Effective Bug Triage with Data Reduction

Towards Bug Triage with Software Data Reduction Technique

Analysis of Bug Triage using Data Preprocessing (Reduction) Techniques

In the bug triage we have an unavoidable step of fixing the bugs which helps in correctly assigning a developer to a new bug. Text classification and binary classification techniques are applied to decrease the time cost in manual work and to enhance the working of automatic bug triage. We address the problem of data reduction and hence we combine the instance selection and the feature selectio...

Analysis of Bug Triage using Data Preprocessing (Reduction) Techniques

In the bug triage we have an unavoidable step of fixing the bugs which helps in correctly assigning a developer to a new bug. Text classification and binary classification techniques are applied to decrease the time cost in manual work and to enhance the working of automatic bug triage. We address the problem of data reduction and hence we combine the instance selection and the feature selectio...

Improved Approach for Predicting the Bug Triage Using Data Reduction Methods

Most of the software companies need to deal with vast number of software bugs day to day. This paper can be viewed as an application of instance selection and feature selection in bug repositories. The aim is to address the problem of data reduction for bug triage, and to reduce the scale and improve the quality of bug data. This can be achieved by combining instance selection with feature sele...

Learning from evolving data streams: online triage of bug reports

Open issue trackers are a type of social media that has received relatively little attention from the text-mining community. We investigate the problems inherent in learning to triage bug reports from time-varying data. We demonstrate that concept drift is an important consideration. We show the effectiveness of online learning algorithms by evaluating them on several bug report datasets collec...