1. Software Quality Engineering Roadmap

2. Business Objectives
Maximize Revenue
Minimize Costs

3. Maximize Revenue Improve market share: Improve product quality
Increase customer satisfaction
Better marketing
Improve cycletime
Increase product value:
Increase product quality
Define value proposition and match product capabilities and quality to customer needs

4. Improve Market Share Improve product quality
Increase customer satisfaction
Identify and address key customer concerns
Continuous improvement process
Practices for measuring and improving satisfaction
Expectation management practices
Better marketing
Match product to marketing needs
Improved requirements practices
Practices for measuring and improving marketing effectiveness
Improve cycletime
Cycletime measurement and continuous improvement
Increase product value
Define value proposition and match product capabilities and quality to customer needs

5. Minimize Costs – Improve Productivity
Productivity measurement and continuous improvement
Practices for improving productivity:
Tools usage
Technology selection
Reuse and common architecture development
Streamlining and automation
Workflow, templates, tools
Task elimination
Developer capability improvement through training

6. Improve Project Management – Activity Management
Practices: planning, estimation, progress tracking
Metrics: estimation accuracy, progress metrics
Estimation practices:
Maintain database of past projects
Estimate based on history of comparable projects
COCOMO (constructive cost model) provides questionnaire and formula for estimation based on organizational and project profile

7. Improve Project Management – Risk Management
Identify and track risks
Metrics examples:
Percentage of unidentified high-impact risks among those that actually occurred
Percentage of unmitigated high-impact risks among those that actually occurred
Percentage of effort spent on risk management and mitigation

8. Improve Project Management – People Management
Practices to measure and improve employee satisfaction
Teaming practices and effectiveness:
Metrics: Turnover %

9. Improve Project Management: In-Process Metrics
Slippage, progress
Inspection effectiveness (evolve as project proceeds)
Defect rates
Test progress
Reliability growth curves

10. Product Quality - Features
Requirements quality & effectiveness
Requirements prioritization & release planning

11. Product Quality - Performance
Defining performance objectives
Practices: designing for performance, performance analysis, performance testing
Primarily measurements and not metrics

12. Product Quality - Dependability
Reliability engineering: objective setting, practices and metrics
Availability: objective setting, practices and metrics
Security:
Practices for identifying threats (defining objectives)
Security engineering practices
Security testing: threat injection
Safety (similar to security and reliability)

13. Product Quality - Usability
Specifying usability objectives
Usability engineering practices
Usability measurements: surveys, avg. learning time, keystrokes for frequent operations etc.
Usability metrics: SUMI

14. Product Quality - Evolvability
Evolvability goals
Practices for improving evolvability

15. Development Effectiveness
Requirements
Design
Testing & Inspections
Configuration Management
Quality Engineering
Creative Research Systems

16. Development Effectiveness - Requirements
Requirements effectiveness practices
Elicitation practices, prototyping, requirements analysis practices, traceability
Requirements metrics
Activity metrics, also requirements defect injection rate

17. Development Effectiveness - Design
Practices for design effectiveness
Modularity practices, design patterns for achieving various quality attributes, design diagramming, design analysis techniques
Design metrics
Activity metrics, injection rates, product quality metrics, reuse percentage

18. Development Effectiveness – Testing & Inspections
Practices for testing effectiveness
Multistage testing, test strategy & planning, test case identification through equiv classes, automation of test generation, randomized parameters, automated testing
Reliability engineering
Test metrics
DRE charts, defect rates and densities, reliability …
Inspection practices and metrics

19. Development Effectiveness – Configuration Management
Configuration management practices
Metrics for configuration management effectiveness
Configuration management defect injection rate

20. Development Effectiveness – Quality Engineering Practices
Processes
Process Improvement / Continuous Improvement
Assessments

21. Quality Engineering Process
Initial process definition and tailoring
Process compliance metrics (certifications, assessments)
Process improvement
Improve effectiveness of practices
Improve breadth of process & practices (increased “maturity level”, CMMI-style)
Minimize volume of process, maximize effectiveness (agile development)
Define set of processes that address the most frequent causes of defects and achieve more of the business objectives: maximizing cost-benefit ratio for process practices
Requires deep understanding of process/quality relationships, high developer maturity and competence, and extensive customization to situational needs
A stage of evolution beyond simply adding process breadth and doing improvement.

22. Continuous Improvement
Quality tools and causal analysis, defect elimination
Identify problem area
Use fishbone diagrams to brainstorm and capture possible causes
Use results to design data collection scheme and gather data about actual causes of problem - This is an extremely important step. The fishbone itself is just a set of guesses. It does not tell you which causes need addressing
Use pareto charts to identify most significant causes of the problem
Use defect elimination techniques (checklists, templates etc) to try to prevent the problem in the future
Repeat continuously or until objective is achieved
Effectiveness measured through trend lines for various process metrics

23. Metrics Concepts Defining Metrics GQM paradigm
Metrics must have significant value: High impact (value provided to user of metric) compared to effort spent in collecting data.
Meaningfulness of metrics
Reliability
Validity
Importance of interpretation
Gathering Measurements

24. Goal-Question-Metric (GQM) Paradigm
What are the objectives for the metric?
Should identify the purpose of the metric – who wants to do what with it?
Includes “viewpoint”: whose viewpoint are we interested in for this? E.g. developer, project manager, organization manager, quality engineer, external assessor, customer.
What specific questions do we want answered?
Identify specific aspects of the problem that we care about
Includes operational definitions of the quantities we want to measure
Define measurements and metrics
What data will need to be gathered? Who will gather it and how?
What metric will be computed from the measurements?
Metrics must provide a basis for action
Metrics must have an interpretation: given a value, how will this be interpreted?
Metrics must have significant value: high impact (value provided to user of metric) compared to effort spent in collecting data
Meaningfulness of metrics
Reliability
Validity

25. Importance of Interpretation
Understanding the intrinsic limitations of the metric
Understanding the limitations of the data collection process
Understanding situational factors that provide context to the numbers

26. Gathering Measurements
Minimizing measurement effort:
Effort spent on providing data is “wasted” effort from project perspective – needs to be minimized!
Often, person who has to put in effort is different from the one who gets immediate value! Higher the effort, less the motivation for the provider to supply good data
Need for tools:
Tools improve accuracy of data, especially if collection is automated
May sometimes need to provide for manual adjustments to tool-generated data
Tools can automate processing of data and generate useful views (graphs) directly
Motivating measurement:
Set high bar on value: only ask for measurements that provide considerable value
Make value visible to people providing measurements (clear how the gathered data will be used)
Try to provide value to those providing measurements:
e.g. customer concerns actually get addressed
e.g. developers get useful feedback that helps them avoid problems and reduce effort

27. Metrics Perspective
Metrics are a small part of the overall quality engineering process.
Define objectives for metrics.
Metrics interpretation is key.
Actions and improvements based on metrics interpretation is the primary value achieved in the use of metrics.