1 citations · 1 across the 6 of their papers we have counts for
3 papers · 1 filter
What Breaks When LLMs Code? Characterizing Operational Safety Failures of Agentic Code Assistants
Alif Al Hasan, Sumon Biswas
Autonomous coding agents built on large language models (LLMs) are rapidly being integrated into development workflows, yet their operational safety properties remain poorly unders…
Improving Code Comprehension through Cognitive-Load Aware Automated Refactoring for Novice Programmers
Subarna Saha, Alif Al Hasan, Fariha Tanjim Shifat +1
Novice programmers often struggle to comprehend code due to vague naming, deep nesting, and poor structural organization. While explanations may offer partial support, they typical…
LLPut: Investigating Large Language Models for Bug Report-Based Input Generation
Alif Al Hasan, Subarna Saha, Mia Mohammad Imran +1
Failure-inducing inputs play a crucial role in diagnosing and analyzing software bugs. Bug reports typically contain these inputs, which developers extract to facilitate debugging.…