3,458 papers · page 28 of 173
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…
In real-world microservice systems, the newly deployed service - one kind of change service, could lead to a new type of minority fault. Existing state-of-the-art (SOTA) methods for fault localization rarely consider the imbalanced fault classification in change service. This pap…
Modern software is often implemented in multiple interacting programming languages. When performing static analysis of such software, it is desirable to reuse existing single-language analyses to allow access to the results of decades of implementation effort.
Software vulnerabilities pose critical security and risk concerns. Many techniques are proposed to assess and prioritize vulnerabilities. To evaluate their performance, researchers often craft datasets from limited data sources, lacking a global overview of broad vulnerability in…
Data Distribution Service (DDS) is a distributed network protocol widely used in cyber-physical systems. DDS provides flexible configurations defined in the formal design specification for safety and security. However, DDS programs suffer from both semantic bugs violating design …