1. Paul Ammann http://cs.gmu.edu/~pammann/
The Agile Heresy: What Drives Traditional Software Engineering, and Why Agile Turns it
Upside Down
Paul Ammann

2. The Caricature It’s Fun To Spin, But Let’s Look A Little Deeper
11/14/2018

3. Overview Déjà vu all over again.
Traditional Evolutionary Design circa 1970
A Disaster!
Planned Design
Managing The Cost Curve Through Upfront Analysis
The Heart of Modern Software Engineering
Agile Approaches
The Return Of Evolution
Managing The Cost Curve Through
Testing
Post Development Design
This Presentation Draws Heavily on Fowler and Ambler
Is Design Dead?, The New Methodology
Examining the Agile Cost of Change Curve
Déjà vu all over again.
11/14/2018

4. Traditional Evolutionary Design
Successful In Other Engineering Disciplines
Each Successive Widget Is an Improvement
In the Beginning, Programmers Just Programmed
Result Was Ad Hoc Structure
Eventually Hard – Impossible, Actually - To Maintain
The tendency towards irreducible number of errors
In a suitably complex system, any attempt to fix observed errors tends to result in the introduction of other errors - Brooks
Key is managing complexity
Why Software Engineering Developed as a Field
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5. Planned Design Introduction of Traditional Development Phases
Requirements, System Design, Detailed Design, etc.
Heavy Reliance on Upfront Analysis
The big errors are made at the beginning and rarely recognized. If caught at all, it is usually after fielding. The lesser errors surface as soon as coding begins and shout out when the first real user tests a prototype - Brooks
Early Life Cycle Effort Has Huge Potential ROI
Anticipate Change, and Plan for it
Identify Defects Early
Success Defined As “On Time and On Budget”
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6. Traditional Cost of Change Curve
Standard Motivation For Up Front Design Techniques
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7. Is Software Engineering Really Like Other Engineering
Separation of Design and Construction
Design is hard to predict; Construction is easy to predict
But software engineering is all design!
The Unpredictability of Requirements
No stable requirements means no predictable plan
But everyone recognizes that software requirements are soft!
Controlling Unpredictable Processes with Iteration
Working versions introduce reality – always a good thing.
The Adaptive Customer
Business value is hard to articulate precisely in advance
Perhaps Software Engineering is Different
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8. Agile: The Return of Evolution
The Problem With Traditional Design:
The Track Record of Anticipating Change is Pretty Lousy
Extremely Difficult To Maintain Non Executable Documents
How Relevant Is Your UML After Six Months?
What Does It Mean If Your Design Needs To Change?
Failure In Prior Design Process? (Traditional) vs
Normal First Class Problem In Software Engineering? (Agile)
How Often Are You Running Your Tests?
Key Gap: Making Mistakes vs. Finding Mistakes
Key Gap: Divergence Between Different Development Teams
Software Evolves Whether We Like It or Not
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9. Defect Discovery: Agile vs. Traditional
It’s All About The Deltas
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10. A Different Approach To Managing The Cost Curve
The Test Harness As Guardian
(Near) Instant Feedback on Changes (or Mistakes)
An Hour? Ten Minutes? Less?
Implies Something Is Executable From The Very Beginning
The Role of Continuous Integration
Effective Communication Mechanism
De-Emphasize Non Executable Artifacts
If It Doesn’t Execute, It’s Not Checkable
Hence, It Rots…
Avoid Anticipating Future Needs
YAGNI: You Ain’t Gonna Need It
The Heresy: Counter To Decades of Design Philosophy
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11. Agile Cost of Change Curve
A Good Agile Project Builds Something Different and Better Than The Original Design
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12. Refactoring – The New Design
Design Still Matters
Agile Distributes Design Effort
Focus is on Needed, Rather Than Anticipated, Functionality
Refactoring Requires Recognizing Defective Designs
And Replacing Them with Functionally Equivalent Designs
Requires Basic Training in Code Smells
Maintenance vs. Green Fields Development
After First 15 Minutes
All Projects Are Maintenance Projects
Design as a Post Development Activity
11/14/2018