2,847 papers · page 17 of 143
Question answering (QA) is a fundamental task of large language models (LLMs), which requires LLMs to automatically answer human-posed questions in natural language. However, LLMs are known to distort facts and make non-factual statements (i.e., hallucinations) when dealing with …
Deep learning (DL) has revolutionized various software engineering tasks. Particularly, the emergence of AI code generators has pushed the boundaries of automatic programming to synthesize entire programs based on user-defined specifications in natural language. However, it remai…
Branching repositories facilitates efficient software development but can also inadvertently propagate vulnerabilities. When an original branch is patched, other unfixed branches remain vulnerable unless the patch is successfully ported. However, due to inherent discrepancies bet…
Docker building is a critical component of containerization in modern software development, automating the process of packaging and converting sources into container images. It is not uncommon to find that Docker build faults (DBFs) occur frequently across Docker-based projects, …
Recent advancements in large language models (LLMs) have significantly advanced the automation of software development tasks, including code synthesis, program repair, and test generation. More recently, researchers and industry practitioners have developed various autonomous LLM…
Distributed tracing is a pivotal technique for software operators to understand and diagnose issues within microservice-based systems, offering a comprehensive view of user requests propagated through various services. However, the unprecedented volume of traces imposes expensive…
The safety and reliability of Automated Driving Systems (ADS) are paramount, necessitating rigorous testing methodologies to uncover potential failures before deployment. Traditional testing approaches often prioritize either natural scenario sampling or safety-critical scenario …
Multilingual systems are prevalent and broadly impactful, but also complex due to the intricate interactions between the heterogeneous programming languages the systems are developed in. This complexity is further aggravated by the diversity of cross-language interoperability acr…
Floating-point constraint solving is challenging due to the complex representation and non-linear computations. Search-based constraint solving provides an effective method for solving floating-point constraints. In this paper, we propose QSF to improve the efficiency of search-b…
With the increasing demand for handling large-scale and complex data, data science (DS) applications often suffer from long execution time and rapid RAM exhaustion, which leads to many serious issues like unbearable delays and crashes in financial transactions. As popular DS libr…
Large Language Models (LLMs) are prone to hallucinations, e.g., factually incorrect information, in their responses. These hallucinations present challenges for LLM-based applications that demand high factual accuracy. Existing hallucination detection methods primarily depend on …
Deep Learning-based Vulnerability Detection (DLVD) techniques have garnered significant interest due to their ability to automatically learn vulnerability patterns from previously compromised code. Despite the notable accuracy demonstrated by pioneering tools, the broader applica…
Detecting vulnerability fix commits in open-source software is crucial for maintaining software security. To help OSS identify vulnerability fix commits, several automated approaches are developed. However, existing approaches like VulFixMiner and CoLeFunDa, focus solely on code …
Deep Learning (DL) models are useful for many software engineering tasks. However, these models are susceptible to adversarial attacks, partly because they learn spurious features that incur spurious correlations between these features and model predictions. In this paper, we tac…
With the rapid advancement of cloud-native computing, securing cloud environments has become an important task. Log-based Anomaly Detection (LAD) is the most representative technique used in different systems for attack detection and safety guarantee, where multiple LAD methods a…
Project building is pivotal to support various program analysis tasks, such as generating intermediate representation code for static analysis and preparing binary code for vulnerability reproduction. However, automating the building process for C/C++ projects is a highly complex…
Unit testing is crucial for software development and maintenance. Effective unit testing ensures and improves software quality, but writing unit tests is time-consuming and labor-intensive. Recent studies have proposed deep learning (DL) techniques or large language models (LLMs)…
Bug report reproduction is a crucial but time-consuming task to be carried out during mobile app maintenance. To accelerate this process, researchers have developed automated techniques for reproducing mobile app bug reports. However, due to the lack of an effective mechanism to …
WebAssembly has become the preferred smart contract format for various blockchain platforms due to its high portability and near-native execution speed. To effectively understand WebAssembly contracts, it is crucial to recover high-level type signatures because of the limited typ…
Can a fuzzer cover more code with minimal corruption of the initial seed? Before a seed is fuzzed, the early greybox fuzzers first systematically enumerated slightly corrupted inputs by applying every mutation operator to every part of the seed, once per generated input. The hope…