A big part of software developers’ time is spent finding answers to their coding-task-related questions. To answer their questions, developers usually perform web searches, ask questions on Q&A websites, or, more recently, in chat communities. Yet, many of these questions have frequently already been answered in previous chat conversations or other online communities. Automatically identifying and then suggesting these previous answers to the askers could, thus, save time and effort. In an empirical analysis, we first explored the frequency of repeating questions on the Discord chat platform and assessed our approach to identify them automatically. The approach was then evaluated with real-world developers in a field experiment, through which we received 142 ratings on the helpfulness of the suggestions we provided to help answer 277 questions that developers posted in four Discord communities. We further collected qualitative feedback through 53 surveys and 10 follow-up interviews. We found that the suggestions were considered helpful in 40% of the cases, that suggesting Stack Overflow posts is more often considered helpful than past Discord conversations, and that developers have difficulties describing their problems as search queries and, thus, prefer describing them as natural language questions in online communities.

Developers frequently use the web to locate API examples that help them solve their programming tasks. While sites like Stack Overflow (SO) contain API examples embedded within their textual descriptions, developers cannot access this API knowledge directly. Instead they need to search for and browse results to select relevant SO posts and then read through individual posts to figure out which answers contain information about the APIs that are relevant to their task. This paper introduces an approach, called Scout, that automatically analyzes search results to extract API signature information. These signatures are used to group and rank examples and allow for a unique API-based presentation that reduces the amount of information the developer needs to consider when looking for API information on the web. This succinct representation enables Scout to be integrated fully within an IDE panel so that developers can search and view API examples without losing context on their development task. Scout also uses this integration to automatically augment queries with contextual information that tailors the developer’s queries, and ranks the results according to the developer’s needs. In an experiment with 40 developers, we found that Scout reduces the number of queries developers need to perform by 19% and allows them to solve almost half their tasks directly from the API-based representation, reducing the number of complete SO posts viewed by approximately 64%.