Automated Bug Triaging

What is Bug Triaging:

The process of Bug Triaging is vast and elaborate. However, the minimalistic definition that we adopt for this work is,

For a given bug report, identifying an appropriate developer who could potentially fix the bug is the primary task of bug triaging.

So, can we automate this process of bug triaging?

RQ1: Is it feasible to perform automated bug triaging using deep learning?
RQ2: How does the unsupervised feature engineering approach perform, compared to traditional feature engineering based approaches?
RQ3: How does the number of training samples per class affect the performance of the classifier?
RQ4: What is the effect of using only the title of the bug report in performing triaging when compared with using the description as well?
RQ5: Is transfer learning effective in this domain?

This is the goal of our research paper published in the CoDS-COMAD 2019 “DeepTriage: Exploring the Effectiveness of Deep Learning for Bug Triaging”.

Please find the poster here, that we presented in CoDS-COMAD 2019 conference. Also, the data and the initial version of the code is available here.

Please note that this feature is an initial proof of concept, and is not yet available as a system for open consumption.

If you want to know more, do reach out to me at anussank@in.ibm.com or tweet to me @goodboyanush