Summarising Big Data: Common GitHub Dataset for Software Engineering Challenges
This provides a standardized resource for researchers in software engineering and natural language processing, though it is incremental as it builds on existing data filtering practices.
The authors tackled the problem of large-scale GitHub data processing and lack of comparability in software engineering research by creating and sharing a common dataset for many software engineering challenges.
In open-source software development environments; textual, numerical and relationship-based data generated are of interest to researchers. Various data sets are available for this data, which is frequently used in areas such as software engineering and natural language processing. However, since these data sets contain all the data in the environment, the problem arises in the terabytes of data processing. For this reason, almost all of the studies using GitHub data use filtered data according to certain criteria. In this context, using a different data set in each study makes a comparison of the accuracy of the studies quite difficult. In order to solve this problem, a common dataset was created and shared with the researchers, which would allow us to work on many software engineering problems.