26,098 papers · page 70 of 1,305
Software security faces a persistent gap: static analysis tools detect vulnerabilities effectively, but their technical outputs remain inaccessible to most developers. This leads to mounting security debt, as organizations must rely on security specialists for remediation, creati…
Decentralized Identity (DID) enhances authentication and privacy by empowering individuals to control their own digital identities, which has gained traction globally. To our knowledge, this paper presents the first end-to-end verification effort (from design to implementation) o…
Large language models (LLMs) excel at generating code from natural language (NL) descriptions. However, the plain textual descriptions are inherently ambiguous and often fail to capture complex requirements like intricate system behaviors, conditional logic, and architectural con…
Timely identification of issue reports reflecting software vulnerabilities is crucial, particularly for Internet-of-Things (IoT) where analysis is slower than non-IoT systems. While Machine Learning (ML) and Large Language Models (LLMs) detect vulnerability-indicating issues in n…
While static program analyzers based on abstract interpretation implement precision-improving techniques to reduce false alarms, such as loop unrolling, their computational cost requires carefully devised heuristics for selective application. Manually designing such heuristics is…
Smart contract comment generation has gained traction as a means to improve code comprehension and maintainability in blockchain systems. However, evaluating the quality of generated comments remains a challenge. Traditional metrics such as BLEU and ROUGE fail to capture domain-s…
This paper studies programmer visual attention on code as it relates to underlying function call graphs during code summarization. Programmer visual attention refers to where people look when performing a software engineering task, and code summarization is the task of writing a …
In large-scale software development, multilingual projects, those involving multiple interacting programming languages, have become increasingly common in both industry and the open-source community. Research indicates that cross-language dependencies in these projects can increa…
In recent years, CodeLLMs have revolutionized the way developers interact with code. One notable application has been program translation, such as converting COBOL to Java or C to Rust. A critical challenge in this domain is ensuring that CodeLLMs are trained on programs that cov…
Large Language Models (LLMs) are increasingly integrated into software engineering (SE) tools for tasks that extend beyond code synthesis, including judgment under uncertainty and reasoning in ethically significant contexts. We present a fully automated framework for assessing et…
Detecting security vulnerabilities in backend Web applications as well as mobile apps is extremely important. Static analysis for vulnerability analysis has subsequently developed as an important field of research. Researchers need extensible frameworks to avoid starting from scr…
Improving the efficiency of software integration testing is a critical challenge in the automotive industry, particularly as Electronic Control Unit (ECU) architectures become increasingly complex. This paper addresses the automation of integration test script generation by lever…
The focus on rapid software delivery inevitably results in the accumulation of technical debt, which, in turn, affects quality and slows future development. Our primary aim is to discover how companies keep their codebases maintainable and how code improvements might be automated…
Robotic aerial vehicles (RAVs), particularly drones, are crucial in civil and military sectors. However, researchers have found that adversaries can inject noise into sensor measurements and cause physical impacts on the RAVs like crashes. Although identifying such signal injecti…
The effectiveness of testing in uncovering software defects depends not only on the characteristics of the test inputs and how thoroughly they exercise the software, but also on the quality of the oracles used to determine whether the software behaves as expected. Therefore, asse…
Generation of thorough test oracles is an open problem. Popular test case generators, like EvoSuite and Randoop, rely on implicit, rule-based, and regression oracles that miss failures that depend on the semantics of the program under test. Formal specifications can yield test or…
Three-way merge tools play crucial roles in modern software development, where a developer forks a branch to make local modifications and requests it to be merged into the main branch via a "pull request." Despite its importance, the task has traditionally been defined in an intu…
Large Language Models (LLMs) are increasingly deployed within agentic systems—collections of interacting, LLM-powered agents that execute complex, adaptive workflows using memory, tools, and dynamic planning. While enabling powerful new capabilities, these systems also introduce …
Autonomous Driving Systems (ADS) must reliably perceive and react to complex environments, even when sensor blind spots obscure critical objects. While existing testing methods often focus on dynamic interactions, they significantly underestimate safety risks arising from both dy…
We present SynVer — a novel, general purpose synthesizer for C programs equipped with machine-checked proofs of correctness using the Verified Software Toolchain. To do so, SynVer employs two Large Language Models (LLMs): the first generates candidate programs from user-provided …