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40th Euromicro Conference on software Engineering and Advanced Applications (SEAA)

作者： Aman, Hirohisa Yamashita, Akiko Sasaki, Takashi Kawahara, Minoru Ehime Univ Ctr Informat Technol Matsuyama Ehime 7908577 Japan Ehime Univ Dept Comp Sci Matsuyama Ehime 7908577 Japan

ISBN: (纸本)9781479957958

In recent years, many open source software (OSS) products have become popular and widely used in the information technology (IT) business. To successfully run IT business, it is important to properly understand the OSS development status. Having a proper understanding of development status is necessary to evaluate and predict the product quality. However, the OSS development status is not easy to understand, because it is often concurrently developed by many distributed contributors, and its developmental structure is complicated. To aid the understanding of the development status, there is an approach that models the trend of source code change events (evolution) with a growth curve. Although an application of growth curves seems to be a promising approach, there has been a big issue that a single growth curve is often unsuitable for modeling the whole evolution because of its complex evolutionary behavior. This paper proposes a multistage model that divides the whole development period into some stages, and applies a different growth curve to a different stage. The empirical investigation in this paper shows that the switching points of stages have meaningful associations with the release dates.

关键词： public domain software software quality source code (software) IT business OSS development status code change events complex evolutionary behavior development period developmental structure distributed contributors growth curve information technology business multistage growth model open source software development open source software products product quality source code change events Computational modeling Data models Logistics Market research Mathematical model software Switches open source software Growth curves development time market research data models computer software software quality Computational modeling Logistics Switches Mathematical Model information technology Office of the Supervising Scientist

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Exploring development-related Factors Affecting the Popularity of open source software Projects 24

Exploring Development-related Factors Affecting the Populari...

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24th IEEE International Conference on Computer Supported Cooperative Work in Design (IEEE CSCWD)

作者： Jiang, Sha Cao, Jian Qi, Qing Shanghai Jiao Tong Univ Shanghai Peoples R China

ISBN: (纸本)9781728165974

open source software development (OSSD) projects is a collaborative process among developers and volunteers with common interests. OSSD is increasingly becoming a trend and many successful OSSD projects have contributed software packages which have been widely adopted. Unfortunately, there is Pareto principle in OSSD projects, and a large number of OSSD projects have little influence, many projects a re unable to attract user interest. Therefore, it is important to understand the factors affecting OSSD project success as measured by project popularity. While technical factors such as license and compatibility with certain operating systems have a direct influence on the popularity of OSSD projects, development-related factors also have latent impacts on the popularity of OSSD projects. Therefore, we collect data on 445 projects and successfully build a structural equation model (SEM) which depicts the inherent relationships between development-related factors and OSSD project popularity. The steps to build the SEM and the implications of this model are discussed in detail in this paper.

关键词： open source software development structural equation model popularity

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Impact of social features implemented in open collaboration platforms on volunteer self-organization: case study of open source software development 13

Impact of social features implemented in open collaboration ...

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Proceedings of the 9th International Symposium on open Collaboration

作者： Junghong Choi Bruce Ferwerda Jungpil Hahn Jinwoo Kim Jae Yun Moon Yonsei University Seoul South Korea National University of Singapore Singapore Korea University Business School Seongbuk-Gu Seoul South Korea

ISBN: (纸本)9781450318525

The promise of collective intelligence emerging from voluntary participation, contribution and knowledge sharing brought about by ubiquitous information and communication technologies has recently attracted the attention of academics and practitioners alike. Of many related phenomena, open source software (OSS) development has been touted as one of the leading examples that speak to the potential of collective intelligence. Recently, the advent of novel open collaboration platforms for open source software development, such as Github, has prompted researchers to examine the impact of increased work transparency induced by the introduction of social features on voluntary self-organization and allocation of resources to projects. We present both qualitative and quantitative analyses from which we derive some initial propositions regarding the impact of transparency on voluntary self-organization processes and decision mechanisms.

关键词： transparency github social computing information overload open source software development social coding

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Demo: ALERT - real-time coordination in open source software development 13

Demo: ALERT - real-time coordination in open source software...

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Proceedings of the 7th ACM international conference on Distributed event-based systems

作者： Dominik Riemer Ljiljana Stojanovic Nenad Stojanovic FZI Karlsruhe Germany

ISBN: (纸本)9781450317580

In this demo, we present the final version of the ALERT system. ALERT aims to improve the collaboration and coordination of developers in open source software development. In this sense, ALERT provides active support for developers in form of real-time notifications. The system is based on an event-driven architecture which integrates data from several information sources used by developers, e.g., forums, source code management systems and issue trackers. This data is acquired by push sensors, preprocessed by several middle-tier components and send to a complex event detector in order to provide real-time decision support for multiple daily development tasks.

关键词： semantic technologies open source software development complex event processing

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Unearthing open source decision-making processes: A case study of python enhancement proposals

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software-PRACTICE & EXPERIENCE 2022年第10期52卷 2312-2346页

作者： Sharma, Pankajeshwara Nand Savarimuthu, Bastin Tony Roy Stanger, Nigel Univ Otago Dept Informat Sci 60 Clyde St Dunedin New Zealand

Good governance practices are pivotal to the success of open source software (OSS) projects. However, the decision-making processes that are made available to stakeholders are at times incomplete and may remain buried and hidden in large amounts of software repository data. This work bridges this gap by unearthing enacted decision-making processes available for Python Enhancement Proposals (PEPs) from 1.54 million email messages that embody decisions made during the evolution of the Python language. This work employs a design science approach in operationalizing a framework called DeMaP miner that is used to discover hidden processes using information retrieval and information extraction techniques. It also uses process mining techniques to visualize the processes, and comparative structural analysis techniques to compare different decision processes. The work identifies a richer set of decision-making activities than those reported on the Python website and in prior research work (48 new decision activities, 199 new pathways and 6 new stages). The extracted decision process has been positively evaluated by a prominent member of the Python steering council. The extracted process can be used for process compliance checking and process improvement in OSS communities. Additionally, the DeMaP Miner framework can be extended and customized to suit other OSS projects, such as the openJDK project.

关键词： consensus decision-making decisions open source software development PEPs Python

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IoT-based group size prediction and recommendation system using machine learning and deep learning techniques

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SN APPLIED SCIENCES 2021年第2期3卷 160页

作者： Chopra, Deepti Kaur, Arvinder Guru Gobind Singh Indraprastha Univ GGSIPU Univ Sch Informat & Commun Technol USICT New Delhi India

In an open source software development environment, it is hard to decide the number of group members required for resolving software issues. Developers generally reply to issues based totally on their domain knowledge and interest, and there are no predetermined groups. The developers openly collaborate on resolving the issues based on many factors, such as their interest, domain expertise, and availability. This study compares eight different algorithms employing machine learning and deep learning, namely-Convolutional Neural Network, Multilayer Perceptron, Classification and Regression Trees, Generalized Linear Model, Bayesian Additive Regression Trees, Gaussian Process, Random Forest and Conditional Inference Tree for predicting group size in five open source software projects developed and managed using an open source development framework GitHub. The social information foraging model has also been extended to predict group size in software issues, and its results compared to those obtained using machine learning and deep learning algorithms. The prediction results suggest that deep learning and machine learning models predict better than the extended social information foraging model, while the best-ranked model is a deep multilayer perceptron((R.M.S.E. sequelize-1.21, opencv-1.17, bitcoin-1.05, aseprite-1.01, electron-1.16). Also it was observed that issue labels helped improve the prediction performance of the machine learning and deep learning models. The prediction results of these models have been used to build an Issue Group Recommendation System as an Internet of Things application that recommends and alerts additional developers to help resolve an open issue.

关键词： Internet of things Machine learning Deep learning software repositories open source software development Edge computing

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Studying the association between Gitcoin's issues and resolving outcomes

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JOURNAL OF SYSTEMS AND software 2023年 206卷

作者： Choetkiertikul, Morakot Puengmongkolchaikit, Arada Chandra, Pandaree Ragkhitwetsagul, Chaiyong Maipradit, Rungroj Hata, Hideaki Sunetnanta, Thanwadee Matsumoto, Kenichi Mahidol Univ Fac Informat & Commun Technol Salaya Thailand Nara Inst Sci & Technol Nara Japan Shinshu Univ Matsumoto Japan

The development of open-source software (OSS) projects usually have been driven through collaborations among contributors and strongly relies on volunteering. Thus, allocating software practitioners (e.g., contributors) to a particular task is non-trivial and draws attention away from the development. Therefore, a number of bug bounty platforms have emerged to address this problem through bounty rewards. Especially, Gitcoin, a new bounty platform, introduces a bounty reward mechanism that allows individual issue owners (backers) to define a reward value using cryptocurrencies rather than using crowdfunding mechanisms. Although a number of studies have investigated the phenomenon on bounty platforms, those rely on different bounty reward systems. Our study thus investigates the association between the Gitcoin bounties and their outcomes (i.e., success and non-success). We empirically study over 4,000 issues with Gitcoin bounties using statistical analysis and machine learning techniques. We also conducted a comparative study with the Bountysource platform to gain insights into the usage of both platforms. Our study highlights the importance of factors such as the length of the project, issue description, type of bounty issue, and the bounty value, which are found to be highly correlated with the outcome of bounty issues. These findings can provide useful guidance to practitioners. Editor's note: open Science material was validated by the Journal of Systems and software open Science Board.(c) 2023 Elsevier Inc. All rights reserved.

关键词： Bounty platform Issue-addressing outcome open source software development

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Biological Mutualistic Models Applied to Study open source software development

Biological Mutualistic Models Applied to Study Open Source S...

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11th IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

作者： Loyola, Pablo Ko, In-Young Korea Adv Inst Sci & Technol Div Web Sci & Technol Daejeon South Korea Korea Adv Inst Sci & Technol Dept Comp Sci Div Web Sci & Technol Daejeon South Korea

ISBN: (纸本)9780769548807;9781467360579

The evolution of the Web has allowed the generation of several platforms for collaborative work. One of the main contributors to these advances is the open source initiative, in which projects are boosted to a new level of interaction and cooperation that improves their software quality and reliability. In order to understand how the group of contributors interacts with the software under development, we propose a novel methodology that adapts Lotka-Volterra-based biological models used for host-parasite interaction. In that sense, we used the concept mutualism from social parasites. Preliminary results based on experiments on the Github collaborative platform showed that open source phenomena can be modeled as a mutualistic system, in terms of the evolution of the population of developers and repositories.

关键词： Web-based collaborative work Population models open source software development

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A revised open source usability defect classification taxonomy

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INFORMATION AND software TECHNOLOGY 2020年 128卷 106396-106396页

作者： Yusop, Nor Shahida Mohamad Grundy, John Schneider, Jean-Guy Vasa, Rajesh Univ Teknol MARA Fac Comp & Math Sci Shah Alam Selangor Malaysia Monash Univ Fac Informat Technol Melbourne Vic Australia Deakin Univ Fac Sci Engn & Built Environm Geelong Vic Australia

Context: : Reporting usability defects is a critical part of improving software. Accurately classifying these reported usability defects is critical for reporting, understanding, triaging, prioritizing and ultimately fixing such defects. However, existing usability defect classification taxonomies have several limitations when used for open source software (OSS) development. This includes incomplete coverage of usability defect problems, unclear criticality of defects, lack of formal usability training of most OSS defect reporters and developers, and inconsistent terminology and descriptions. Objective: : To address this gap, as part of our wider usability defect reporting research, we have developed a new usability defect taxonomy specifically designed for use on OSS projects. Method: : We used Usability Problem Taxonomy (UPT) to classify 377 usability defect reports from Mozilla Thunderbird, Firefox for Android, and the Eclipse Platform. At the same time, we also used the card-sorting technique to group defects that could not be classified using UPT. We looked for commonalities and similarities to further group the defects within each category as well as across categories. Results: : We constructed a new taxonomy for classifying OSS usability defects, called open source Usability Defect Classification (OSUDC). OSUDC was developed by incorporating software engineering and usability engineering needs to make it feasible to be used in open source software development. The use of the taxonomy has been validated on five real cases of usability defects. However, evaluation results using the OSUDC were only moderately successful. Conclusion: : The OSUDC serves as a common vocabulary to describe and classify usability defects with respect to graphical user interface issues. It may help software developers to better understand usability defects and prioritize them accordingly. For researchers, the OSUDC will be helpful when investigating both trends of usability defect typ

关键词： Usability defect reporting Usability defect taxonomy Empirical evaluation open source software development

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The Butterfly "Affect": impact of development practices on cryptocurrency prices

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EPJ DATA SCIENCE 2020年第1期9卷 21页

作者： Bartolucci, Silvia Destefanis, Giuseppe Ortu, Marco Uras, Nicola Marchesi, Michele Tonelli, Roberto Imperial Coll Business Sch London England Brunel Univ London London England Univ Cagliari DIEE Cagliari Italy Univ Cagliari DMI Cagliari Italy UCL Ctr Blockchain Technol London England

The network of developers in distributed ledgers and blockchains open source projects is essential to maintaining the platform: understanding the structure of their exchanges, analysing their activity and its quality (e.g. issues resolution times, politeness in comments) is important to determine how "healthy" and efficient a project is. The quality of a project affects the trust in the platform, and therefore the value of the digital tokens exchanged over it. In this paper, we investigate whether developers' emotions can effectively provide insights that can improve the prediction of the price of tokens. We consider developers' comments and activity for two major blockchain projects, namely Ethereum and Bitcoin, extracted from Github. We measure sentiment and emotions (joy, love, anger, etc.) of the developers' comments over time, and test the corresponding time series (i.e. theaffect time series) for correlations and causality with the Bitcoin/Ethereum time series of prices. Our analysis shows the existence of a Granger-causality between the time series of developers' emotions and Bitcoin/Ethereum price. Moreover, using an artificial recurrent neural network (LSTM), we can show that the Root Mean Square Error (RMSE)-associated with the prediction of the prices of cryptocurrencies-significantly decreases when including the affect time series.

关键词： Blockchain open source software development Data mining

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