The goal of this project is to develop deep-learning based algorithms for identifying near-duplicates in a large collection of bug reports. Project tasks will consist of the following:
- Providing expert advice on the best deep-learning approaches to use for solving EA’s bug de-duplication problem.
- Designing, testing, and evaluating deep-learning algorithms to solve the bug deduplication problem, more precisely:
- Supervising a Queen’s Masters Student (hereafter called “the student”) to work on this problem.
- Co-author publications with NRC personnel and the student.
Sponsored by National Research Council of Canada