Improved Searchability of Bug Reports Using Content-Based Labeling with Machine Learning of Sentences.

Most stakeholders refer to past bug reports when they encounter a problem since bug reports contain useful information. However, searching for specific content is difficult because there are many bug reports. The desired content depends on the viewpoint of the stakeholder. A full text search includes unwanted content, which is costly. Although this problem has been previously noted, a solution has yet to be proposed. Herein we propose Content-based Labeling Method as a solution. This method organizes information in a bug report by labeling each sentence based on its contents, allowing stakeholders' viewpoints to be considered. We evaluate the improvement in searchability. The Content-based Labeling Method improves the searchability according to the F-measure and precision of the experimental results.