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Agile Physics - The Math of Flow

Short explanations of how and why to apply math, probability, and statistics in Agile development. These are topics everyone should know, but are too scared to ask.

Description

This is a growing course (new material added over time) that explains the math behind what we experience when doing Agile work. It is a series of short topics that deep dive into Flow.

Course curriculum so far

  1. Before we begin...

    1. Welcome and about this course

    2. References, resources and thanks...

  2. System Utilization

    1. System Utilization and Queuing Time

    2. System Utilization Key Points Pop Quiz

    3. Calculating the Financial Impact of High System Utilization

    4. Understanding the formula (only if interested - be brave)

    5. Paper: The single server queue in heavy traffic, Kingman 1961

  3. Likely Improvement by Adding Teams or People

    1. Amdahl's Law - Speedup in parallel systems

    2. Calculator: How much improvement do I get by adding more teams or people?

    3. Scaling by Adding Teams or People Pop Quiz

  4. Cycle Time (or Lead Time) Distribution

    1. Video: Understanding Cycle Time Distributions (history and intro)

    2. Interactive Article: Understanding Cycle Time Distribution Shapes

    3. Paper: The Economic Impact of Software Development Process Choice - Cycle-time Analysis and Monte Carlo Simulation Results

    4. Article: The Math and Science Behind Blocked (my blocker management SaaS application)

    5. Downloads: Presentation + Spreadsheet + Simulation Tools

  5. How Much Data Do We Need (for forecasting, etc)

    1. Calculator: How Many Samples Do I Need?

    2. Rule of Three - Approximation of "If it was there we should have seen it by now after n samples"

    3. Hypothesis Experiment Effect Size and Sample Count

  6. Optimal Batch Size

    1. Calculator: Computing the Optimal Batch Size

  7. Undiscovered Defect Estimation

    1. Calculator: Capture-Re Capture: Latent Defect Estimation

    2. Spreadsheet: Latent Defect Estimation

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