Engaging developers in open source software projects: harnessing social and technical data mining to improve software development

Author(s):  
Patrick Eric Carlson
Author(s):  
Chitu Okoli ◽  
Kevin Carillo

Intellectual property is an old concept, with the first recorded instances of patents (1449) and copyrights (1662) both occurring in England (“Intellectual property”, Wikipedia, 2004). The first piece of software was submitted for copyright to the United States Copyright Office in 1961, and was accepted as copyrightable under existing copyright law (Hollaar, 2002). The open source movement has relied upon controversial intellectual property rights that are rooted in the overall history of software development (Lerner & Tirole, 2002; von Hippel & von Krogh, 2003). By defining specific legal mechanisms and designing various software licenses, the open source phenomenon has successfully proposed an alternative software development model whose approach to the concept of intellectual property is quite different from that taken by traditional proprietary software. A separate article in this encyclopedia treats open source software communities in general as a type of virtual community. This article takes a historical approach to examining how the intellectual property rights that have protected free/open source software have contributed towards the formation and evolution of virtual communities whose central focus is software projects based on the open source model.


10.28945/4516 ◽  
2020 ◽  
Author(s):  
Christine Bakke

Aim/Purpose: To examine crowd-sourced programming as an experiential learning, instructional medium. The goal is to provide real-time, real-world, artificial intelligence programming without textbook instructional materials. Background: Open source software has resulted in loosely knit communities of global software developers that work together on a software project. Taking open source software development to another level, current trends have expanded into crowd sourced development of Artificial Intelligence (AI). This project explored the use of Amazon Alexa’s tools and web resources to learn AI software development. Methodology: This project incorporated experiential and inquiry educational methods that combined direct experience with crowd-sourced programming while requiring students to take risks, solve problems, be creative, make mistakes and resolve them. The instructor facilitated the learning experience through weekly meetings and structured reports that focused on goal setting and analysis of problems. This project is part of ongoing research into small group creative works research that provides students with real-world coding experience. Contribution: Undergraduate students successfully programmed an introductory level social bot using experiential learning methods and a crowd-sourced programming project (Amazon Alexa social bot). Findings: A of the experience and findings will be included with final paper release summary Recommendations for Practitioners: Crowd sourced programming provides opportunities and can be harnessed for semester long coding projects to develop student programming skills through direct involvement in real open sourced projects. Recommendation for Researchers: There is a high rate of failure associated with software projects, yet pro-gramming courses continue to be taught as they have been for decades. More research needs to be done and instructional materials developed for the undergraduate level that use real programming projects. Can we improve the rate of success for software projects by requiring expe-riential education in our courses? Impact on Society: Crowd-sourced programming is an opportunity for students to learn to program and build their portfolio with real world experience. Students participating in crowd-sourced programming are involved in creative works research and gain experience developing real-world software. Future Research: Future research will explore experiential learning such as crowd-sourced and other open source programming opportunities for undergraduate students to participate in real software development.


Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 309
Author(s):  
Edna Dias Canedo ◽  
Heloise Acco Tives ◽  
Madianita Bogo Marioti ◽  
Fabiano Fagundes ◽  
José Antonio Siqueira de Cerqueira

Computer science is a predominantly male field of study. Women face barriers while trying to insert themselves in the study of computer science. Those barriers extend to when women are exposed to the professional area of computer science. Despite decades of social fights for gender equity in Science, Technology, Engineering, and Mathematics (STEM) education and in computer science in general, few women participate in computer science, and some of the reasons include gender bias and lack of support for women when choosing a computer science career. Open source software development has been increasingly used by companies seeking the competitive advantages gained by team diversity. This diversification of the characteristics of team members includes, for example, the age of the participants, the level of experience, education and knowledge in the area, and their gender. In open source software projects women are underrepresented and a series of biases are involved in their participation. This paper conducts a systematic literature review with the objective of finding factors that could assist in increasing women’s interest in contributing to open source communities and software development projects. The main contributions of this paper are: (i) identification of factors that cause women’s lack of interest (engagement), (ii) possible solutions to increase the engagement of this public, (iii) to outline the profile of professional women who are participating in open source software projects and software development projects. The main findings of this research reveal that women are underrepresented in software development projects and in open source software projects. They represent less than 10% of the total developers and the main causes of this underrepresentation may be associated with their workplace conditions, which reflect male gender bias.


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