
Sign in

Forgot password?

Confirm
  • Forgot password?
    Sign Up
  • Confirm
    Sign In
Creat membership Creat membership
Sign in

Forgot password?

Confirm
  • Forgot password?
    Sign Up
  • Confirm
    Sign In
Collection
For ¥0.57 per day, unlimited downloads CREATE MEMBERSHIP Download

toTop

If you have any feedback, Please follow the official account to submit feedback.

Turn on your phone and scan

home > search >

Predicting Software Outcomes Using Data Mining and Text Mining

Author:
Uzma Raja   Marietta J. Tretter  


Issue Date:
2007


Abstract(summary):

Organizations spend a major portion of their Information Technology budget on software maintenance. In this paper, we present a predictive model for the maintenance outcomes of the software projects. We also identify the factors that affect software maintenance outcomes. We build our model using Data Mining (DM) techniques on Open Source Software (OSS) project data. We use the public access to the data archives of over 100,000 projects hosted by SourceForge.net (SF). We use prior research in software engineering to identify the initial set of variables used in the model building process. We use multiple DM techniques available in SAS Enterprise Miner. We also create additional new variables from the textual data provided by SF, through SAS Text Miner. The use of these new variables improves the model, significantly. The final model is selected based on domain knowledge and fit statistics of the models. Results indicate that end-user participation, product functionality, and usefulness of the project affect the software maintenance quality.


Page:
9


VIEW PDF

The preview is over

If you wish to continue, please create your membership or download this.

Create Membership

Similar Literature

Submit Feedback

This function is a member function, members do not limit the number of downloads