14 citations · 14 across the 5 of their papers we have counts for
5 papers
Leveraging Deep Learning for Abstractive Code Summarization of Unofficial Documentation
AmirHossein Naghshzan, Latifa Guerrouj, Olga Baysal
Usually, programming languages have official documentation to guide developers with APIs, methods, and classes. However, researchers identified insufficient or inadequate documenta…
Improving Code Example Recommendations on Informal Documentation Using BERT and Query-Aware LSH: A Comparative Study
Sajjad Rahmani, AmirHossein Naghshzan, Latifa Guerrouj
Our research investigates the recommendation of code examples to aid software developers, a practice that saves developers significant time by providing ready-to-use code snippets.…
Leveraging Data Mining Algorithms to Recommend Source Code Changes
AmirHossein Naghshzan, Saeed Khalilazar, Pierre Poilane +3
Context: Recent research has used data mining to develop techniques that can guide developers through source code changes. To the best of our knowledge, very few studies have inves…
Leveraging Unsupervised Learning to Summarize APIs Discussed in Stack Overflow
AmirHossein Naghshzan, Latifa Guerrouj, Olga Baysal
Automated source code summarization is a task that generates summarized information about the purpose, usage, and--or implementation of methods and classes to support understanding…
Understanding How and Why Developers Seek and Analyze API-related Opinions
Gias Uddin, Olga Baysal, Latifa Guerrouj +1
With the advent and proliferation of online developer forums as informal documentation, developers often share their opinions about the APIs they use. Thus, opinions of others ofte…