26,098 papers · page 131 of 1,305
When using large language models (LLMs) for code translation of complex software, numerous compilation and runtime errors can occur due to insufficient context awareness. To address this issue, this paper presents a code translation method based on call graphs and bridged debugge…
Recent Large Language Models (LLMs) have demonstrated significant capabilities in generating code snippets directly from problem statements. This increasingly automated process mirrors traditional human-led software development, where code is often written in response to a requir…
This paper briefly outlines a high-level architecture of a context-aware ethics-based negotiation approach in which autonomous systems utilize user ethical profiles, together with contextual factors and user status, to control their autonomy while collaboratively negotiating to r…
In this paper, we present MADE-WIC, a large dataset of functions and their comments with multiple annotations for technical debt and code weaknesses leveraging different state-of-the-art approaches. It contains about 860K code functions and more than 2.7M related comments from 12…
Cross-lingual code clone detection has gained attention in software development due to the use of multiple programming languages. Recent advances in machine learning, particularly Large Language Models (LLMs), have motivated a reexamination of this problem.
Deep learning (DL) frameworks are the fundamental infrastructure for various DL applications. Framework defects can profoundly cause disastrous accidents, thus requiring sufficient detection. In previous studies, researchers adopt DL models as test inputs combined with mutation t…
Deep Neural Networks (DNNs) are being trained and trusted for performing fairly complex tasks, even in business- and safety-critical applications. This necessitates that they be formally analyzed before deployment. Scalability of such analyses is a major bottleneck in their wides…
The most promising applications of quantum computing are centered around solving search and optimization tasks, particularly in fields such as physics simulations, quantum chemistry, and finance. However, the current quantum software testing methods face practical limitations whe…
Producing accurate software models is crucial in model-driven software engineering (MDE). However, modeling complex systems is an error-prone task that requires deep application domain knowledge. In the past decade, several automated techniques have been proposed to support acade…
The maintenance of build systems imposes a considerable overhead on software development. Since automated quality assurance methods are rarely applied to build specifications, the importance of the role peer code review plays in the maintenance of build systems is amplified. Yet …
The task of modernizing legacy software has gained increasing attention in recent years. Old code is prone to security vulnerabilities, and is difficult to maintain and upgrade. Manual approaches to modernize legacy software involve intensive human effort and are challenging to s…
In recent years, the integration of AI tools such as ChatGPT into software development has grown significantly, reflecting broader trends in AI-assisted workflows [8]. These tools have great potential to improve decision making related to software patches in pull requests (PR), w…
In this experience paper, we design, implement, and evaluate a new static type-error detection tool for Python. To build a practical tool, we first collected and analyzed 68 real-world type errors gathered from 20 open-source projects. This empirical investigation revealed four k…
Unit testing, essential for identifying bugs, is often neglected due to time constraints. Automated test generation tools exist but typically lack readability and require developer intervention. Large Language Models (LLMs) like GPT and Mistral show potential in test generation, …
This study evaluates OSS project survivability using the Kaplan-Meier Survival Function and polynomial regression models. The key factors identified include the number of contributors and project popularity, which significantly influence survivability. Traditional indicators like…
Fuzz driver generation (FDG) is a fundamental technique for fuzzing library software. Existing FDG approaches have been highly successful with open-source libraries. However, in practice, due to the complex nature of OEM Android frameworks (e.g., customized compilation toolchains…
Microservice architecture has become a popular architecture adopted by many cloud applications. However, identifying the root cause of a failure in microservice systems is still a challenging and time-consuming task. In recent years, researchers have introduced various causal inf…
We investigate a modification of the classical Bounded Model Checking (BMC) procedure that does not handle loops through unrolling but via modifications to the control flow graph (CFG). A portion of the CFG representing a loop is replaced by a node asserting invariants of the loo…
Within the realms of scientific computing, large-scale data processing, and artificial intelligence-powered computation, disparities in performance, which originate from differing code implementations, directly influence the practicality of the code. Although existing works tried…
Interior unsafe is an essential design paradigm advocated by the Rust community in system software development. However, there is little official guidance or few best practices regarding how to encapsulate unsafe code and achieve interior unsafe. To address this issue, this paper…