3,458 papers · page 15 of 173
Acceptance criteria (ACs) play a critical role in software development by clearly defining the conditions under which a software feature satisfies stakeholder expectations. However, manually creating accurate, comprehensive, and unambiguous acceptance criteria is challenging, par…
Incremental program analysis (IPA) has gained increasing attention as an effective approach for maintaining up-to-date analysis results by leveraging previously computed results in response to program changes. Consequently, a variety of IPA algorithms and tools have been proposed…
Large language models (LLMs) have demonstrated strong capabilities in code generation, underscoring the critical need for rigorous and comprehensive evaluation. Existing evaluation approaches fall into three categories, including human-centered, metric-based, and LLM-based. Consi…
USB is a widely used interface standard in modern operating systems for connecting computers to various external devices. External devices can launch attacks by injecting random data into the host via USB, causing memory errors or even system-level crashes. Fuzzing has been prove…
Copy-paste-modify is a widespread and pragmatic practice in software development, where developers adapt reused code snippets, sourced from platforms such as Stack Overflow, GitHub, or LLM outputs, into their local codebase. A critical yet underexplored aspect of this adaptation …
End-to-end autonomous driving systems (ADSs), with their strong capabilities in environmental perception and generalizable driving decisions, are attracting growing attention from both academia and industry. However, once deployed on public roads, ADSs are inevitably exposed to d…
Logging code is written by developers to capture system runtime behavior and plays a vital role in debugging, performance analysis, and system monitoring. However, defects in logging code can undermine the usefulness of logs and lead to misinterpretations. Although prior work has…
Recent advances in reasoning-capable large lan-guage models (LLMs) have led to their application in a wide range of tasks, including log parsing. These LLMs generate intermediate reasoning traces during inference, offering a unique opportunity to analyze and improve their perform…
The resilience of large-scale AI training platforms are fundamental to enabling contemporary AI innovation and business development. However, with the rapid increase in the scale and complexity of AI model training tasks, anomalies become the norm rather than the exception at sca…
Automating code review with Large Language Models (LLMs) shows immense promise, yet practical adoption is hampered by their lack of reliability, context-awareness, and control. To address this, we propose Specification-Grounded Code Review (SGCR), a framework that grounds LLMs in…
LLMs demonstrate strong performance in automated software engineering, particularly for code generation and issue resolution. While proprietary models like GPT-4o achieve high benchmarks scores on SWE-bench, their API dependence, cost, and privacy concerns limit adoption. Open-so…
Protocol specifications, defined in Request for Comments (RFCs), play a critical role in ensuring the correctness of protocol software systems. To check consistency, specification–implementation pairs are essential for testing and verification. However, existing efforts in specif…
Large Language Models (LLMs) can translate natural language requirements into code, yet empirical analyses of representative models reveal that semantic errors—programs that compile but behave incorrectly—constitute the majority of observed faults (e.g., >60% on DeepSeek-Coder-6.…
Deep learning compilers optimize DNN program execution by capturing them as operator-based computation graphs. However, developers’ deep learning programs often contain complex Python language features that prevent compilers from recognizing the entire program as a complete compu…
God Header Files, large header files included by numerous other code files, present significant challenges for code comprehension and maintenance. Existing approaches leverage various code similarity metrics to decompose them, but these metrics do not always capture the code’s fu…
Redundant test cases, although well-studied in software engineering, are previously underexplored in UI testing of mobile apps. Our study of real-world test suites shows that, equipped with large-scale testing suites, redundancy in UI testing often manifests as redundant UI inter…
Large language models (LLMs) have demonstrated impressive capabilities in code generation, by leveraging retrieval-augmented generation (RAG) methods. However, the computational costs associated with LLM inference, particularly in terms of latency and energy consumption, have rec…
The interpreter and the Just-In-Time (JIT) compiler are two core components of modern JavaScript engines, both of which take bytecodes as input. Most bugs in these components are closely related to specific bytecodes. Therefore, effective fuzzing should pay close attention to how…
The rapid growth of audio-centric platforms and applications such as Whatsapp and Twitter has transformed the way people communicate and share audio content in modern society. However, these platforms are increasingly misused to disseminate harmful audio content, such as hate spe…
Robots are increasingly becoming part of our daily lives, interacting with both the environment and humans to perform their tasks. The software of such robots often undergoes upgrades, for example, to add new functionalities, fix bugs, or delete obsolete functionalities. As a res…