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Full-Text Articles in Physical Sciences and Mathematics
Recommending Who To Follow In The Software Engineering Twitter Space, Abhabhisheksh Sharma, Yuan Tian, Agus Sulistya, Dinusha Wijedasa, David Lo
Recommending Who To Follow In The Software Engineering Twitter Space, Abhabhisheksh Sharma, Yuan Tian, Agus Sulistya, Dinusha Wijedasa, David Lo
Research Collection School Of Computing and Information Systems
With the advent of social media, developers are increasingly using it in their software development activities. Twitter is one of the popular social mediums used by developers. A recent study by Singer et al. found that software developers use Twitter to “keep up with the fast-paced development landscape.” Unfortunately, due to the general-purpose nature of Twitter, it’s challenging for developers to use Twitter for their development activities. Our survey with 36 developers who use Twitter in their development activities highlights that developers are interested in following specialized software gurus who share relevant technical tweets.To help developers perform this task, in …
Recommending Apis For Software Evolution, Ferdian Thung
Recommending Apis For Software Evolution, Ferdian Thung
Dissertations and Theses Collection (Open Access)
Softwares are constantly evolving. This evolution has been made easier through the use of Application Programming Interfaces (APIs). By leveraging APIs, developers reuse previously implemented functionalities and concentrate on writing new codes. These APIs may originate from either third parties or internally from other compo- nents of the software that are currently developed. In the first case, developers need to know how to find and use third party APIs. In the second case, developers need to be aware of internal APIs in their own software. In either case, there is often too much information to digest. For instance, finding the …
Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shaowei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik
Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shaowei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Software engineers share experiences with modern technologies by means of software information sites, such as Stack Overflow. These sites allow developers to label posted content, referred to as software objects, with short descriptions, known as tags. However, tags assigned to objects tend to be noisy and some objects are not well tagged. To improve the quality of tags in software information sites, we propose EnTagRec, an automatic tag recommender based on historical tag assignments to software objects and we evaluate its performance on four software information sites, Stack Overflow, Ask Ubuntu, Ask Different, and Free code. We observe that that …