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Enabling GSD Task Allocation via Cloud-based Software Processes
Newcasle University, UK.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).ORCID iD: 0000-0002-6952-1053
Newcasle University, UK.
2017 (English)In: International Journal of Networked and Distributed Computing, E-ISSN 2211-7946, Vol. 5, no 4, 221-232 p.Article in journal (Refereed) Published
Abstract [en]

Allocating tasks to distributed sites in Global Software Development (GSD) projects is often done unsystematically and based on the personal experience of project managers. Wrong allocation decisions increase the project’s risks as tasks have dependencies that are inherited by the distributed sites. Decision support can help make the task allocation a more informed and systematic process. The challenges in allocating tasks to distributed sites exist because of three distance dimensions between sites (geographical, temporal and cultural). An informed task allocation decision needs to consider these distances. Therefore, in this paper, we propose to integrate and semi-automate the calculation of an existing Global Distance Metric (GDM) into an architecture that supports executing cloud-based software processes. We analyze the potential of integrating the GDM into this architecture and identify the needed extensions to the architecture.

Place, publisher, year, edition, pages
2017. Vol. 5, no 4, 221-232 p.
Keyword [en]
Global software development, Distributed tasks allocation decision support, Cloud-basedsoftware processes, Global distance
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-37333DOI: 10.2991/ijndc.2017.5.4.4OAI: oai:DiVA.org:mdh-37333DiVA: diva2:1160988
Projects
AMASS - Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems
Available from: 2017-11-28 Created: 2017-11-28 Last updated: 2017-11-28Bibliographically approved

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Gallina, Barbara

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