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Proposal for an Experience Framework to Enhance Agile Methodologies

This proposal outlines the development of an Experience Framework (EF) aimed at strengthening Agile methodologies through structured validation and standardization. The framework seeks to address the lack of resources on effective Experience Frameworks and responds to the challenges of managing and accessing agile experimentation results. Key features include standardized data collection and analysis, facilitation of experiment replications, and the establishment of metrics for gauging Agile practices. With the aim of increasing knowledge, ensuring continuous improvement, and promoting collective information ownership, the EF is designed to make results accessible and actionable in real-world scenarios.

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Proposal for an Experience Framework to Enhance Agile Methodologies

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  1. Proposal of an Experience Framework for Agile Methodologies

  2. The rationale • Agile methodologies need validations • Scarce literature on Experience Framework (for AMs) • Previous few experiences have been troubles to access/manage results -Visek

  3. Experience Framework • A structure in which share experience, identify common standards for experiment actuation, collecting data and analyzing data, identify metrics and new approaches • In order to: validate practices, suggest suitable adoptions, increase knowledge in AMs

  4. ExperienceFramework • Create EF for the Agile Methodologies. Some features: • Allowing experiment replications. Replication is fundamental for the consolidation and validation of best practices in every applied discipline. Replication needs a standardization of the experimental process in order to avoid bias • Agile. To be compatible with AMs: repositories continuous integration, experiment replications, easy access, collective information ownership. The consolidated results should be promptly generalized and readily accessible

  5. 1. Standards for data collection

  6. 2. Standards for data analysis

  7. Examples • Statistics automated tools - SPSS • Patterns and makes predictions from an orderly display of data using concepts of probability and statistics • Statistical methods to make inferences and valid arguments about real-world situations

  8. 3. Standards for the set up of experiments

  9. 1. Experiment context and profile • Formative Research A formative research action on the environment may help in defining the experiment standards and detect the pre-test scenario in the company • Information about the industrial circumstances • Background information about the experiment • Information about related research

  10. 2. GQM + Lesson Learned

  11. 3. Experiment design • Theoretical Foundation of the Intervention - experiments unit, … • Distribution of Materials by Community Network Members (before the experiment)

  12. 4. Standards for the experiment data collection • Data collection instrument • Data collection schedule • Data collection Start Up • Building a measurement support system

  13. 4. Standards for the actuation of experiments

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