Playing With Your Project Data in Scrum Retrospectives

Modern, agile software development methods rely on iterative work and improvement cycles to deliver their claimed benefits. In Scrum, the most popular agile method, process improvement is implemented through regular Retrospective meetings. In these meetings, team members reflect on the latest development iteration and decide on improvement actions. To identify potential issues, data on the completed iteration needs to be gathered. The Scrum method itself does not prescribe these steps in detail. However, Retrospective games, i.e. interactive group activities, have been proposed to encourage the sharing of experiences and problems. These activities mostly rely on the collected perceptions of team members. However, modern software development practices produce a large variety of digital project artifacts, e.g. commits in version control systems or test run results, which contain detailed information on performed teamwork. We propose taking advantage of this information in new, data-driven Retrospective activities, allowing teams to gain additional insights based on their own team-specific data.

[1]  Christoph Matthies,et al.  Towards Empirically Validated Remedies for Scrum Retrospective Headaches , 2020, HICSS.

[2]  Abram Hindle,et al.  Judging a Commit by Its Cover: Correlating Commit Message Entropy with Build Status on Travis-CI , 2016, 2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR).

[3]  Luke Hohmann,et al.  Innovation Games: Creating Breakthrough Products Through Collaborative Play , 2006 .

[4]  Manfred Broy,et al.  Artefacts in software engineering: a fundamental positioning , 2018, Software & Systems Modeling.

[5]  Mirko Perkusich,et al.  Assisting the continuous improvement of Scrum projects using metrics and Bayesian networks , 2017, J. Softw. Evol. Process..

[6]  Michele Marchesi,et al.  The JIRA Repository Dataset: Understanding Social Aspects of Software Development , 2015, PROMISE.

[7]  Georgios Gousios,et al.  Oops, My Tests Broke the Build: An Explorative Analysis of Travis CI with GitHub , 2017, 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR).

[8]  Paul Dourish,et al.  Seeking the source: software source code as a social and technical artifact , 2005, GROUP.

[9]  Ita Richardson,et al.  Making Software Engineering Research Relevant , 2014, Computer.

[10]  Bertrand Meyer,et al.  Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment , 2018, Lecture Notes in Computer Science.

[11]  T T YingAnnie,et al.  Source code that talks , 2005 .

[12]  Suzanne M. Embury,et al.  Effect of Continuous Integration on Build Health in Undergraduate Team Projects , 2018, DEVOPS.

[13]  Christoph Matthies,et al.  Attitudes, Beliefs, and Development Data Concerning Agile Software Development Practices , 2019, 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET).

[14]  Christoph Matthies,et al.  Counteracting Agile Retrospective Problems with Retrospective Activities , 2019, EuroSPI.

[15]  Esther Derby,et al.  Agile Retrospectives: Making Good Teams Great , 2006 .

[16]  Tao Xie,et al.  Software intelligence: the future of mining software engineering data , 2010, FoSER '10.

[17]  Antònia Mas Picahaco,et al.  Agile Retrospective Games for Different Team Development Phases , 2016, J. Univers. Comput. Sci..

[18]  Premkumar T. Devanbu,et al.  Belief & Evidence in Empirical Software Engineering , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE).

[19]  Jane Cleland-Huang,et al.  Cold-Start Software Analytics , 2016, 2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR).

[20]  Christoph Matthies,et al.  Agile metrics for a university software engineering course , 2016, 2016 IEEE Frontiers in Education Conference (FIE).

[21]  Chris Northwood Planning Your Work , 2018 .

[22]  James L. Wright,et al.  Source code that talks: an exploration of Eclipse task comments and their implication to repository mining , 2005, ACM SIGSOFT Softw. Eng. Notes.

[23]  Christoph Matthies,et al.  Beyond Surveys: Analyzing Software Development Artifacts to Assess Teaching Efforts , 2018, 2018 IEEE Frontiers in Education Conference (FIE).

[24]  Armando Fox,et al.  TEAMSCOPE: measuring software engineering processes with teamwork telemetry , 2018, ITiCSE.

[25]  Celal Ziftci,et al.  Who Broke the Build? Automatically Identifying Changes That Induce Test Failures in Continuous Integration at Google Scale , 2017, 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP).

[26]  John Noll,et al.  A Qualitative Method for Mining Open Source Software Repositories , 2012, OSS.