  New programming languages (e.g., Swift, Go, Rust, etc.) are being introduced
to provide a better opportunity for the developers to make software development
robust and easy. At the early stage, a programming language is likely to have
resource constraints that encourage the developers to seek help frequently from
experienced peers active in QA sites such as Stack Overflow (SO). In this
study, we have formally studied the discussions on three popular new languages
introduced after the inception of SO (2008) and match those with the relevant
activities in GitHub whenever appropriate. For that purpose, we have mined
4,17,82,536 questions and answers from SO and 7,846 issue information along
with 6,60,965 repository information from GitHub. Initially, the development of
new languages is relatively slow compared to mature languages (e.g., C, C++,
Java). The expected outcome of this study is to reveal the difficulties and
challenges faced by the developers working with these languages so that
appropriate measures can be taken to expedite the generation of relevant
resources. We have used the LDA method on SO's questions and answers to
identify different topics of new languages. We have extracted several features
of the answer pattern of the new languages from SO to study their
characteristics. These attributes were used to identify difficult topics. We
explored the background of developers who are contributing to these languages.
We have created a model by combining Stack Overflow data and issues,
repository, user data of GitHub. Finally, we have used that model to identify
factors that affect language evolution. We believe that the outcome of our
study is likely to help the owner/sponsor of these languages to design better
features and documentation. It will also help the software developers or
students to prepare themselves to work on these languages in an informed way.
