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AI development is embracing open-source paradigm, but the fundamental distinction between AI models and traditional software artifacts may lead to a divergent open-source development paradigm with different collaborative practices, which…

Open source software (OSS) has been playing a fundamental role in not only information technology but also our social lives. Attracted by various advantages of OSS, increasing commercial companies take extensive participation in open source…

A risk in adopting third-party dependencies into an application is their potential to serve as a doorway for malicious code to be injected (most often unknowingly). While many initiatives from both industry and research communities focus on…

Forking-based development has made it easier and straightforward for developers to contribute to open-source software (OSS). Developers can fork an existing project and add changes in their local version without interrupting the development…

Governments are increasingly employing funding for open source software (OSS) development as a policy lever to support the security of software supply chains, digital sovereignty, economic growth, and national competitiveness in science and…

Commit is an important operation of revision control for open-source software (OSS). Recent research has been pursued to explore the statistical laws of such an operation, but few of those papers conduct empirical investigations on commit…

Open source software (OSS) vulnerabilities threaten the security of software systems that use OSS. Vulnerability databases provide valuable information (e.g., vulnerable version and patch) to mitigate OSS vulnerabilities. There arises a…

Over the last years, the software industry has adopted several DevOps technologies related to practices such as continuous integration and continuous delivery. The high demand for DevOps practitioners requires non-trivial adjustments in…

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no…

With the rapid increasing number of open source software (OSS), the majority of the software vulnerabilities in the open source components are fixed silently, which leads to the deployed software that integrated them being unable to get a…

Both recommender systems and bots should proactively and smartly answer the questions of software developers or other project stakeholders to assist them in performing their tasks more efficiently. This paper reflects on the achievements…

Research computing centers around the world struggle with onboarding new users. Subject matter experts, researchers, and principal investigators are often overwhelmed by the complex infrastructure and software offerings designed to support…

Generative recommendation models can model user behavior as sequences of events and provide a shared backbone for multiple recommendation tasks. In production, however, pre-training gains do not automatically translate into downstream…

For Open Source Software (OSS) projects, discussions in Issue Tracking Systems (ITS) serve as a crucial collaboration mechanism for diverse stakeholders. However, these discussions can become lengthy and entangled, making it hard to find…

In recent years, sequential recommender systems (SRSs) and session-based recommender systems (SBRSs) have emerged as a new paradigm of RSs to capture users' short-term but dynamic preferences for enabling more timely and accurate…

Developers rely on open-source packages and must review dependencies to safeguard against vulnerable or malicious upstream code. A careful review of all dependencies changes often does not occur in practice. Therefore, developers need…

Open source software (OSS) development relies on diverse skill sets. However, to our knowledge, there are no tools which detect OSS-related skills. In this paper, we present a novel method to detect OSS skills and prototype it in a tool…

The sequential recommendation problem has attracted considerable research attention in the past few years, leading to the rise of numerous recommendation models. In this work, we explore how Large Language Models (LLMs), which are nowadays…

Modern recommender systems operate in uniquely dynamic settings: user interests, item pools, and popularity trends shift continuously, and models must adapt in real time without forgetting past preferences. While existing tutorials on…

Generalized reciprocity -- the tendency to help others after receiving help oneself -- is widely theorized as a mechanism sustaining cooperation on online knowledge-sharing platforms. Yet robust empirical evidence from field settings…