4,951 papers · page 16 of 248
Robotics systems are complex, safety-critical systems that can consist of hundreds of software components that interact with each other dynamically during run time. Software components of robotics systems often exhibit reactive, periodic, and state-dependent behavior. Incorrect c…
Industrial deployments of automated program repair (APR), e.g., at Facebook and Bloomberg, signal a new milestone for this exciting and potentially impactful technology. In these deployments, developers use APR-generated patch suggestions as part of a human-driven debugging proce…
Understanding code changes is of crucial importance in a wide range of software evolution activities. The traditional approach is to use textual differencing, as done with success since the 1970s with the ubiquitous diff tool. However, textual differencing has the important limit…
GitHub Sponsors was launched in 2019, enabling donations to open-source software developers to provide financial support, as per GitHub's slogan: "Invest in the projects you depend on". However, a 2022 study on GitHub Sponsors found that only two-fifths of developers who were see…
Who creates the most innovative open-source software projects? And what fate do these projects tend to have? Building on a long history of research to understand innovation in business and other domains, as well as recent advances towards modeling innovation in scientific researc…
Bug reports are vital for software maintenance that allow users to inform developers of the problems encountered while using the software. As such, researchers have committed considerable resources toward automating bug replay to expedite the process of software maintenance. None…
As software systems increasingly interact with humans in application domains such as transportation and healthcare, they raise concerns related to the social, legal, ethical, empathetic, and cultural (SLEEC) norms and values of their stakeholders. Normative non-functional require…
As software engineering advances and the code demand rises, the prevalence of code clones has increased. This phenomenon poses risks like vulnerability propagation, underscoring the growing importance of code clone detection techniques. While numerous code clone detection methods…
Machine learning (ML) is increasingly being used as a key component of most software systems, yet serious concerns have been raised about the fairness of ML predictions. Researchers have been proposing novel methods to support the development of fair machine learning solutions. N…
Programming industrial robots is difficult and expensive. Although recent work has made substantial progress in making it accessible to a wider range of users, it is often limited to simple programs and its usability remains untested in practice. In this article, we introduce Dup…
Effective DBMS fuzzing relies on high-quality initial seeds, which serve as the starting point for mutation. These initial seeds should incorporate various DBMS features to explore the state space thoroughly. While built-in test cases are typically used as initial seeds, many DBM…
Test migration, which enables the reuse of test cases crafted with knowledge and creativity by testers across various platforms and programming languages, has exhibited effectiveness in mobile app testing. However, unit test migration at the source code level has not garnered ade…
Recent years have witnessed the proliferation of learning-based Android malware detectors. These detectors can be categorized into three types, String-based, Image-based and Graph-based. Most of them have achieved good detection performance under the ideal setting. In reality, ho…
Deep learning plays a critical role in numerous intelligent software applications. Enterprise developers submit and run deep learning jobs on shared, multi-tenant platforms to efficiently train and test models. These platforms are typically equipped with a large number of graphic…
Traceability allows stakeholders to extract and comprehend the trace links among software artifacts introduced across the software life cycle, to provide significant support for software engineering tasks. Despite its proven benefits, software traceability is challenging to recov…
Pre-trained code models have recently achieved substantial improvements in many code intelligence tasks. These models are first pre-trained on large-scale unlabeled datasets in a task-agnostic manner using self-supervised learning, and then fine-tuned on labeled datasets in downs…
Multi-sensor fusion stands as a pivotal technique in addressing numerous safety-critical tasks and applications, e.g., self-driving cars and automated robotic arms. With the continuous advancement in data-driven artificial intelligence (AI), MSF's potential for sensing and unders…
Machine Learning (ML) is increasingly gaining significance for enduser programmer (EUP) applications. However, machine learning end-user programmers (ML-EUPs) without the right background face a daunting learning curve and a heightened risk of mistakes and flaws in their models. …
Code comment generation aims at generating natural language descriptions for a code snippet to facilitate developers' program comprehension activities. Despite being studied for a long time, a bottleneck for existing approaches is that given a code snippet, they can only generate…
Property-based testing (PBT) is a testing methodology where users write executable formal specifications of software components and an automated harness checks these specifications against many automatically generated inputs. From its roots in the QuickCheck library in Haskell, P…