相关论文: Poster: Improving Bug Localization with Report Qua…
Recent findings suggest that Information Retrieval (IR)-based bug localization techniques do not perform well if the bug report lacks rich structured information (eg relevant program entity names). Conversely, excessive structured…
Being light-weight and cost-effective, IR-based approaches for bug localization have shown promise in finding software bugs. However, the accuracy of these approaches heavily depends on their used bug reports. A significant number of bug…
Bug localization is a crucial aspect of software maintenance, running through the entire software lifecycle. Information retrieval-based bug localization (IRBL) identifies buggy code based on bug reports, expediting the bug resolution…
Information Retrieval-based Fault Localization (IRFL) techniques aim to identify source files containing the root causes of reported failures. While existing techniques excel in ranking source files, challenges persist in bug report…
Bug localization is a tedious activity in the bug fixing process in which a software developer tries to locate bugs in the source code described in a bug report. Since this process is time-consuming and requires additional knowledge about…
Bug localization remains a critical yet time-consuming challenge in large-scale software repositories. Traditional information retrieval-based bug localization (IRBL) methods rely on unchanged bug descriptions, which often contain noisy…
Bug fixing is a complex and time-consuming task in software development. Bug localization research tends to focus on the accuracy of automated tools that suggest source code files for developers to look at. However, little is known about…
During software maintenance and evolution, developers need to deal with a large number of change requests by modifying existing code or adding code into the system. An efficient tackling of change request calls for an accurate localising of…
We explore the application of Information Retrieval (IR) based bug localization methods at a large industrial setting, Facebook. Facebook's code base evolves rapidly, with thousands of code changes being committed to a monolithic repository…
Software bugs pose a significant challenge during development and maintenance, and practitioners spend nearly 50% of their time dealing with bugs. Many existing techniques adopt Information Retrieval (IR) to localize a reported bug using…
Locating bugs is an important, but effort-intensive and time-consuming task, when dealing with large-scale systems. To address this, Information Retrieval (IR) techniques are increasingly being used to suggest potential buggy source code…
Despite decades of research, software bug localization remains challenging due to heterogeneous content and inherent ambiguities in bug reports. Existing methods, such as Information Retrieval (IR)-based approaches, often attempt to match…
Bug localisation, the study of developing methods to localise the files requiring changes to resolve bugs, has been researched for a long time to develop methods capable of saving developers' time. Recently, researchers are starting to…
Bug report management is a costly software maintenance process comprised of several challenging tasks. Given the UI-driven nature of mobile apps, bugs typically manifest through the UI, hence the identification of buggy UI screens and UI…
Many automated tasks in software maintenance rely on information retrieval techniques to identify specific information within unstructured data. Bug localization is such a typical task, where text in a bug report is analyzed to identify…
One of the most important tasks related to managing bug reports is localizing the fault so that a fix can be applied. As such, prior work has aimed to automate this task of bug localization by formulating it as an information retrieval…
The performance of a machine learning system is not only determined by the model but also, to a substantial degree, by the data it is trained on. With the increasing use of machine learning, issues related to data quality have become a…
Context: IR-based bug localization is a classifier that assists developers in locating buggy source code entities (e.g., files and methods) based on the content of a bug report. Such IR-based classifiers have various parameters that can be…
Modern Deep Learning (DL) architectures based on transformers (e.g., BERT, RoBERTa) are exhibiting performance improvements across a number of natural language tasks. While such DL models have shown tremendous potential for use in software…
Bug localization refers to the identification of source code files which is in a programming language and also responsible for the unexpected behavior of software using the bug report, which is a natural language. As bug localization is…