4,951 papers · page 4 of 248
In Federated Learning, clients train models on local data and send updates to a central server, which aggregates them into a global model using a fusion algorithm. This collaborative yet privacy-preserving training comes at a cost. FL developers face significant challenges in att…
This paper explores the integration of Visual Code Assistants in Integrated Development Environments (IDEs). In Software Engineering, whiteboard sketching is often the initial step before coding, serving as a crucial collaboration tool for developers. Previous studies have invest…
AI-based mission-critical software exposes a blessing and a curse: its inherent statistical nature allows for flexibility in result quality, yet the mission-critical importance demands adherence to stringent constraints such as execution deadlines. This creates a space for trade-…
A common practice in the reliability engineering of cloud services involves the collection of monitoring metrics, followed by comprehensive analysis to identify performance issues. However, existing methods often fall short of detecting diverse and evolving anomalies across diffe…
Code retrieval, which retrieves code snippets based on users' natural language descriptions, is widely used by devel-opers and plays a pivotal role in real-world software development. The advent of deep learning has shifted the retrieval paradigm from lexical-based matching towar…
Runtime verification (RV) found hundreds of bugs by monitoring passing tests against formal specifications (specs). RV first instruments a program to obtain relevant events, e.g., method calls, to monitor. A hindrance to RV adoption, especially in continuous integration, is its h…
Android applications are pervasively adopted and heavily relied on in our daily life, leading to the growing demand for enhanced user experiences, such as ease for operation and robustness. Nevertheless, developers continue to prioritize traditional functionality and performance,…
Code refinement aims to enhance existing code by addressing issues, refactoring, and optimizing to improve quality and meet specific requirements. As software projects scale in size and complexity, the traditional iterative exchange between re-viewers and developers becomes incre…
The Linux kernel is actively-developed and widely-used. It supports billions of devices of all classes, from high-performance computing to the Internet-of-Things, in part because of its sophisticated configuration system, which automatically tailors the source code according to t…
Log-based anomaly detection is essential for maintaining software availability. However, existing log-based anomaly detection approaches heavily rely on fine-grained exact labels of log entries which are very hard to obtain in real-world systems. This brings a key problem that an…
Software security is of utmost importance for most software systems. Developers must systematically select, plan, design, implement, and especially, maintain and evolve security features-functionalities to mitigate attacks or protect personal data such as cryptography or access c…
Test oracles play a crucial role in software testing, enabling effective bug detection. Despite initial promise, neural methods for automated test oracle generation often result in a large number of false positives and weaker test oracles. While LLMs have shown impressive effecti…
Computational notebooks are intended to prioritize the needs of scientists, but little is known about how scientists interact with notebooks, what requirements drive scientists' software development processes, or what tactics scientists use to meet their requirements. We conducte…
Deep code models are vulnerable to adversarial attacks, making it possible for semantically identical inputs to trigger different responses. Current black-box attack methods typically prioritize the impact of identifiers on the model based on custom importance scores or program c…
As embedded devices become increasingly popular, monolithic firmware, known for its execution efficiency and simplicity, is widely used in resource-constrained devices. Different from ordinary firmware, the monolithic firmware image is packed without the file that indicates its f…
Recent advancements in automated program repair (APR) have been significantly driven by the application of Large Language Models (LLMs). In particular, the integration of LLMs with traditional template-based repair methods has demonstrated effective outcomes. Despite this, the sy…
Deep Reinforcement Learning (DRL) is a paradigm of artificial intelligence where an agent uses a neural network to learn which actions to take in a given environment. DRL has recently gained traction from being able to solve complex environments like driving simulators, 3D roboti…
Testing for accessibility is a significant step when developing software, as it ensures that all users, including those with disabilities, can effectively engage with web and mobile applications. While automated tools exist to detect accessibility issues in software, none are as …
Commit messages provide descriptions of the modifications made in a commit using natural language, making them crucial for software maintenance and evolution. Recent developments in Large Language Models (LLMs) have led to their use in generating high-quality commit messages, suc…
Deep Neural Networks (DNN) have found numerous applications in various domains, including fraud detection, medical diagnosis, facial recognition, and autonomous driving. However, D NN - based systems often suffer from reliability issues due to their inherent complexity and the st…