Related papers: An Empirical Study on Common Defects in Modern Web…
Large Language Models (LLMs) are gaining popularity among software engineers. A crucial aspect of developing effective code generation LLMs is to evaluate these models using a robust benchmark. Evaluation benchmarks with quality issues can…
Patch reviewing is critical for software development, especially in distributed open-source development, which highly depends on voluntary work, such as Linux. This paper studies the past 10 years of patch reviews of the Linux memory…
In the past couple of decades, significant research efforts are devoted to the prediction of software bugs. However, most existing work in this domain treats all bugs the same, which is not the case in practice. It is important for a defect…
Recent studies have shown that bugs can be categorized into intrinsic and extrinsic types. Intrinsic bugs can be backtracked to specific changes in the version control system (VCS), while extrinsic bugs originate from external changes to…
Large Language Models (LLMs) increasingly serve as research assistants, yet their reliability in scholarly tasks remains under-evaluated. In this work, we introduce PaperAsk, a benchmark that systematically evaluates LLMs across four key…
Importance of document clustering is now widely acknowledged by researchers for better management, smart navigation, efficient filtering, and concise summarization of large collection of documents like World Wide Web (WWW). The next…
A recent trend towards running more demanding web applications, such as video games or client-side LLMs, in the browser has led to the adoption of the WebGPU standard that provides a cross-platform API exposing the GPU to websites. This…
In 2023, images on the web make up 41% of transmitted data, significantly impacting the performance of web apps. Fortunately, image formats like WEBP and AVIF could offer advanced compression and faster page loading, but may face…
This work introduces CodeFlowLM, an incremental learning framework for Just-In-Time Software Defect Prediction (JIT-SDP) that leverages pre-trained language models (PLMs). Unlike traditional online learners, CodeFlowLM employs continual…
Despite the advancements in software testing, bugs still plague deployed software and result in crashes in production. When debugging issues -- sometimes caused by "heisenbugs" -- there is the need to interpret core dumps and reproduce the…
With technical performance being similar for various web browsers, improving user perceived performance is integral to optimizing browser quality. We investigated the importance of priming, which has a well-documented ability to affect…
The complexity of code reviews has driven efforts to automate review comments, but prior approaches oversimplify this task by treating it as snippet-level code-to-text generation and relying on text similarity metrics like BLEU for…
Reusable software components, typically distributed as packages, are a central paradigm of modern software development. The JavaScript ecosystem serves as a prime example, offering millions of packages with their use being promoted as…
Web client fingerprinting has become a widely used technique for uniquely identifying users, browsers, operating systems, and devices with high accuracy. While it is beneficial for applications such as fraud detection and personalized…
Large language models of code (Code-LLMs) have recently brought tremendous advances to code completion, a fundamental feature of programming assistance and code intelligence. However, most existing works ignore the possible presence of bugs…
In this paper, we first collect and track a large number of fixed and unfixed violations across revisions of software. The empirical analyses reveal that there are discrepancies in the distributions of violations that are detected and those…
Smartphones and tablets have established themselves as mainstays in the modern computing landscape. It is conceivable that in the near future such devices may supplant laptops and desktops, becoming many users primary means of carrying out…
Previous learning-based vulnerability detection methods relied on either medium-sized pre-trained models or smaller neural networks from scratch. Recent advancements in Large Pre-Trained Language Models (LLMs) have showcased remarkable…
The recent swift development of LLMs like GPT-4, Gemini, and GPT-3.5 offers a transformative opportunity in medicine and healthcare, especially in digital diagnostics. This study evaluates each model diagnostic abilities by interpreting a…
Quantum Computers (QCs), once they mature, will be able to solve some problems faster than Classic Computers. This phenomenon is called "quantum advantage" (or a stronger term "quantum supremacy"). Quantum advantage will help us to speed up…