Related papers: Explainable Software Bot Contributions: Case Study…
Recently, face recognition systems have demonstrated remarkable performances and thus gained a vital role in our daily life. They already surpass human face verification accountability in many scenarios. However, they lack explanations for…
As software development increasingly adopts automation, bot-driven development (BotDD) represents a transformative shift where bots assume proactive roles in coding, testing, and project management. In bot-driven development, bots go beyond…
Smartphones and tablets have established themselves as mainstays in the modern computing landscape. It is conceivable that in the near future such devices may supplant laptops and desktops, becoming many users primary means of carrying out…
Modern web dashboards and enterprise applications increasingly rely on complex, distributed microservices architectures. While these architectures offer scalability, they introduce significant challenges in debugging and observability. When…
Various automated program repair (APR) techniques have been proposed to fix bugs automatically in the last decade. Although recent researches have made significant progress on the effectiveness and efficiency, it is still unclear how APR…
The rise of large language models for code has reshaped software development. Autonomous coding agents, able to create branches, open pull requests, and perform code reviews, now actively contribute to real-world projects. Their growing…
We are witnessing a massive adoption of software engineering bots, applications that react to events triggered by tools and messages posted by users and run automated tasks in response, in a variety of domains. This thematic issues…
Software bugs pose an ever-present concern for developers, and patching such bugs requires a considerable amount of costs through complex operations. In contrast, introducing bugs can be an effortless job, in that even a simple mutation can…
In this paper we are trying to determine a scheme for the fair allocation of points to the contributors of the collaborative community. The major problem of fair allocation of points among the contributors is that we have to analyze the…
Knowledge-based systems reason over some knowledge base. Hence, an important issue for such systems is how to acquire the knowledge needed for their inference. This paper assesses active learning methods for acquiring knowledge for "static…
The growing complexity of software systems and the influence of software-supported decisions in our society awoke the need for software that is transparent, accountable, and trustworthy. Explainability has been identified as a means to…
Previous work established that open source software (OSS) projects can benefit from the involvement of UX professionals, who offer user-centric perspectives and contributions to improve software usability. However, their participation in…
[This paper has been withdrawn by the author due to updated research available on arXiv (arXiv:1811.01918)] As the modern open-source paradigm makes it easier to contribute to software projects, the number of developers involved in these…
As AI becomes an integral part of our lives, the development of explainable AI, embodied in the decision-making process of an AI or robotic agent, becomes imperative. For a robotic teammate, the ability to generate explanations to justify…
Software development is a complex activity which depends on diverse technologies and people's expertise. The approaches to developing software highly depend on these different characteristics, which are the context developers are subject…
An edit summary is a succinct comment written by a Wikipedia editor explaining the nature of, and reasons for, an edit to a Wikipedia page. Edit summaries are crucial for maintaining the encyclopedia: they are the first thing seen by…
Question-and-answer platforms such as Stack Overflow are an important way for software developers to share and retrieve knowledge. However, reusing poorly understood code can lead to serious problems, such as bugs or security…
Explainable artificial intelligence is a research field that tries to provide more transparency for autonomous intelligent systems. Explainability has been used, particularly in reinforcement learning and robotic scenarios, to better…
Explainability, i.e. the ability of a system to explain its behavior to users, has become an important quality of software-intensive systems. Recent work has focused on methods for generating explanations for various algorithmic paradigms…
Certain aspects of the explainability of AI systems will be critically discussed. This especially with focus on the feasibility of the task of making every AI system explainable. Emphasis will be given to difficulties related to the…