4,951 papers · page 42 of 248
Automatic machine learning, or AutoML, holds the promise of truly democratizing the use of machine learning (ML), by substantially automating the work of data scientists. However, the huge combinatorial search space of candidate pipelines means that current AutoML techniques, gen…
One prominent tactic used to keep malicious behavior from being detected during dynamic test campaigns is logic bombs, where malicious operations are triggered only when specific conditions are satisfied. Defusing logic bombs remains an unsolved problem in the literature. In this…
Native code is now commonplace within Android app packages where it co-exists and interacts with Dex bytecode through the Java Native Interface to deliver rich app functionalities. Yet, state-of-the-art static analysis approaches have mostly overlooked the presence of such native…
While the long-term effects of the COVID-19 pandemic on software professionals and organizations are difficult to predict, it seems likely that working from home, remote-first teams, distributed teams, and hybrid (part-remote/part-office) teams will be more common. It is therefor…
Neural networks can be regarded as a new programming paradigm, i.e., instead of building ever-more complex programs through (often informal) logical reasoning in the programmers' mind, complex 'AI' systems are built by optimising generic neural network models with big data. In th…
The npm registry is one of the pillars of the JavaScript and Type-Script ecosystems, hosting over 1.7 million packages ranging from simple utility libraries to complex frameworks and entire applications. Each day, developers publish tens of thousands of updates as well as hundred…
Crash localization, an important step in debugging crashes, is challenging when dealing with an extremely large number of diverse applications and platforms and underlying root causes. Large-scale error reporting systems, e.g., Windows Error Reporting (WER), commonly rely on manu…
In community-based software development, developers frequently rely on live-chatting to discuss emergent bugs/errors they encounter in daily development tasks. However, it remains a challenging task to accurately record such knowledge due to the noisy nature of interleaved dialog…
Source code summaries are important for program comprehension and maintenance. However, there are plenty of programs with missing, outdated, or mismatched summaries. Recently, deep learning techniques have been exploited to automatically generate summaries for given code snippets…
GitHub Sponsors, launched in 2019, enables donations to individual open source software (OSS) developers. Financial support for OSS maintainers and developers is a major issue in terms of sustaining OSS projects, and the ability to donate to individuals is expected to support the…
Software systems must be updated regularly to address changing requirements and urgent issues like security-related bugs. Traditionally, updates are performed by shutting down the system to replace certain components. In modern software organizations, updates are increasingly fre…
A rendering regression is a bug introduced by a web browser where a web page no longer functions as users expect. Such rendering bugs critically harm the usability of web browsers as well as web applications. The unique aspect of rendering bugs is that they affect the presented v…
The recently introduced WebAssembly standard aims to be a portable compilation target, enabling the cross-platform distribution of programs written in a variety of languages. We propose an approach to slice WebAssembly programs in order to enable applications in reverse engineeri…
Neural networks have had discernible achievements in a wide range of applications. The wide-spread adoption also raises the concern of their dependability and reliability. Similar to traditional decision-making programs, neural networks can have defects that need to be repaired. …
Code search is a widely used technique by developers during software development. It provides semantically similar implementations from a large code corpus to developers based on their queries. Existing techniques leverage deep learning models to construct embedding representatio…
The performance of neural code search is significantly influenced by the quality of the training data from which the neural models are derived. A large corpus of high-quality query and code pairs is demanded to establish a precise mapping from the natural language to the programm…
Deep learning becomes the driving force behind many contemporary technologies and has been successfully applied in many fields. Through software dependencies, a multi-layer supply chain (SC) with a deep learning framework as the core and substantial down-stream projects as the pe…
Code summarization aims to generate brief natural language descriptions for source codes. The state-of-the-art approaches follow a transformer-based encoder-decoder architecture. As the source code is highly structured and follows strict grammars, its Abstract Syntax Tree (AST) i…
Code review is effective, but human-intensive (e.g., developers need to manually modify source code until it is approved). Recently, prior work proposed a Neural Machine Translation (NMT) approach to automatically transform source code to the version that is reviewed and approved…
A key issue in collaborative software development is communication among developers. One modality of communication is a commit message, in which developers describe the changes they make in a repository. As such, commit messages serve as an "audit trail" by which developers can u…