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, Software Engineering
Mitchell Joblin, Barbara Eckl, Thomas Bock, Angelika Schmid, Janet Siegmund, Sven Apel
Summary: Despite the absence of a formal process and a central command-and-control structure, developer organization in open-source software (OSS) projects are not random. Highly successful OSS projects develop a hybrid organizational structure, with hierarchical and non-hierarchical parts. Developers' positions transition from the non-hierarchical part to the hierarchical part as they gain experience and engage in coordination and coding activities.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2023)
Article
Computer Science, Software Engineering
Binny M. Samuel, Hillol Bala, Sherae Daniel, V Ramesh
Summary: This study explores collaboration norms in organizations OSS (orgsOSS) and uncovers that developers in orgsOSS do not always adhere to traditional ideals of widespread sharing and participation. However, certain developer and task characteristics can influence the promotion of these ideals, providing important insights for future orgsOSS projects and other similarly structured software development projects.
IEEE TRANSACTIONS ON 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, Information Systems
Di Cui, Lingling Fan, Sen Chen, Yuanfang Cai, Qinghua Zheng, Yang Liu, Ting Liu
Summary: This paper presents the first attempt to understand bug fixes from the perspective of dependencies. A systematic study on bug fixes collected from 157 Apache open source projects is conducted, revealing a relatively high proportion of bug fixes introducing dependency-level changes. These fixes are strongly correlated with high priority, large fixing churn, long fixing time, frequent bug reopening, and bug inducing. In addition, patched files with dependency-level changes consume much more maintenance costs compared to those without these changes.
SCIENCE CHINA-INFORMATION SCIENCES
(2022)
Article
Computer Science, Software Engineering
Thomas Bock, Claus Hunsen, Mitchell Joblin, Sven Apel
Summary: Mailing lists are essential for coordinating developers in open-source projects. This study proposes two methods for studying synchronization between collaboration and communication activities from a higher-level perspective, and finds that a higher-level view on developer coordination leads to stronger statistical dependence between technical activities.
AUTOMATED SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Siqi Sun, Cheng Huang, Tiejun Wu, Yi Shen
Summary: With the increasing complexity of cyberattacks, multistage combination attacks have become the primary method of attack. This research proposes an automated knowledge graph construction architecture for open-source security tools, which fills a gap in the field of automated security tools' knowledge extraction.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2023)
Article
Operations Research & Management Science
Shakshi Singhal, P. K. Kapur, Vivek Kumar, Saurabh Panwar
Summary: This study proposes reliability growth models for Open Source Software (OSS) by incorporating dynamism in the debugging process. Stochastic differential equation-based analytical models are used to represent the instantaneous rate of error generation, and exponential and Erlang distribution functions are employed to model the fault introduction rate. Real-life failure data from OSS projects, GNU Network Object Model Environment, and Eclipse are utilized to validate the proposed methodology. Genetic Algorithm is applied for parameter estimation, and cross-validation is performed to examine the forecasting efficacy of the model. The results demonstrate the effectiveness of the proposed models in parameter estimation, predictive performance, and decision-making under uncertainty.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Software Engineering
Rajdeep Kaur, Kuljit Kaur Chahal
Summary: This paper examines the impact of developer and project-related factors on developer abandonment in OSS projects. The findings show that developer experience, role, and joining date have an influence on whether developers abandon the projects, while coding language does not have a definite impact.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2022)
Article
Chemistry, Multidisciplinary
Abdulkadir Seker, Banu Diri, Halil Arslan
Summary: Software collaboration platforms have become popular, allowing developers from diverse locations to contribute to open source projects. This study proposed new developer metrics extracted from activities on GitHub, with binary_issue_related, issue_commented, binary_pr_related, and issue_opened being the most successful. Comparing metrics with other studies, the results indicated that issue-related metrics are crucial for GitHub, and commenting activities can be as valuable as code contributions. The generated binary metrics showed remarkable results and can be used for various software development challenges.
APPLIED SCIENCES-BASEL
(2021)
Article
Biology
Vishhvaan Gopalakrishnan, Dena Crozier, Kyle J. Card, Lacy D. Chick, Nikhil P. Krishnan, Erin McClure, Julia Pelesko, Drew F. K. Williamson, Daniel Nichol, Soumyajit Mandal, Robert A. Bonomo, Jacob G. Scott
Summary: A morbidostat is a bioreactor that uses antibiotics to control bacterial growth, making it suitable for studying antibiotic resistance evolution. We present a low-cost morbidostat called the EVolutionary biorEactor (EVE) that can be constructed by students with minimal engineering and programming experience. We validate EVE in a real classroom setting by evolving replicate Escherichia coli populations under chloramphenicol challenge, providing students the opportunity to learn about bacterial growth and antibiotic resistance.
Article
Astronomy & Astrophysics
Adrian M. Price-Whelan, Pey Lian Lim, Nicholas Earl, Nathaniel Starkman, Larry Bradley, David L. Shupe, Aarya A. Patil, Lia Corrales, C. E. Brasseur, Maximilian Noethe, Axel Donath, Erik Tollerud, Brett M. Morris, Adam Ginsburg, Eero Vaher, Benjamin A. Weaver, James Tocknell, William Jamieson, Marten H. van Kerkwijk, Thomas P. Robitaille, Bruce Merry, Matteo Bachetti, H. Moritz Gunther, Thomas L. Aldcroft, Jaime A. Alvarado-Montes, Anne M. Archibald, Attila Bodi, Shreyas Bapat, Geert Barentsen, Juanjo Bazan, Manish Biswas, Mederic Boquien, D. J. Burke, Daria Cara, Mihai Cara, Kyle E. Conroy, Simon Conseil, Matthew W. Craig, Robert M. Cross, Kelle L. Cruz, Francesco D'Eugenio, Nadia Dencheva, Hadrien A. R. Devillepoix, Jorg P. Dietrich, Arthur Davis Eigenbrot, Thomas Erben, Leonardo Ferreira, Daniel Foreman-Mackey, Ryan Fox, Nabil Freij, Suyog Garg, Robel Geda, Lauren Glattly, Yash Gondhalekar, Karl D. Gordon, David Grant, Perry Greenfield, Austen M. Groener, Steve Guest, Sebastian Gurovich, Rasmus Handberg, Akeem Hart, Zac Hatfield-Dodds, Derek Homeier, Griffin Hosseinzadeh, Tim Jenness, Craig K. Jones, Prajwel Joseph, J. Bryce Kalmbach, Emir Karamehmetoglu, Mikolaj Kaluszynski, Michael S. P. Kelley, Nicholas Kern, Wolfgang E. Kerzendorf, Eric W. Koch, Shankar Kulumani, Antony Lee, Chun Ly, Zhiyuan Ma, Conor MacBride, Jakob M. Maljaars, Demitri Muna, N. A. Murphy, Henrik Norman, Richard O'Steen, Kyle A. Oman, Camilla Pacifici, Sergio Pascual, J. Pascual-Granado, Rohit R. Patil, Gabriel Perren, Timothy E. Pickering, Tanuj Rastogi, Benjamin R. Roulston, Daniel F. Ryan, Eli S. Rykoff, Jose Sabater, Parikshit Sakurikar, Jesus Salgado, Aniket Sanghi, Nicholas Saunders, Volodymyr Savchenko, Ludwig Schwardt, Michael Seifert-Eckert, Albert Y. Shih, Anany Shrey Jain, Gyanendra Shukla, Jonathan Sick, Chris Simpson, Sudheesh Singanamalla, Leo P. Singer, Jaladh Singhal, Manodeep Sinha, Brigitta M. Sipocz, Lee R. Spitler, David Stansby, Ole Streicher, Jani Sumak, John D. Swinbank, Dan S. Taranu, Nikita Tewary, Grant R. Tremblay, Miguel De Val-Borro, Zlatan Vasovic, Samuel J. Van Kooten, Shresth Verma, Jose Vinicius de Miranda Cardoso, Peter K. G. Williams, Tom J. Wilson, Benjamin Winkel, W. M. Wood-Vasey, Rui Xue, Peter Yoachim, Chen Zhang, Andrea Zonca
Summary: The Astropy Project is an open-source Python package that provides commonly needed functionality to the astronomical community. Its core package, astropy, serves as the foundation for specialized projects and packages. This article summarizes the key features of the core package and provides updates on the project. It also discusses the connections with astronomical observatories and missions, and the future outlook and challenges of the Astropy Project.
ASTROPHYSICAL JOURNAL
(2022)
Review
Engineering, Multidisciplinary
Zhifang Liao, Bolin Zhang, Xuechun Huang, Song Yu, Yan Zhang
Summary: This paper proposes a PR review prediction model based on multi-dimensional features and a PR revision recommendation model based on the PR review knowledge graph, in order to solve the code review problems and improve the quality in the open-source community. By extracting and classifying the 43 features of PR, a prediction model based on Random Forest Classifier is built to predict the review results. Meanwhile, using graph-based similarity calculation, PR revisions are recommended based on historical review comments and related issues. The experimental results demonstrate the effectiveness and robustness of these two models in PR review and revision.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Computer Science, Software Engineering
Yuxing Ma, Tapajit Dey, Chris Bogart, Sadika Amreen, Marat Valiev, Adam Tutko, David Kennard, Russell Zaretzki, Audris Mockus
Summary: Open source software is essential for modern society, but limited understanding exists about the periphery of the entire OSS ecosystem. By collecting a large amount of version control data and providing capabilities to analyze it, we can better understand the connections and evolution of open source software projects.
EMPIRICAL SOFTWARE ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Joao A. Duro, Yiming Yan, Ioannis Giagkiozis, Stefanos Giagkiozis, Shaul Salomon, Daniel C. Oara, Ambuj K. Sriwastava, Jacqui Morison, Claire M. Freeman, Robert J. Lygoe, Robin C. Purshouse, Peter J. Fleming
Summary: The article introduces a tool named Liger designed for non-specialists in industry to perform optimization. Users can interact with Liger through a visual programming language to create optimization workflows and solve multi-objective optimization problems. Liger includes a novel optimization library called Tigon, offering various multi-objective evolutionary algorithms and support for implementing optimization models of different problem types.
APPLIED SOFT COMPUTING
(2021)
