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Software Delivery Risk Management: Application of Bayesian Networks in Agile Software Development

REFERENCES [1] M. Li, M. Huang, F. Shu and J. Li, “A risk-driven method for eXtreme programming release planning,” in Proc. of the 28th int. conf. on Software engineering , Shanghai, China, 2006, pp. 423–430. http://dx.doi.org/10.1145/1134285.1134344 [2] A. Nagy, M. Njima and L. Mkrtchyan, “A Bayesian Based Method for Agile Software Development Release Planning and Project Health Monitoring,” in 2nd Int. Conf. Intelligent Networking and Collaborative Systems (INCOS), Nov. 24–26, 2010, Thessaloniki, Greece. IEEE, 2010. http://dx.doi.org/10

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Software reliability growth modeling for agile software development

References Aggarwal, A.G., Kapur, P. and Garmabaki, A. (2011). Imperfect debugging software reliability growth model for multiple releases, Proceedings of the 5th National Conference on Computing for Nation Development-INDIACOM, New Delhi, India, pp. 337-344. Agile Alliance (2017). http://www.agilealliance.org/. Dingsøyr, T. and Lassenius, C. (2016). Emerging themes in agile software development: Introduction to the special section on continuous value delivery, Information and Software Technology 77(1): 56

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Several Ideas on Integration of SCRUM Practices within Microsoft Solutions Framework

Notes, vol. 11, no. 4, pp. 14-24, Aug. 1986. https://doi.org/10.1145/12944.12948 [9] “Manifesto for Agile Software Development,” Agile Alliance, 2001. [10] Software Development Models [Online]. Available: http://istqbexamcertification.com/what-are-the-software-developmentmodels/ [11] K. Beck, Extreme Programming Explained: Embrace Change, Addison-Wesley, 1999. ISBN: 978-0-321-27865-4. [12] J. Martin, Rapid Application Development, Macmillan Publishing Company, 1999. [13] The Standish Group

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Adopting to Agile Software Development

Abstract

Agile software development can be made successful, but there is no well-defined way how to achieve this. The problem is that the successful adoption of agile methods and practices is a complex process and this process should be customizable for a particular organization or a team. This research focuses on identification of agile methods and practices. Result of the research is the ranking of agile methods, practices and their usage trends. As some terms of agile software development are interpreted differently in different organizations and teams, terminology used is analyzed. Results of the research can be used as a reference material for those who are planning to adopt agile methods or are looking for the next agile practice to implement. Results will be used for the development of an expert system to support agile adoption.

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Product development models in the IT sector-From Waterfall to Agile Project Management Model s in the case of AVIRA SOFT S.R.L

.. Ghinea, V. M., Dima, A. M., & Hadad, S. (2017). EXCELLENCE MODEL FOR SUSTAINABLE CONVERGENCE IN THE EU HIGHER EDUCATION. Amfiteatru Economic, 19(11), 1107-1122 Hazzan, O. & Dubinsky, Y. (2008). Agile software engineering. London: Springer Verlag. Imran, G., Jawawi, D.N.A, Dorairaj, S. (2016). Emerging Innovations in Agile Software Development. Hershey PA: IGI Global. Layton, M.C. & Ostermiller,S.J. (2017). Agile Project Management For Dummies. Retrieved from: https

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Combining Data Analytics with Team Feedback to Improve the Estimation Process in Agile Software Development

Abstract

We apply a mixed research method to improve the user stories estimation process in a German company following agile software development. We combine software project data analytics with elicitation of teams’ feedback, identify root causes for wrong estimates and propose an improved version of the estimation process. Three major changes are adopted in the new process: a shorter non numerical scale for story points, an analogy-based estimation process, and retrospectives analyses on the accuracy of previous sprints estimates. The new estimation process is applied on a new project, and an improvement of estimates accuracy from 10% to 45% is observed.

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Evaluation of the Agility Level of the Organization

, Lean, and Kanban . Boston, MA: Addision-Wesley Professional, 2014. [5] K. Beck, M. Beedle, R. C. Martin et al. (2001, February) Manifesto for Agile Software Development , [Online]. Available: http://agilemanifesto.org/ [6] G. Linkevics, “Adopting to agile software development,” in Scientific J. of Applied Computer Systems. Riga, LV: Riga Technical University, 2014, pp. 64–70. [7] T. M. Mitchell, “Learning Sets of Rules,” in Machine Learning. New York: McGraw-Hill, 1997, pp. 283–291.

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Intercultural Communication and Management Factors and Their Impact to the Process of Global Software Development for Virtual and Non-Virtual Teams

References Agile Alliance, Manifesto for Agile Software Development, 2001, http://agilemanifesto.org/ Beck K., Extreme Programming Explained: Embrace Change. Boston: Addison-Wesley, 2000. Carmel E., Global Software Teams: Collaborating Across Borders and Time Zones. Upper Saddle River, NJ: Prentice Hall, 1999. Coggins E., 8 Factors That Impact Cross-Cultural Communication in the Workplace and Beyond. Hubpages. D’Iribarne P., 2009, Conceptualizing national cultures: an

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Introduction to the Special Issue on Software Engineering Methods, Tools and Products Improvement and Evaluation

References [1] ISBSG Repository Data Release 11. International Software Benchmarking Standards Group, 2009. [2] OWL 2 Web Ontology Language. Document Overview (Second Edition), W3C, 11 December 2012, 2009. [3] Kassab M. An empirical study on the requirements engineering practices for agile software development. In Software Engineering and Advanced Applications (SEAA), 2014 40th EUROMICRO Conference on , pages 254–261. IEEE, 2014. [4] Kowalska J. and Ochodek M. Supporting analogy-based e ort estimation with the use of ontologies. e

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Communication Process Modeling In Research Projects

/04/18/refactor-your-pmp-part-5-communications-management/ retrieved 12 June 2012 (2011). 6. Beck, Kent., et al. "Manifesto for Agile Software Development". Agile Alliance. http://agilemanifesto.org/, retrieved 14 June 2012, (2001). 7. http://www.tutorialspoint.com/management_concepts/agile_project_management.htm 8. Witten, I. H., Frank, E., Hal, M. A., Data Mining - Practical Machine Learning Tools and Techniques, Elsevier Third Edition, (2011). 9. http://weka.sourceforge.net/packageMetaData/, retrieved 10 June 2012. 10. Bruegge, Bernd., Dutoit, H. Allen., Object

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