Related papers: Beyond the black box
In the field of explainable AI, a vibrant effort is dedicated to the design of self-explainable models, as a more principled alternative to post-hoc methods that attempt to explain the decisions after a model opaquely makes them. However,…
Computational aspects increasingly shape environmental sciences. Actually, transdisciplinary modelling of complex and uncertain environmental systems is challenging computational science (CS) and also the science-policy interface. Large…
This article surveys the use of algorithmic systems to support decision-making in the public sector. Governments adopt, procure, and use algorithmic systems to support their functions within several contexts -- including criminal justice,…
Artificial intelligence (AI) is becoming increasingly more popular and can be found in workplaces and homes around the world. The decisions made by such "black box" systems are often opaque; that is, so complex as to be functionally…
Recent advancements in quantum computing software are gradually increasing the scope and size of quantum programs being developed. At the same time, however, these larger programs provide more possibilities for functional errors that are…
In this paper, we make the key delineation on the roles of resolution and statistical uncertainty in hierarchical bandits-based black-box optimization algorithms, guiding a more general analysis and a more efficient algorithm design. We…
Public development processes are a key characteristic of open source projects. However, fixes for vulnerabilities are usually discussed privately among a small group of trusted maintainers, and integrated without prior public involvement.…
What is the impact of software engineering research on current practices in industry? In this paper, I report on my direct experience as a PhD/post-doc working in software engineering research projects, and then spending the following five…
Open Artificial Intelligence (Open source AI) collaboratives offer alternative pathways for how AI can be developed beyond well-resourced technology companies and who can be a part of the process. To understand how and why they work and…
Open source software projects usually acknowledge contributions with text files, websites, and other idiosyncratic methods. These data sources are hard to mine, which is why contributorship is most frequently measured through changes to…
The growing emphasis on studying equity, diversity, and inclusion within software engineering has amplified the need to explore hidden populations within this field. Exploring hidden populations becomes important to obtain invaluable…
Estimation of software reliability often poses a considerable challenge, particularly for critical softwares. Several methods of estimation of reliability of software are already available in the literature. But, so far almost nobody used…
Existing studies in black-box optimization for machine learning suffer from low generalizability, caused by a typically selective choice of problem instances used for training and testing different optimization algorithms. Among other…
Users around the world rely on software-intensive systems in their day-to-day activities. These systems regularly contain bugs and security vulnerabilities. To facilitate bug fixing, data-driven models of automatic program repair use pairs…
Software bugs significantly contribute to software cost and increase the risk of system malfunctioning. In recent years, many automated program-repair approaches have been proposed to automatically fix undesired program behavior. Despite of…
With the advance in quantum computing in recent years, quantum software becomes vital for exploring the full potential of quantum computing systems. Quantum programming is different from classical programming, for example, the state of a…
DARPA's AI Cyber Challenge (AIxCC) showed that cyber reasoning systems (CRSs) can go beyond vulnerability discovery to autonomously confirm and patch bugs: seven teams built such systems and open-sourced them after the competition. Yet all…
GitHub, a central hub for collaborative software development, has revolutionized the open-source software (OSS) ecosystem through its GitHub Marketplace, a platform launched in 2017 to host automation tools aimed at enhancing the efficiency…
Open Source Software (OSS) project success relies on crowd contributions. When an issue arises in pull-request based systems, @-mentions are used to call on people to task; previous studies have shown that @-mentions in discussions are…
Black-box optimization is often encountered for decision-making in complex systems management, where the knowledge of system is limited. Under these circumstances, it is essential to balance the utilization of new information with…