3,458 papers · page 29 of 173
The availability of Large Language Models (LLMs) which can generate code, has made it possible to create tools that improve developer productivity. Integrated development environments or IDEs which developers use to write software are often used as an interface to interact with L…
Microtask programming enables software engineers such as freelancers and part-time employees to contribute to software projects even when they can not spend much time on them. It decomposes software design into small, self-contained specifications. The decomposed specifications e…
Equivalence analysis focuses on assessing whether different programs, or different versions of a program, exhibit identical behavior. While extensive research has been done on equivalence analysis, there is a lack of detailed and quantitative reasoning techniques for non-equivale…
While there exist several tools to leverage Large Language Models (LLMs) for code generation, their capabilities are limited to the source code editor and are disconnected from the overall software development process. These tools typically generate standalone code snippets that …
Static code analyzers are now a common part of the codereview process. These automated tools integrate into the code review process by commenting on code changes and suggesting improvements, in the same way as human reviewers. The comments made by static analyzers often trigger a…
A version control system, such as Git, requires a way to integrate changes from different developers or branches. Given a merge scenario, a merge tool either outputs a clean integration of the changes, or it outputs a conflict for manual resolution. A clean integration is correct…
Since its major release in 2006, the Unified Extensible Firmware Interface (UEFI) has become the industry standard for interfacing a computer's hardware and operating system, replacing BIOS. UEFI has higher privileged security access to system resources than any other software co…
Logs produced by software applications are invaluable for spotting deviations from expected system behavior. However, automatically detecting anomalies from log data is challenging due to the volume, semi-structured nature, lack of standard formatting, and potential evolution of …
WebAssembly (abbreviated Wasm) has emerged as a cornerstone of web development, offering a compact binary format that allows high-performance applications to run at near-native speeds in web browsers. Despite its advantages, Wasm's binary nature presents significant challenges fo…
Deep Neural Network (DNN) testing is one of the most widely-used techniques to guarantee the quality of DNNs. However, DNN testing typically requires the ground truth of test inputs, which is time-consuming and labor-intensive to obtain. To relieve the labeling-cost problem of DN…
Directed grey-box fuzzing is a widely used automatic testing technique that has helped developers test specific code space in the target program. Although many directed fuzzers are designed to test the Linux kernel, challenges still remain due to the complexity of industrial requ…
Machine learning (ML)-based models are often black box, making it challenging to understand and interpret their decision-making processes. Surrogate models are constructed to approximate the behavior of a target model and are an essential tool for analyzing black-box models. The …
Context Comprehending code is crucial in all areas of software development, with many existing supporting tools and techniques for various languages. However, for R, a widely used programming language, especially in the field of statistical computing, the support is limited. R of…
Context Many researchers rely on the R programming language to perform their statistical analyses and visualizations in the form of R scripts. However, recent research and experience show, that many of these scripts contain problems. From being hard to comprehend by combining sev…
In recent years, automatic program repair has gained much attention in the research community. Generally, program repair approaches consider a faulty program and a test suite that captures the program's intended behavior. The goal is automatically generating a patch that corrects…
Type recovery in stripped binaries is a critical and challenging task in reverse engineering, as it is the basis for many security applications (e.g., vulnerability detection). Traditional analysis methods are limited by software complexity and emerging types in real-world projec…
As mobile applications become increasingly integral to our daily lives, concerns about ethics have grown drastically. Users share their experiences, report bugs, and request new features in application reviews, often highlighting safety, privacy, and accountability concerns. Appr…
Large Language Models (LLMs), such as GPT-4, StarCoder, and Code Llama, are transforming the way developers approach programming by automatically generating code based on given contexts, such as natural language descriptions or incomplete surrounding code. Despite advancements, g…
This research explores the transformative potential of generative AI in software development. Generative AI is revolutionizing the field by offering capabilities to automatically generate, refactor, and test code. Through the use of action research, new methods and tools based on…
Traceability plays a vital role in facilitating various software development activities by establishing the traces between different types of artifacts (e.g., issues and commits in software repositories). Among the explorations for automated traceability recovery, the IR (Informa…