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Software Quality Engineering Roadmap

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Presentation on theme: "Software Quality Engineering Roadmap"— Presentation transcript:

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.

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