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Reinforcement learning is well suited for optimizing policies of recommender systems. Current solutions mostly focus on model-free approaches, which require frequent interactions with the real environment, and thus are expensive in model…

Machine Learning · Computer Science 2020-01-22 Xueying Bai , Jian Guan , Hongning Wang

Caveat emptor, or let the buyer beware, is commonly attributed to open source software (OSS)-the onus is on the OSS consumer to ensure that it is fit for use in the consumer's context. OSS has been compared to an open market bazaar where…

Software Engineering · Computer Science 2024-04-26 Nancy Mead , Carol Woody , Scott Hissam

The development of Open-Source Software (OSS) projects relies on the collaborative work of contributors, generally scattered around the world. To enable this collaboration, OSS projects are hosted on social-coding platforms like GitHub,…

Software Engineering · Computer Science 2025-03-10 Sergio Cobos , Javier Luis Cánovas Izquierdo

Improving software performance is an important yet challenging part of the software development cycle. Today, the majority of performance inefficiencies are identified and patched by performance experts. Recent advancements in deep learning…

Software Engineering · Computer Science 2022-06-29 Spandan Garg , Roshanak Zilouchian Moghaddam , Colin B. Clement , Neel Sundaresan , Chen Wu

Low-code platforms (latest reincarnation of the long tradition of model-driven engineering approaches) have the potential of saving us countless hours of repetitive boilerplate coding tasks. However, as software systems grow in complexity,…

Reinforcement learning is about learning agent models that make the best sequential decisions in unknown environments. In an unknown environment, the agent needs to explore the environment while exploiting the collected information, which…

Machine Learning · Computer Science 2021-02-12 Hong Qian , Yang Yu

Recommender systems are a valuable tool for software engineers. For example, they can provide developers with a ranked list of files likely to contain a bug, or multiple auto-complete suggestions for a given method stub. However, the way…

Software Engineering · Computer Science 2022-08-02 Christoph Treude

Automated testing is crucial for maintaining open-source software quality. However, motivating contributors to include tests for code changes remains a challenge. While existing interventions, such as code coverage metrics and reviewer…

Software Engineering · Computer Science 2026-04-28 Teal Amore , Nathan Berman , Siyuan Jiang

In software development, the identification of source code file experts is an important task. Identifying these experts helps to improve software maintenance and evolution activities, such as developing new features, code reviews, and bug…

Software Engineering · Computer Science 2022-08-17 Otávio Cury , Guilherme Avelino , Pedro Santos Neto , Ricardo Britto , Marco Túlio Valente

The growing usage of research software in the research community has highlighted the need to recognize and acknowledge the contributions made not only by researchers but also by Research Software Engineers. However, the existing methods for…

Software Engineering · Computer Science 2024-06-05 Deekshitha , Siamak Farshidi , Jason Maassen , Rena Bakhshi , Rob van Nieuwpoort , Slinger Jansen

Software documentation is an essential but labor intensive task that often requires a dedicated team of developers to ensure coverage and accuracy. Good documentation will help shorten the development cycle and improve the overall team…

Software Engineering · Computer Science 2017-01-31 Thomas Zheng , Jeff Shaw , Sergey Kozlov

Scientific open-source software (Sci-OSS) projects are critical for advancing research, yet sustaining these projects long-term remains a major challenge. This paper explores the sustainability of Sci-OSS hosted on GitHub, focusing on two…

Software Engineering · Computer Science 2025-11-12 Sharif Ahmed , Addi Malviya Thakur , Gregory R. Watson , Nasir U. Eisty

Large scientific collaborations, often with hundreds or thousands of members, are an excellent opportunity for a case study in best practices implemented while developing open source hardware. Using a publicly available design of timing…

Various works have utilized deep learning to address the query optimization problem in database system. They either learn to construct plans from scratch in a bottom-up manner or steer the plan generation behavior of traditional optimizer…

Databases · Computer Science 2024-08-15 Kai Zhong , Luming Sun , Tao Ji , Cuiping Li , Hong Chen

Open-source software (OSS) is widely spread in industry, research, and government. OSS represents an effective development model because it harnesses the decentralized efforts of many developers in a way that scales. As OSS developers work…

Software Engineering · Computer Science 2022-11-24 William Schueller , Johannes Wachs , Vito D. P. Servedio , Stefan Thurner , Vittorio Loreto

With the development of deep learning techniques, supervised learning has achieved performances surpassing those of humans. Researchers have designed numerous corresponding models for different data modalities, achieving excellent results…

Artificial Intelligence · Computer Science 2023-08-29 Qiang Li , Qiuyang Ma , Weizhi Nie , Anan Liu

Requirements Engineering has recently been greatly influenced by the way how firms use Open Source Software (OSS) and Software Ecosystems (SECOs) as a part of their product development and business models. This is further emphasized by the…

Software Engineering · Computer Science 2022-08-05 Johan Linåker , Krzysztof Wnuk

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…

Software Engineering · Computer Science 2024-05-28 Xuetao Li , Yuxia Zhang , Cailean Osborne , Minghui Zhou , Zhi Jin , Hui Liu

In shared autonomy, user input is combined with semi-autonomous control to achieve a common goal. The goal is often unknown ex-ante, so prior work enables agents to infer the goal from user input and assist with the task. Such methods tend…

Machine Learning · Computer Science 2018-05-24 Siddharth Reddy , Anca D. Dragan , Sergey Levine

Recent improvements in deep reinforcement learning have allowed to solve problems in many 2D domains such as Atari games. However, in complex 3D environments, numerous learning episodes are required which may be too time consuming or even…

Machine Learning · Computer Science 2017-12-13 Nicolas Bougie , Ryutaro Ichise
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