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Neural networks are an emerging data-driven programming paradigm widely used in many areas. Unlike traditional software systems consisting of decomposable modules, a neural network is usually delivered as a monolithic package, raising challenges for some maintenance tasks such as…
Testing Deep Learning (DL) based systems inherently requires large and representative test sets to evaluate whether DL systems generalise beyond their training datasets. Diverse Test Input Generators (TIGs) have been proposed to produce artificial inputs that expose issues of the…
Logs record the behavioral data of running programs and are typically generated by executing log statements. Software developers generally carry out logging practices with clear intentions and associated concerns (I&Cs). However, I&Cs may not be properly fulfilled in source code …
Software developers spend about a quarter of their workday using the web to fulfill various information needs. Searching for relevant information online can be time-consuming, yet acquired information is rarely systematically persisted for later reference. In this work, we introd…
Software security research has a core problem: it is impossible to prove the security of complex software. A low number of known defects may simply indicate that the software has not been attacked yet, or that successful attacks have not been detected. A high defect count may be …
In this digital era, our privacy is under constant threat as our personal data and traceable online/offline activities are frequently collected, processed and transferred by many software applications. Privacy attacks are often formed by exploiting vulnerabilities found in those …
Specifications for reactive systems synthesis consist of assumptions and guarantees. However, some specifications may include unnecessary assumptions, i.e., assumptions that are not necessary for realizability. While the controllers that are synthesized from such specifications a…
Code search aims to retrieve semantically relevant code snippets for a given natural language query. Recently, many approaches employing contrastive learning have shown promising results on code representation learning and greatly improved the performance of code search. However,…
Database Management Systems (DBMSs) provide efficient data retrieval and manipulation for many applications through Structured Query Language (SQL). Incorrect implementations of DBMSs can result in logic bugs, which cause SELECT queries to fetch incorrect results, or UPDATE and D…
Much research on automated program debugging often assumes that bug fix location(s) indicate the faults' root causes and that root causes of faults lie within single code elements (statements). It is also often assumed that the number of statements a developer would need to inspe…
Deep learning (DL) models of code have recently reported great progress for vulnerability detection. In some cases, DL-based models have outperformed static analysis tools. Although many great models have been proposed, we do not yet have a good understanding of these models. Thi…
Due to convenience, open-source software is widely used. For beneficial reasons, open-source maintainers often fix the vulnerabilities silently, exposing their users unaware of the updates to threats. Previous works all focus on black-box binary detection of the silent dependency…
SMT solvers check the satisfiability of logic formulas over first-order theories, which have been utilized in a rich number of critical applications, such as software verification, test case generation, and program synthesis. Bugs hidden in SMT solvers would severely mislead thos…
Newcomers are critical for the success and continuity of open source software (OSS) projects. To attract newcomers and facilitate their onboarding, many OSS projects recommend tasks for newcomers, such as good first issues (GFIs). Previous studies have preliminarily investigated …
Android apps frequently access personal information to provide customized services. Since such information is sensitive in general, regulators require Android app vendors to publish privacy policies that describe what information is collected and why it is collected. Existing wor…
With the advent of deep learning, AI components have achieved unprecedented performance on complex, human competitive tasks, such as image, video, text and audio processing. Hence, they are increasingly integrated into sophisticated software systems, some of which (e.g., autonomo…
The sense of belonging to a community is a basic human need that impacts an individual's behavior, long-term engagement, and job satisfaction, as revealed by research in disciplines such as psychology, healthcare, and education. Despite much research on how to retain developers i…
Transformers have gained popularity in the software engineering (SE) literature. These deep learning models are usually pre-trained through a self-supervised objective, meant to provide the model with basic knowledge about a language of interest (e.g., Java). A classic pre-traini…
Open-source, community-driven package repositories see thousands of malware packages each year, but do not currently run automated malware detection systems. In this work, we explore the security goals of the repository administrators and the requirements for deploying such malwa…
As pre-trained models automate many code intel-ligence tasks, a widely used paradigm is to fine-tune a model on the task dataset for each programming language. A recent study reported that multilingual fine-tuning benefits a range of tasks and models. However, we find that multil…