1. Determining Requirements-to-Code Expansion Factors – The Magical Number Seven?
Ali Afzal Malik, Supannika Koolmanojwong, Barry Boehm USC-CSSE
{alimalik, koolmano,
Annual Research Review
March 17, 2009
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2. Cockburn’s Use Case Expansion Levels
(Cockburn, Writing Effective Use Cases, 2001)
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3. What are the Level-to-Level Expansion Factors?
Cloud to Kite
Kite to Sea Level
Sea Level to Fish
Fish to Clam
Clam to Lava
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4. IBM-UK Expansion Factor Experience
Business Objectives 5 Cloud
Business Events/Subsystems 35 Kite
Use Cases/Components 250 Sea level
Main Steps/Main Operations Fish
Alt. Steps/Detailed Operations 15,000 Clam
SLOC* 1,000K – 1,500K Lava
*(70 – 100 SLOC/Detailed Operation)
(Hopkins & Jenkins, Eating the IT Elephant, 2008)
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5. Testing Applicability to Small E-Services Projects
Graduate level
12 weeks in Fall; 12 weeks in Spring
Team size: 6 on-campus, 2 off-campus students
Real Clients: Neighborhoods and USC departments
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6. Empirical Study 20 projects Architected Agile 2004 - 2006
Custom-development
Analyzed
Requirements elaboration
Effort elaboration
Documentation size elaboration
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7. Mapping Cockburn Metaphor* Project Data Document(s) Cloud
Organizational goals
Operational Concept Description
Kite
Top-level services
Sea Level
Use cases
System and Software Requirements Definition
System and Software Architecture Description
Fish
Main steps
Lava
SLOC
Source code
*Clam level skipped.
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8. Requirements Elaboration1 2
Expansion from Cloud to Kite
Expansion from Kite to Sea Level 3 4
Expansion from Sea Level to Fish
Expansion from Fish to Lava
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9. Effort & Documentation Size Elaboration
Expansion of Project Effort
Expansion of Document Size
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10. Expansion Factors Summary
Stage
Elaboration Factors
Number of
Requirements
Relative
Effort
Relative Documentation
Size
Cloud to Kite
1.59
2.30
1.94
Kite to Sea Level
1.10
14.06
7.82
Sea Level to Fish
3.75
1.04
2.60
Fish to Lava
74.27
3.89
6.13
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11. Conclusions
Magical number seven not a good fit to architected agile projects
Fewer actual expansion levels
Some confounding factors
Student teams motivated to work out details early
Wide variation in OTS solution components
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