相关论文: Improving IR-Based Bug Localization with Context-A…

Modern retrieval pipelines increasingly rely on query reformulation and neural reranking to improve effectiveness, but this comes at a significant computational cost and introduces a fundamental tradeoff between recall and query drift.…

Bugs are inescapable during software development due to frequent code changes, tight deadlines, etc.; therefore, it is important to have tools to find these errors. One way of performing bug identification is to analyze the characteristics…

The increasing amount of data on the Web, in particular of Linked Data, has led to a diverse landscape of datasets, which make entity retrieval a challenging task. Explicit cross-dataset links, for instance to indicate co-references or…

The rapid pace of large-scale software development places increasing demands on traditional testing methodologies, often leading to bottlenecks in efficiency, accuracy, and coverage. We propose a novel perspective on software testing by…

Bugs, especially those in concurrent systems, are often hard to reproduce because they manifest only under rare conditions. Testers frequently encounter failures that occur only under specific inputs, even when occurring with low…

Fuzzing has proven to be very effective for discovering certain classes of software flaws, but less effective in helping developers process these discoveries. Conventional crash-based fuzzers lack enough information about failures to…

Recent years have witnessed the growing demands for resolving numerous bug reports in software maintenance. Aiming to reduce the time testers/developers take in perusing bug reports, the task of bug report summarization has attracted a lot…

Fuzzing is a highly-scalable software testing technique that uncovers bugs in a target program by executing it with mutated inputs. Over the life of a fuzzing campaign, the fuzzer accumulates inputs inducing new and interesting target…

As a popular Q&A site for programming, Stack Overflow is a treasure for developers. However, the amount of questions and answers on Stack Overflow make it difficult for developers to efficiently locate the information they are looking for.…

Fuzzing has become a commonly used approach to identifying bugs in complex, real-world programs. However, interpreters are notoriously difficult to fuzz effectively, as they expect highly structured inputs, which are rarely produced by most…

Computer Emergency Response Teams (CERTs) face increasing challenges processing the growing volume of security-related information. Daily manual analysis of threat reports, security advisories, and vulnerability announcements leads to…

Developers are increasingly overwhelmed by AI-generated issue reports that lack actionability and reproducibility, eroding trust in automated bug detection tools. In this paper, we present IssueSpecter, an automated tool that finds bugs in…

The utilization of third-party open-source libraries is widespread in modern software development. Due to the dependency relationships, vulnerabilities within open-source libraries pose significant security threats to downstream software.…

In-context Ranking (ICR) is an emerging paradigm for Information Retrieval (IR), which leverages contextual understanding of LLMs by directly incorporating the task description, candidate documents, and the query into the model's input…

We present the Benchmark of Information Retrieval (IR) tasks with Complex Objectives (BIRCO). BIRCO evaluates the ability of IR systems to retrieve documents given multi-faceted user objectives. The benchmark's complexity and compact size…

With the increasing complexity and rapid expansion of the scale of AI systems in cloud platforms, the log data generated during system operation is massive, unstructured, and semantically ambiguous, which brings great challenges to fault…

Identifying Bug-Inducing Commits (BICs) is fundamental for understanding software defects and enabling downstream tasks such as defect prediction and automated program repair. Yet existing SZZ-based approaches rely on git blame, restricting…

Bank supervisors face the complex task of ensuring that new measures are consistently aligned with historical precedents. To address this challenge, we introduce a novel Information Retrieval (IR) System tailored to assist supervisors in…

Case Based Reasoning (CBR) is an intelligent way of thinking based on experience and capitalization of already solved cases (source cases) to find a solution to a new problem (target case). Retrieval phase consists on identifying source…

Natural language elements in source code, e.g., the names of variables and functions, convey useful information. However, most existing bug detection tools ignore this information and therefore miss some classes of bugs. The few existing…