4,951 papers · page 22 of 248
Failures with different root causes can greatly disrupt multi-fault localization, therefore, categorizing failures into distinct groups according to the culprit fault is highly important. In such a failure indexing task, the crux lies in the failure proximity, which comprises two…
A type of meeting that has been understudied in the software engineering literature to date is what we term the software maintenance meeting: a regularly scheduled team meeting in which emergent issues are addressed that are usually out of scope of the daily stand-up but not nece…
Software Bills of Materials (SBOMs) have emerged as tools to facilitate the management of software dependencies, vulnerabilities, licenses, and the supply chain. While significant effort has been devoted to increasing SBOM awareness and developing SBOM formats and tools, recent s…
Deep learning-based vulnerability detection has shown great performance and, in some studies, outperformed static analysis tools. However, the highest-performing approaches use token-based transformer models, which are not the most efficient to capture code semantics required for…
Bounded formal analysis techniques (such as bounded model checking) are incredibly powerful tools for today's software engineers. However, such techniques often suffer from scalability challenges when applied to large-scale, real-world systems. It can be very difficult to ensure …
Testing is an important aspect of software development, but unfortunately, it is often neglected. While test quality analyses such as code coverage or mutation analysis inform developers about the quality of their tests, such reports are viewed only sporadically during continuous…
Exploratory testing leverages the tester's knowledge and creativity to design test cases for effectively uncovering system-level bugs from the end user's perspective. Researchers have worked on test scenario generation to support exploratory testing based on a system knowledge gr…
Symbolic execution is a popular program analysis technique. It systematically explores all feasible paths of a program but its scalability is largely limited by the path explosion problem, which causes the number of paths proliferates at runtime. A key idea in existing methods to…
Leveraging recent advancements in large language models, modern neural code completion models have demonstrated the capability to generate highly accurate code suggestions. However, their massive size poses challenges in terms of computational costs and environmental impact, hind…
With the widely usage of open-source software, supply-chain-based vulnerability attacks, including SolarWind and Log4Shell, have posed significant risks to software security. Currently, people rely on vulnerability advisory databases or commercial software bill of materials (SBOM…
The rapid progress of autonomous vehicles (AVs) has brought the prospect of a driverless future closer than ever. Recent fatalities, however, have emphasized the importance of safety validation through large-scale testing. Multiple approaches achieve this fully automatically usin…
We conducted a survey of 135 software engineering (SE) practitioners to understand how they use Generative AI-based chatbots like ChatGPT for SE tasks. We find that they want to use ChatGPT for SE tasks like software library selection but often worry about the truthfulness of Cha…
Reinforcement learning from demonstrations (RLfD) is a promising approach to improve the exploration efficiency of reinforcement learning (RL) by learning from expert demonstrations in addition to interactions with the environment. In this paper, we propose a framework that combi…
We introduce Object Graph Programming (OGO), which enables reading and modifying an object graph (i.e., the entire state of the object heap) via declarative queries. OGO models the objects and their relations in the heap as an object graph thereby treating the heap as a graph dat…
Security practitioners routinely use static analysis to detect security problems and privacy violations in Android apps. The soundness of these analyses depends on how the platform is modelled and the list of sensitive methods. Collecting these methods often becomes impractical g…
Feeling part of a group is a basic human need that significantly influences an individual's behavior, long-term engagement, and job satisfaction. A strong sense of belonging holds particular importance within software delivery teams, which grapple with challenges related to well-…
Recent research has begun to examine the potential of automatically finding and fixing accessibility issues that manifest in software. However, while recent work makes important progress, it has generally been skewed toward identifying issues that affect users with certain disabi…
The mining of models from data finds widespread use in industry. There exists a variety of model inference methods for perfectly deterministic behaviour, however, in practice, the provided data often contains noise due to faults such as message loss or environmental factors that …
In the wake of developments in the field of Natural Language Processing, Question Answering (QA) software has penetrated our daily lives. Due to the data-driven programming paradigm, QA software inevitably contains bugs, i.e., misbehaving in real-world applications. Current testi…
Recently, deep learning models have been widely applied in program understanding tasks, and these models achieve state-of-the-art results on many benchmark datasets. A major challenge of deep learning for program understanding is that the effectiveness of these approaches depends…