Explainable AI Points to Reused Code as a Hidden Signal of Software Faults
Researchers have built a reuse-aware, package-level fault prediction model for Java applications that pairs architectural metrics with SHAP and LIME ...
Researchers have built a reuse-aware, package-level fault prediction model for Java applications that pairs architectural metrics with SHAP and LIME ...
University of Arizona researchers have developed a formal-methods approach that automatically encodes microservice source code into a constraint model, enabling ...
NJIT researchers won a Distinguished Paper Award at the IEEE/ACM Automated Software Engineering conference for showing that many standard proxies ...
New research from Seoul National University shows that generative AI is absorbing the entry-level tasks and failure-based learning through which ...
A new viewpoint in the Journal of General Internal Medicine finds that only 4 percent of papers in leading medical ...
Researchers in Madrid have built Caret, an open-source conversational AI assistant for Eclipse that validates its own suggestions, traces every ...
Version 2.0.1 of SpinGlassPEPS.jl consolidates a Julia tensor-network solver for Ising-like optimization into a single package while adding truncation diagnostics, ...
Researchers in Hyderabad have built a deep learning pipeline that predicts fault-prone software modules with 99.3 percent accuracy in under ...
Researchers have developed a domain-adversarial deep learning method that captures contextual code semantics and aligns data distributions across projects, improving ...
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© 2025 Scienmag - Science Magazine