Abstract
Automatic Summarization is one of the very important tasks that are performed to improve the searching experience in the internet world. Software Repositories are one of the greatest sources of information for the software development community as it contains varied information like the team behavior, intentions, emotions, the bugs, the project style, project management information, etc. The paper is an extension to the previous work where we have used just the feature-based technique to generate the summary for the Bug Reports. Here in this paper, we have used machine-learning approaches along with the Features to find out how the results vary. For the machine learning approaches, as there are many approaches which are available, we use the very popular approaches KNN, CART, NB and SVM for the observation. We observed that when the machine learning approaches are integrated with the feature-based approach, the results improve.
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