Mine bug report history for discovering process maps, inefficiencies and inconsistencies
We applied business process mining tools and techniques to analyze the event log data (bug report history) generated by an issue tracking system with the objective of discovering runtime process maps, inefficiencies and inconsistencies. This will help process analyst for informed decision making.

Process mine multiple software repositories for software defect resolution
The process followed from the inception (issue reported in ITS) till resolution is studied for Google Chromium project which involves process mining data from three repositories: Google Chromium ITS, Rietveld PCR system and VCS. The mined data is analyzed from control flow and organizational perspective.

Integration of social media with issue tracking system
Project aims at measuring and analyzing the extent of presence of social media websites in issue tracking systems and implement a tool which integrates ITS with social media, leveraging the advantage offered by social media in improving the quality of software maintenance.

Analyzing linguistic pattern for bug reports component classification
Project aims to predict the component to which a bug, reported in issue tracking system, pertains. Model is trained with labeled data using relevant features (structured and unstructured) and component is predicted for newly reported bugs using the trained model. 

Moodroid: Mobile Moodle
Moo-Droid is a complete client side application which allows student to access assignments in all enrolled courses in just few clicks. It is designed for Android phones.

Anonymize Me
We implemented k-anonymity and l-diversity to avoid privacy breach for a data set. It helps to ensure that an individual is not identified uniquely.