Researchers have made significant progress in automating the software development
process in the past decades. Automated techniques for issue summarization, bug …

Large Language Models (LLMs) show promise in transforming software development, with a
growing interest in integrating them into more intelligent apps. Frameworks like LangChain …

Type inference for dynamic programming languages such as Python is an important yet
challenging task. Static type inference techniques can precisely infer variables with enough …

After decades of research, constructing call graphs for modern C-based software remains
either imprecise or inefficient when scaling up to the ever-growing complexity. The main …

When dealing with millions of lines of C code, we still cannot have the cake and eat it: type
analysis for call graph construction is scalable yet highly imprecise. We address this …

Constructing a static call graph requires trade-offs between soundness and precision.
Program analysis techniques for constructing call graphs are unfortunately usually …

Python has emerged as one of the most popular programming languages, extensively
utilized in domains such as machine learning, data analysis, and web applications. Python's …

An increasing number of researchers rely on computational methods to generate or
manipulate the results described in their scientific publications. Software created to this end …

Python is a widely used programming language that powers important application domains
such as machine learning, data analysis, and web applications. For many programs in these …

While Large Language Models'(LLMs) coding capabilities have advanced rapidly,
corresponding evaluation benchmarks on real-world programming setups are yet to catch …