软件工程

AI coding agents can create and submit pull requests (PRs) to a common repository at the same time; however, there is little research on the frequency of such concurrent submissions or the cost associated with them. In this study, we use…

Software engineering has a complicated relationship with "correctness". We recognize the challenges of full formal rigor as well as many required properties beyond functional correctness. Although we satisfice in practice, we are still…

Large language models (LLMs) are increasingly used to interpret operational evidence and assist incident response in cloud-native microservice systems. However, recovery-oriented use cases require more than identifying a root cause. After…

Modern software development relies heavily on open-source components. Reusing components accelerates innovation but increases exposure to supply-chain attacks exploiting known vulnerabilities. Software Bills of Materials (SBOMs) improve…

Control Flow Graph (CFG) is an important program representations for software analysis, code understanding, and software maintenance. Traditional CFG generation techniques mainly rely on bytecode or abstract syntax trees. However, these…

CI/CD workflows have become executable operational policy: they decide what gets built, tested, released, and deployed, and they mediate how maintainers interact with delivery infrastructure. That makes them an important measurement point…

Code language models are now trusted collaborators in production workflows for debugging, refactoring, and iterative repair, and every benchmark that evaluates them assumes the instructions they act on are correct. We study what happens…

Modern GPU domain-specific languages (DSLs), such as Triton and TileLang, are increasingly used to implement specialized deep-learning kernels and as target languages for automated kernel-generation systems. Existing DSL-kernel evaluations…

Ensuring software compliance with regulations such as the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (EU AI Act) poses a significant challenge, as requirements engineers must translate complex legal text…

Natural language requirements (NLRs) are essential for bridging communication gaps among diverse stakeholders in software development. However, the inherent ambiguity in NLRs can pose significant challenges. In particular, some requirements…

REST APIs are widely used in industry. Therefore, a lot of research has been focused on how to automatically generate test cases for REST APIs, with few different open-source fuzzers existing in the literature. For a thorough testing,…

Unlike natural-language specifications, executable formal specifications provide machine-checkable constraints for verifying, debugging, and repairing code. However, writing such specifications is labor-intensive, and existing LLM-based…

Role-based multiagent code generation aims to make LLMs more effective on repository-scale problems, moving beyond small programming tasks. We evaluate this approach on 12 Java repositories, finding greater similarity to developer code than…

We present a methodology to systematically assess the scale and impact of an organization's contributions to open source software (OSS). The methodology combines the archival data of Software Heritage with usage metrics, dependency…

Autonomous driving (AD) systems continuously transform multi-rate and asynchronous sensor streams into vehicle actuation through graphs of callbacks, nodes, and middleware components. In such systems, temporal correctness cannot be…

Android provides a wide range of system settings that allow users to control the runtime behaviors of apps, such as screen rotation and UI display. However, setting-related bugs occur when developers do not fully align their apps with the…

COBOL remains critical across banking, insurance, and government infrastructure. However, maintenance is increasingly challenging due to outdated technologies, sparse documentation, and developer retirement, necessitating code translation…

Large language models can generate plausible quantum code, but it is unclear whether they can reliably target the specific software development kit (SDK) version requested by the user. We study this problem as API drift and introduce…

Large language models (LLMs) are increasingly used to port scientific codes across heterogeneous high-performance computing (HPC) programming models, such as translating CUDA to OpenMP, OpenACC, Kokkos or SYCL. However, current evaluations…

The language models that underpin agents have seen a rapid rise in performance on function calling benchmarks. However, the metrics used in the training and evaluation of these models often encourage models to make positive claims even when…