Agile Methods Knowledge Representation for Systematic Practices Adoption

The popularity of agile methods is constantly increasing. Information and feedback on how these frameworks were adopted can easily be found in academia and industrial knowledge bases. Such a collective experience allowed the development of many approaches in the aim of simplifying the adoption process and maximizing the chances of success. These approaches provide practitioners with guidelines to help them find the practice that suits their team best. Nonetheless, these approaches are not systematic and practitioners need to go through a long process. For instance, they need to identify the important situational factors that can have a positive/negative effect on the agile practice adoption. Available experiences thus require lots of effort to be discovered. This research proposes an agile methods knowledge representation using an ontology so that the knowledge and experience on agile adoption reported in literature may be reusable and systematic. Based on this model, added knowledge and inference rules, practitioners will systematically be able to decide which practice to select and adopt, i.e, for a given goal, practitioners can retrieve which practices to achieve; from a situation, teams can tell what can be harmful and what can be useful for adopting a practice or what problems they may encounter; etc.

[1]  Eric S. K. Yu,et al.  A Repository of Agile Method Fragments , 2010, ICSP.

[2]  Casper Lassenius,et al.  Scaling Scrum in a Large Globally Distributed Organization: A Case Study , 2016, 2016 IEEE 11th International Conference on Global Software Engineering (ICGSE).

[3]  Brian Fitzgerald,et al.  An Empirical Study of System Development Method Tailoring in Practice , 2000, ECIS.

[4]  Fernando Silva Parreiras,et al.  Agile methods tailoring - A systematic literature review , 2015, J. Syst. Softw..

[5]  Jordi Cabot,et al.  Situational Evaluation of Method Fragments: An Evidence-Based Goal-Oriented Approach , 2010, CAiSE.

[6]  Tore Dybå,et al.  Challenges of shared decision-making: A multiple case study of agile software development , 2012, Inf. Softw. Technol..

[7]  D. D. Gregorio How the Business Analyst supports and encourages collaboration on agile projects , 2012, 2012 IEEE International Systems Conference SysCon 2012.

[8]  Manuel Kolp,et al.  An Intentional Perspective on Partial Agile Adoption , 2017, ICSOFT.

[9]  Felix Flentge,et al.  Agile Technical Management of Industrial Contracts: Scrum Development of Ground Segment Software at the European Space Agency , 2011, XP.

[10]  Tommi Mikkonen,et al.  Exploring ScrumBut - An empirical study of Scrum anti-patterns , 2016, Inf. Softw. Technol..

[11]  Michael Maham Planning and Facilitating Release Retrospectives , 2008, Agile 2008 Conference.

[12]  Yngve Lindsjørn,et al.  Obstacles to Efficient Daily Meetings in Agile Development Projects: A Case Study , 2013, 2013 ACM / IEEE International Symposium on Empirical Software Engineering and Measurement.

[13]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[14]  Manuel Kolp,et al.  Agile Manifesto and Practices Selection for Tailoring Software Development: A Systematic Literature Review , 2018, PROFES.

[15]  Gary B. Wills,et al.  Using Factor Analysis to Generate Clusters of Agile Practices (A Guide for Agile Process Improvement) , 2010, 2010 Agile Conference.

[16]  Aybüke Aurum,et al.  Understanding Decision-Making in Agile Software Development: A Case-study , 2008, 2008 34th Euromicro Conference Software Engineering and Advanced Applications.