Intellectual Property Challenges in the Crowdsourced Software Engineering: An Analysis of Crowdsourcing Platforms

Author(s):  
Hani Al-bloush ◽  
Badariah Solemon
2018 ◽  
Vol 7 (4.35) ◽  
pp. 354
Author(s):  
Hani Al-Bloush ◽  
Badariah Solemon

Crowdsourced Software Engineering (CSE) is an application of online problem-solving model that provides a dynamic way of harnessing crowd intelligence in obtaining creative solutions. It consists of four elements: crowdsourcer, crowd, platform, and tasks. Although CSE offers various advantages to software engineering practices, recent research highlighted that there is still a lack of thorough understanding of Intellectual Property (IP) ownership rights of CSE elements. Therefore, management and control of CSE for obtaining adequate IP from the crowd is inevitable to reduce the risks of using that IP.  This paper reviews existing CSE platforms and analyses associated IP challenges encountered by software engineering activities. 51 platforms were preselected and amongst these, analyses were performed on 37 CSE platforms. Exclusion of 11 platforms is on the basis of unavailability and 3 of which are linked to the same webpage. It also shows that 59% of the platforms acquire IP ownership of deliverables submitted by the crowd while 19% do not have a statement which provides clarity on IP ownership in their legal documents. This paper is significant in providing better understanding of IP risks of these CSE platforms and in assisting both crowdsourcers and the crowd in choosing crowdsourcing platforms based on the default IP ownership specification, which is often specified in legal documents of these platforms.


2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.


Author(s):  
Mark J. Davison ◽  
Ann L. Monotti ◽  
Leanne Wiseman

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