1.
The sequel: Another year using the Project Defect Model 1 May 4, 2004 Ben Linders
The sequel: another year using the Project
Defect Model
ESEPG 2004 Conference,
London, June 14
Ben Linders
Operational Development & Quality
Ericsson R&D, The Netherlands
ben.linders@ericsson.com, +31 161 24 9885

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The sequel: Another year using the Project Defect Model 2 May 4, 2004 Ben Linders
Overview
• Why a defect model?
• How does it work?
• Experiences from projects
• Conclusions
Measurements for product quality
and process effectiveness

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The sequel: Another year using the Project Defect Model 3 May 4, 2004 Ben Linders
Ericsson, The Netherlands
• Benelux Market Unit & Main R&D Design Center
• R&D: Intelligent Networks
– Strategic Product Management
– Product marketing & technical sales support
– Provisioning & total project management
– Development & maintenance
– Customization
– Supply & support
• 1300 employees, of which 350 in R&D
Projects: Quality next to Lead-time and Costs

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The sequel: Another year using the Project Defect Model 4 May 4, 2004 Ben Linders
Purpose Project Defect Model
Why?
– to control quality of the product during development
– and improve development/inspection/test processes
Business Benefit:
Better planning & tracking
Early risks signals
Save time and costs
Happy customers!

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The sequel: Another year using the Project Defect Model 5 May 4, 2004 Ben Linders
History of the Model
• 2001
– Defined, introduced in first project
• 2002
– Used in 2 projects, improved along the way
– First release predictions
• 2003
– Industrialize model/tool
– First results presented at ESEPG 2003
– Used in all (5) major projects
• 2004
– Target defined (Balanced ScoreCard)
– New applications: Total projects, defect flows

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The sequel: Another year using the Project Defect Model 6 May 4, 2004 Ben Linders
Modeling Defect Flow
Insertion: Where are defects made? How to prevent?
Detection: Where are defects found? Early/economic removal?

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The sequel: Another year using the Project Defect Model 7 May 4, 2004 Ben Linders
Planning & Tracking of Quality
• Plan Quality Up Front
– Documents/code (# defects made)
– Inspection & Test effectiveness (% detection rate)
Quality consequence of project decisions
• Track Quality during project
– Actual # defects found (inspection/test)
– Estimate remaining defects: to be found / delivered
'Real-time' prediction of product quality possible
Quality view of design/test progress
Quicker escalation of quality risks

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The sequel: Another year using the Project Defect Model 8 May 4, 2004 Ben Linders
Implementation
• Tool: Excel based defect data base & estimation
• Frequent estimation & analysis/feedback sessions
• Weekly tracking & reporting of product quality
• Includes proven techniques: ODC, requirement coverage, test matrices
Tailored per project, flexible, result oriented
Overall data based on all projects: Planning constants
Quality data, additional to time & costs!

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The sequel: Another year using the Project Defect Model 9 May 4, 2004 Ben Linders
Results
• Data from the projects
• Feedback sessions
• Conclusions
7 projects, of which 3 ongoing
Incremental development, team based
Different size/length: size factor used.
RUP based process

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The sequel: Another year using the Project Defect Model 10 May 4, 2004 Ben Linders
Detection rates projects
• Big projects have a better detection rate:
– More extensive test phases
– Interdependencies/risks between projects clear, quicker actions
– Incremental development, learning from first increments brings benefits
• Average detection rate in line with industry figures:
– DACS: Typical software projects 15% slip though (85% detection)
– Jones: Average 85%, most efficient 95%
Analyze/track projects that go below the target performance of 90%
* Project still ongoing at time of measurement
Project detection rates (inspections & test)
Proj A Proj B Proj C Proj D Proj E* Proj F* Proj G* Average
Rate 95% 95% 90% 59% 94% 86% 89% 90%
Size 1 4 1 1 5 3 1

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The sequel: Another year using the Project Defect Model 11 May 4, 2004 Ben Linders
Injection rates phases
• Very elaborated architecture (feasibility phase). Many defects made,
most of them are found in the architecture reviews.
• Lean design.
• Most defects made during coding
“Normal” defect pattern, with sufficient focus in all phases on defect
prevention.
Phase injection rates
Requirements Architecture Design Code
Rate 6% 21% 15% 58%

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The sequel: Another year using the Project Defect Model 12 May 4, 2004 Ben Linders
Detection rates phases
• Lower detection rate in requirements phase: incremental development,
start when only part of requirements is stable
• High architecture/design: effective inspections, good architecture skills
• Lower code detection: one project just starting with code inspections
(when excluded from measurement: 50% code detection rate)
• Function & system test: Acceptable rates
• Network test, low rate, but defects that are found would give major
problems to customers: Good cost/benefit of the test phase
Focus on inspection improvement & test focus, capture defects earlier
Phase detection rates
Requirements Architecture Design Code Function Test System Test Netw ork Test Total
Rate 30% 67% 66% 40% 48% 48% 27% 47%

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The sequel: Another year using the Project Defect Model 13 May 4, 2004 Ben Linders
Feedback sessions
• Frequent, short
• At the workplace
• All data available (Excel)
• Design/test leaders
Show data
ask questions
form conclusions
take needed actions
Feedback sessions enabled earlier conclusions, better acceptance of
results, and quick and focused corrective/preventive actions.
Feedback: Collected data delivered to the
people that have been doing the work, in order
to support their understanding of the situation at
hand and help them to take needed actions

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The sequel: Another year using the Project Defect Model 14 May 4, 2004 Ben Linders
Conclusions
Project Defect Model helps projects to:
– Estimate/track defects: Improve product release quality, save time/cost
– Design/test progress: Better planning, risk management, decisions
Benefits for R&D
– Project portfolio: Dimension project teams/maintenance teams
– Product quality: Less maintenance, satisfied customers
– Employees: More involved, empowered, motivated

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The sequel: Another year using the Project Defect Model 15 May 4, 2004 Ben Linders
Further reading
Papers
– Controlling Product Quality During Development with a Defect Model,
Proceedings ESEPG 2003
– Make what’s counted count, Better Software magazine march 2004
References
– Managing the software process. Watts Humphrey.
– Metrics and models in Software Quality Engineering. Stephen H. Kan.
Ben Linders, Ericsson R&D, The Netherlands
ben.linders@ericsson.com, +31 161 24 9885