1 citations · 1 across the 3 of their papers we have counts for
10 papers
SCATE: Learning to Supervise Coding Agents for Cost-Effective Test Generation
Sijia Gu, Noor Nashid, Ali Mesbah
While autonomous coding agents have significantly advanced automated test generation, they remain fundamentally limited by lazy generation, a phenomenon where agents prematurely te…
Beyond Accuracy: Behavioral Dynamics of Agentic Multi-Hunk Repair
Noor Nashid, Daniel Ding, Keheliya Gallaba +2
Automated program repair has traditionally focused on single-hunk defects, overlooking multi-hunk bugs that are prevalent in real-world systems. Repairing these bugs requires coord…
Issue2Test: Generating Reproducing Test Cases from Issue Reports
Noor Nashid, Islem Bouzenia, Michael Pradel +1
Automated tools for solving GitHub issues are receiving significant attention by both researchers and practitioners, e.g., in the form of foundation models and LLM-based agents pro…
Characterizing Multi-Hunk Patches: Divergence, Proximity, and LLM Repair Challenges
Noor Nashid, Daniel Ding, Keheliya Gallaba +2
Multi-hunk bugs, where fixes span disjoint regions of code, are common in practice, yet remain underrepresented in automated repair. Existing techniques and benchmarks pre-dominant…
LLM Test Generation via Iterative Hybrid Program Analysis
Sijia Gu, Noor Nashid, Ali Mesbah
Automating unit test generation remains a significant challenge, particularly for complex methods in real-world projects. While Large Language Models (LLMs) have made strides in co…
Dockerfile Flakiness: Characterization and Repair
Taha Shabani, Noor Nashid, Parsa Alian +1
Dockerfile flakiness-unpredictable temporal build failures caused by external dependencies and evolving environments-undermines deployment reliability and increases debugging overh…