敏捷分析和团队规模的影响——规范化的实践.pdf

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1、THANK YOU1Karen McRitchieAnalysis of Agile Metrics and the Impact of Team Size-An Exercise In Normalizing Copyright Galorath Incorporated 202330,000 foot view of what will be coveredAbstractAgile Data&Normalization010203Agile data is mixed and it can be difficult to interpret the number of sprints/i

2、terations,particularly for benchmarking purposes.A study of agile projects in the ISBSG dataset was performed.Resultant metrics were used to examine productivity changes with different team sizes.This presentation will review the data analysis process,findings and how they are considered for estimat

3、ing in SEER-SEM.2Analysis of Ranges and TrendsApplying Trends to EstimatesAgile sizing is associated with story points but they have issuesThe ChallengeStories are team specificLack of Standardization occurs when each team defines what is meant by a story.It can be helpful for project implementation

4、,but there is no practical way to compare stories from one team to the next.Loss of learning The lack of non-standard metrics leads to the lack of historical perspective.Benchmarking and measuring improvement become nearly impossible,even within an organization.3Difficult to measure and learnCaveat

5、this presentation is not about using functional size.That is stipulated The OpportunityISBSG has a critical mass of agile specific data to study and help Examine Data RangesReview requirements/stories to identify users,objects and their functional relationships.Derive Normalized MetricsEnsure that a

6、ll sprint data are expressed in consistent units.Develop a sprint productivity metric that can be used regardless of the sprint duration or team size.Examine Team Size ImpactsReview how normalized productivity is impacted by team size.Look at different views and data selections to see where the stro