Article
Business
Johannes Wachs, Mariusz Nitecki, William Schueller, Axel Polleres
Summary: Open Source Software plays a crucial role in the digital economy, but the geographic distribution of developers has been uneven. However, recent data shows an increasing number of developers in Asia, Latin America, and Eastern Europe, indicating a more balanced global spread of OSS developers. Localized policies are needed to support networks of OSS developers.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Management
Nataliya Langburd Wright, Frank Nagle, Shane Greenstein
Summary: This study is the first to explore the relationship between open source software (OSS) and entrepreneurship on a global scale. Using cross-country data, the study shows that participation on the GitHub OSS platform has a positive impact on the founding of new technology ventures in a country. The study also finds that OSS contributions lead to ventures that are more mission- and global-oriented and of higher quality.
Article
Engineering, Multidisciplinary
Qing Zhao, Xiangjuan Yao, Xiangying Dang, Dunwei Gong
Summary: This paper proposes a method based on a probability propagation model to effectively and quickly identify the most influential users in the open source software community. The method takes into account the interaction behavior among users by quantifying user feedback on projects and establishing a new probability propagation model between users.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Software Engineering
Pavneet Singh Kochhar, Eirini Kalliamvakou, Nachiappan Nagappan, Thomas Zimmermann, Christian Bird
Summary: The study indicates that factors such as building a vibrant community, providing prompt answers, developing an open source culture, complying with security regulations, and exploring business opportunities are the driving forces for companies to open source their products. In the transition of six Microsoft open-source systems, the process involves aspects such as code reviews, version control systems, continuous integration, and developers' perceptions of these changes. Regarding the open source community's perspective, positive responses were observed in contributions and interactions with internal developers.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2021)
Article
Computer Science, Software Engineering
Sonja Wogrin, Diego Alejandro Tejada-Arango, Robert Gaugl, Thomas Klatzer, Udo Bachhiesl
Summary: This paper introduces the open-source Low-carbon Expansion Generation Optimization (LEGO) model, which is a versatile tool for techno-economic analyses in the energy sector. It offers flexibility in analyzing different time periods.
Article
Computer Science, Information Systems
Georg Buchgeher, Stefan Schoeberl, Verena Geist, Bernhard Dorninger, Philipp Haindl, Rainer Weinreich
Summary: Architecture decision records (ADRs) have been proposed as a resource-efficient means for capturing architectural design decisions (ADDs), and have received attention not only from researchers but also from practitioners. However, our study on open source repositories at GitHub shows that the adoption of ADRs is still low, with only about 50% of repositories containing one to five ADRs. In repositories that use ADRs more systematically, decisions are recorded as a team activity conducted by multiple users over a longer period of time, with most repositories using the template proposed by Michael Nygard.
Article
Computer Science, Software Engineering
Debasish Chakroborti, Sristy Sumana Nath, Kevin A. Schneider, Chanchal K. Roy
Summary: This study investigates software development patterns in open-source projects and finds that simplifying phase management enables frequent software releases, following the small release conventions of Extreme Programming. Additionally, a combination of development and management activities can predict the number of software releases in a month.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2023)
Article
Engineering, Industrial
Knut Blind, Torben Schubert
Summary: Open Source Software (OSS) has both positive and negative economic impacts on countries' GDP due to its dual nature. While providing a commonly accessible productive resource for all countries, OSS also leads to outward-directed spillovers associated with own contributions, resulting in mixed effects on GDP. Smaller countries experience a decline in GDP due to knowledge spillovers, but the net effect is still positive.
JOURNAL OF TECHNOLOGY TRANSFER
(2023)
Article
Computer Science, Software Engineering
Jiayuan Zhou, Shaowei Wang, Yasutaka Kamei, Ahmed E. Hassan, Naoyasu Ubayashi
Summary: Operating an open source project requires both intrinsic and extrinsic motivation. However, the characteristics of donors and the usage of donations are not well-understood. This study investigates the donations received through the Open Collective platform to gain insights into their characteristics and usage in open source projects.
EMPIRICAL SOFTWARE ENGINEERING
(2022)
Article
Chemistry, Multidisciplinary
Mamdouh Alenezi
Summary: The evolution of software systems and understanding their internal quality is crucial in software engineering. This study analyzed the evolution of object-oriented open-source software systems in terms of size, internal quality metrics, showing significant differences among systems in LOC, significant correlations between internal quality metrics, and positive effects of complexity and inheritance on LOC. Coupling and Cohesion did not show significant effects on LOC.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Software Engineering
C. Marimuthu, Sridhar Chimalakonda, K. Chandrasekaran
Summary: Developers often face issues such as delayed app notifications, inconsistent background location updates, and suspended background tasks, with library developers showing quicker responses to API changes compared to application developers.
SOFTWARE-PRACTICE & EXPERIENCE
(2021)
Article
Computer Science, Software Engineering
Damian A. Tamburri, Fabio Palomba, Rick Kazman
Summary: Software engineering success relies on balancing distance, culture, global engineering practices and more. This paper introduces an automated approach, CodeFace4Smells, to identify four community smell types. A large-scale empirical study on 60 open-source communities reveals that community smells are highly diffused in open-source and perceived by developers as significant issues for software community evolution.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2021)
Article
Computer Science, Software Engineering
Georgia M. Kapitsaki, Georgia Charalambous
Summary: This paper introduces findOSSLicense, a license recommender that helps users choose the appropriate open source license for their software under creation. The recommendation process is based on a hybrid recommender that considers user needs and system flexibility, and involves analysis of existing open source licenses.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2021)
Article
Computer Science, Information Systems
Marc Oriol, Carlos Mueller, Jordi Marco, Pablo Fernandez, Xavier Franch, Antonio Ruiz-Cortes
Summary: Recent surveys show that the use of Open Source Software (OSS) is increasingly important for organizations. However, choosing the right OSS or contributing to its development is a complex task. There is a lack of useful OSSECO analysis tools for potential adopters or contributors.
INTERNET OF THINGS
(2023)
Article
Computer Science, Artificial Intelligence
Linda Erlenhov, Francisco Gomes de Oliveira Neto, Philipp Leitner
Summary: This paper presents an empirical study on bot activity, using both quantitative and qualitative analysis. The study highlights the differences in definitions of bot activity in open-source software and identifies tools that comply with the characteristics of Devbots. The analysis also reveals that most projects experiment with multiple bots before making a decision on adoption or switching. Factors such as generated noise and required adaptation in development practices are found to drive discussions about the adoption or removal of Devbots.
PEERJ COMPUTER SCIENCE
(2022)
Article
Computer Science, Software Engineering
Shuzheng Gao, Cuiyun Gao, Yulan He, Jichuan Zeng, Lunyiu Nie, Xin Xia, Michael Lyu
Summary: Code summaries help developers understand programs and save time during software maintenance. Recent studies have used deep learning techniques, such as Transformer-based approaches, to generate accurate code summaries. However, integrating code structure information into Transformers effectively has been under-explored in this task domain.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2023)
Article
Computer Science, Software Engineering
Chen Zeng, Yue Yu, Shanshan Li, Xin Xia, Zhiming Wang, Mingyang Geng, Linxiao Bai, Wei Dong, Xiangke Liao
Summary: With the rapid increase of public code repositories, developers have a strong interest in retrieving precise code snippets using natural language. Existing deep learning-based approaches for code search in large-scale repositories still have low accuracy due to limitations in code representation and modeling. In this paper, we propose deGraphCS, a learnable deep graph model that uses an intermediate representation technique to convert source code into variable-based flow graphs, enabling more precise modeling of code semantics. Experimental results show that deGraphCS achieves state-of-the-art performance in accurately retrieving code snippets from a large-scale dataset.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2023)
Article
Computer Science, Software Engineering
Filipe Roseiro Cogo, Xin Xia, Ahmed E. Hassan
Summary: Programming language documentation is crucial for supporting application developers in effectively using a programming language. This article presents an automated approach for evaluating the alignment between developers' information needs and the current state of documentation. The approach leverages semi-supervised topic modelling and reveals both similarities and differences between Q&A posts and official documentation. The results show a relatively high level of topical alignment in Rust documentation, while also identifying areas where specific topics, such as network, game, and database development, are lacking in information.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2023)
Article
Computer Science, Software Engineering
Ting Zhang, Donggyun Han, Venkatesh Vinayakarao, Ivana Clairine Irsan, Bowen Xu, Ferdian Thung, David Lo, Lingxiao Jiang
Summary: Many duplicate bug report detection techniques have been proposed, but insufficient comparison has been made among them. This study fills this gap by comparing these techniques, and a new benchmark is prepared to evaluate their performance. Surprisingly, a simpler technique outperforms sophisticated ones, and a simple technique already adopted in practice achieves comparable results as a research tool. The study provides insights on the current state of duplicate bug report detection and benefits future research in this area.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2023)
Article
Computer Science, Software Engineering
Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies
Summary: Automatically generated static code warnings commonly have many false alarms. To improve the accuracy of determining which warnings are actionable, analysts should delve deeper into their algorithms and make better choices. This study demonstrates that by locally adjusting the decision boundary, effective predictors for actionable static code warnings can be created, reaching a new benchmark of 92% median AUC across eight open-source Java projects.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Yibo Zhang, Jingjing Wang, Lanjie Zhang, Yufang Zhang, Qi Li, Kwang-Cheng Chen
Summary: In this paper, the reliable transmission scheme of downlink Non-Orthogonal Multiple Access (NOMA) systems is investigated. The base station's coverage area is divided into multiple annular regions, with receivers randomly distributed within them, to achieve NOMA pairing. Bit Error Rate (BER) expressions with Quadrature Phase-Shift Keying (QPSK) modulation are derived. The BER performance of the receiver with the worst channel gain in each region is studied to ensure reliable communications. An optimal power allocation algorithm is proposed to minimize the transmission power while meeting a given BER constraint. Extensive simulations validate the accuracy of the obtained BER expressions and the effectiveness of the proposed algorithm. These findings offer valuable insights for achieving reliable transmission in NOMA systems with randomly deployed receivers.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Chenxi Li, Wenji He, Haipeng Yao, Tianle Mai, Jingjing Wang, Song Guo
Summary: The increasing applications of LEO satellite networks in various domains have highlighted the need for efficient routing algorithms to accommodate the dynamic changes in network topology. In this paper, we propose a knowledge graph-based representation of satellite network topologies and routing architecture to optimize path selection and calculation cost. Our approach incorporates predicting potential relations between data packets and nodes to select the best relay nodes, resulting in improved packet loss ratio and average delay. Extensive simulations are performed to evaluate the performance and availability of the proposed algorithm.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Wei Wei, Jingjing Wang, Zhengru Fang, Jianrui Chen, Yong Ren, Yuhan Dong
Summary: In this paper, a joint design of the UAV-USV-UUV network, also referred to as 3U network, is proposed for cooperative underwater target hunting. An energy-oriented target hunting model is proposed by jointly optimizing the UAV's position, the UUV's trajectory as well as their inter-connectivity. Simulation results show the proposed scheme is suitable for underwater target hunting with a high success rate considering a trade-off between the system energy consumption and inter-connectivity.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Software Engineering
Weifeng Sun, Meng Yan, Zhongxin Liu, Xin Xia, Yan Lei, David Lo
Summary: Many previous studies have focused on the co-evolution of production and test code based on samples mined from software repositories. However, the quality of the mined samples is crucial for reliable research conclusions. We conducted an empirical study and found that the existing assumption used in identifying production-test co-evolution samples is often noisy. Based on our findings, we proposed a method called CHOSEN which outperforms existing identification methods and helps draw more accurate conclusions regarding the co-evolution of production and test code.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2023)
Article
Computer Science, Software Engineering
Lwin Khin Shar, Biniam Fisseha Demissie, Mariano Ceccato, Yan Naing Tun, David Lo, Lingxiao Jiang, Christoph Bienert
Summary: Android malware detection is an active research field, with machine learning-based approaches proposed using different features such as API usage and sequences. The study found that permission use features performed the best, package-level features were generally better than class-level features, and static features generally outperformed dynamic features.
EMPIRICAL SOFTWARE ENGINEERING
(2023)
Article
Computer Science, Software Engineering
Zhuo Zhang, Yan Lei, Xiaoguang Mao, Meng Yan, Xin Xia, David Lo
Summary: Numerous fault localization techniques identify suspicious statements that may cause program failures by analyzing the statistical correlation between test results and program executions. However, they often overlook the importance of failure context in fault analysis and localization. To address this, we propose a context-aware neural fault localization approach (CAN) that incorporates failure context into fault localization by constructing a program dependency graph and using graph neural networks. Experimental results on large-sized programs demonstrate that CAN achieves promising results and outperforms existing baselines by a substantial margin.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Houze Feng, Jingjing Wang, Zhengru Fang, Junhui Qian, Kwang-Cheng Chen
Summary: This paper examines the factors influencing the peak age of information in the transaction-confirmation process of blockchain technology in UAV-aided wireless sensor networks. The closed-form expressions for the average peak age of information are provided. The results indicate that reducing the block size and queue length can decrease the peak age of information, and fixed interval network traffic and network traffic with Markovian properties exhibit better aging behavior than other situations.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Xiangwang Hou, Jingjing Wang, Chunxiao Jiang, Xudong Zhang, Yong Ren, Merouane Debbah
Summary: Integrating unmanned aerial vehicles (UAVs) with federated learning (FL) is a promising approach for handling massive data generated by intelligent devices. This paper proposes a UAV-enabled covert federated learning architecture that emits artificial noise to enhance data security. The effectiveness of the proposed scheme is validated through experiments.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Qing Huang, Zhiqiang Yuan, Zhenchang Xing, Zhengkang Zuo, Changjing Wang, Xin Xia
Summary: This article introduces the need for both API reference (know-what) knowledge and programming task (know-how) knowledge in software programming and proposes a fusion of API-KG and Task-KG to construct an API-Task knowledge graph. The study confirms the necessity of combining both types of knowledge to answer API usage problems. The fused and semantically-enriched API-Task KG supports coherent API/Task-centric knowledge search.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
