• Quality measurements in agile software development

    by  • July 24, 2013 • Quality measurement, Software quality

    In the context of agile software process the measurement approaches on varying levels and for varying purposes have been proposed. In this subsection we present the core measurements that are involved in agile software development methods.

    Measurements in Scrum

    The SCRUM methodology defines certain measures. Based on The Scrum Guide (Schwaber and Sutherland 2011) the following are the recommended measures in SCRUM:

    • Product backlog. At any point in time, the total work remaining to reach a goal can be summed. The Product Owner tracks this total work remaining at least for every Sprint Review. The Product Owner compares this amount with work remaining at previous Sprint Reviews to assess progress toward completing projected work by the desired time for the goal. This information is made transparent to all stakeholders. Various trend burn-down, burn-up and other projective practices have been used to forecast progress. These have proven useful. However, these do not replace the importance of empiricism. In complex environments, what will happen is unknown. Only what has happened may be used for forward-looking decision-making.
    • Sprint backlog. At any point in time in a Sprint, the total work remaining in the Sprint Backlog items can be summed.

    The quality goals are specified in the “Definition of done” and therefore during the sprint, the quality goals should not decrease. The SCRUM methodology does not propose more specific measurements regarding product quality.

    Measurements in KANBAN

    In KANBAN methodology (Anderson and Reinertsen 2010) the work progress is tracked using cumulative flow diagrams, see Figure 1. The average lead time of work items can be read from x-axis and the amount of work in progress from y-axis.


    Figure 1. Cumulative flow diagram

    Other proposed charts in KANBAN according to Anderson and Reinertsen (2010) are, e.g., the following:

    • lead time distribution
    • mean lead time trend
    • mean lead time and due date performance
    • throughput (#deployed per month)
    • issues and blocked work item chart
    • quality (bugs per feature each day)

    In the next post, we will present the key findings from empirical research on measurements, different measures and their rationale in the agile context, in practice.


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