11 papers
Code Reasoning for Software Engineering Tasks: A Survey and A Call to Action
Saurabh Pujar, Ira Ceka, Irene Manotas +3
The rise of large language models (LLMs) has led to dramatic improvements across a wide range of natural language tasks. Their performance on certain tasks can be further enhanced…
TempoBench: Reasoning Execution Without Causal Attribution Is Just Simulation
Nikolaus Holzer, William Fishell, Baishakhi Ray +1
Current training paradigms, optimized for long-horizon reasoning trace execution, have made Large Language Models (LLMs) excel at pattern matching and forward simulation of reasoni…
Trustworthy AI Software Engineers
Aldeida Aleti, Baishakhi Ray, Rashina Hoda +1
With the rapid rise of AI coding agents, the fundamental premise of what it means to be a software engineer is in question. In this vision paper, we examine what it means for an AI…
CodeSense: a Real-World Benchmark and Dataset for Code Semantic Reasoning
Monoshi Kumar Roy, Simin Chen, Benjamin Steenhoek +4
Understanding and reasoning about code semantics is essential for enhancing code LLMs' abilities to solve real-world software engineering (SE) tasks. Although several code reasonin…
Your Compiler is Backdooring Your Model: Understanding and Exploiting Compilation Inconsistency Vulnerabilities in Deep Learning Compilers
Simin Chen, Jinjun Peng, Yixin He +2
Deep learning (DL) compilers are core infrastructure in modern DL systems, offering flexibility and scalability beyond vendor-specific libraries. This work uncovers a fundamental v…
AppForge: From Assistant to Independent Developer -- Are GPTs Ready for Software Development?
Dezhi Ran, Yuan Cao, Mengzhou Wu +10
Large language models (LLMs) have demonstrated remarkable capability in function-level code generation tasks. Unlike isolated functions, real-world applications demand reasoning ov…