Mining crowd sourcing repositories for open innovation in software engineering

Various development tools have been introduced and the choice of suitable development tool depends on the particular context like the type of application to be developed, the development process and application domain, etc. The real challenge is to deliver new features at the right time with a faster development cycle. The selection of suitable development tools will help developers to save time and effort. In this research, we will explore software engineering repositories (like StackOverflow) to collect feedback from developers about development tools. This will explore which features in a development tool are most important, which features are missing, and which features require changes. The answers to these questions can be found by mining the community question-answering sites (CQA). We will use user feedback to innovate the new features in the development tool. Various techniques of Big Data, Data Mining, Deep Learning, and Transformers including Generative Pre-Training Transformer will be used in our research. Some of the major techniques include (i) data collection from CQA sites like StackOverflow, (ii) data preprocessing (iii) categories the data into various topics using topic modeling (iv) sentiment analysis of data to get positive or negative aspects of features (v) ranking of users and their feedback. The output of this research will categorize the users feedback into various ideas, this will help organizations to decide which features are required, which features are not required, which features are difficult or confusing, and which new features should be introduced into a new release.