Search Results for author:
Found 5 papers, 2 papers with code
Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study
Conclusions: Our research addresses the critical issue of deep learning bug reproducibility.
Predicting Line-Level Defects by Capturing Code Contexts with Hierarchical Transformers
Unfortunately, despite the use of many software quality assurance (SQA) practices in software development (e. g., code review, continuous integration), defects may still exist in the official release of a software product.
A Systematic Review of Automated Query Reformulations in Source Code Search
Developers consult these requests and often choose a few keywords from them as an ad hoc query.
Generating Cyber Threat Intelligence to Discover Potential Security Threats Using Classification and Topic Modeling
In this paper, we identify and explore relevant CTI from hacker forums utilizing different supervised (classification) and unsupervised learning (topic modeling) techniques.
The Forgotten Role of Search Queries in IR-based Bug Localization: An Empirical Study
We confirmed that the state-of-the-art query construction approaches are indeed not sufficient for constructing appropriate queries (for bug localization) from certain natural language-only bug reports although they contain such queries.
