Software Quality Engineering CS410

1. Software Quality EngineeringCS410 Class 5 Seven Basic Quality Tools

2. Seven Basic Quality Tools • Promoted by Ishikawa (1989) • Set of statistical tools for quality control • Can be used to analyze software metrics • Most applicable to Project Managers • Statistical process control for SW development is more challenging than traditional manufacturing • Tools can have a positive influence on quality improvement and decision making

3. Seven Basic Quality Tools • Seven Tools 1. Checklist (or Check Sheet) 2. Pareto Diagram 3. Histogram 4. Scatter Diagram 5. Run Chart 6. Control Chart 7. Cause-Effect Diagram • Figure 5.1 p. 130

4. Checklist • A paper (or softcopy) form used for collecting and arranging data so that it can be easily used later • Also a method for ensuring that key points and tasks are addressed, or performed, at the correct times • Also a method to assist in knowing when a particular task is complete • Can be implemented as an expert system to guide process and give advise

5. Checklist • Checklist examples: • Common Error Checklist - developed as part of DPP, used at stage kickoff to review common errors at that stage • Process Checklists • Program Fix Checklists - ensure that all the required steps for completing a fix have been done (example fig. 5.2 pp132-133) • Code Complete Checklists - ensure that all coding standards and procedures have been followed

6. Pareto Diagram • Pareto Principle (80/20 rule) • 80% of the defects are contained in 20% of the modules and components • 20% of a particular defect type cause 80% of the customer calls • Pareto analysis helps identify focus areas that cause most of the problems • Pareto Analysis can be charted as frequencies in descending rank order with a cumulative percentage line (fig 5.3 p. 134 and fig. 5.4 p. 136)

7. Histogram • A graphic representation of frequency distribution • Should convey complete information at a glance • Examples: • Defect distributions by Sev level (fig. 5.5(A) p. 137) • Defect distribution by days open (fig. 5.5(B) p. 137) • Profile of Customer Satisfaction (fig. 5.6 p. 137)

8. Run Charts • A real-time statement of quality and/or workload. • Defect arrival rates weekly • Defect backlog • Delinquent fixes • Should include target for comparison • Can track significant events, and show results • Figure 5.7 p. 138

9. Run Charts • Good tool for project and schedule management. • Run Chart can display the typical “S” Curve • Tracks actual vs. planned over time • Completion of design review • Completion of code inspection • Completion of code integration • Completion of component test • Completion of system test • etc.

10. Scatter Diagrams • Usually relates to investigative work (I.e. investigating relationships) • Requires precise data • Works well for correlation analysis • For example: Code complexity vs. Defect Rate (fig 5.9 p. 140) • Shows positive correlation • Can be used as a predictor • Can be used as a tool to reduce defect rate (by reducing code complexity)

11. Scatter Diagrams • Can also be used for identifying/prioritizing areas requiring action items • For example: Defects rates for reused components in multiple projects (fig. 5.10 p. 141, and fig. 5.11 p. 142) • Helps identify chronic problem components • Helps focus action items on greatest payback

12. Control Chart • A tool used in Statistical Process Control (SPC) • Can be used real-time for improving consistency and stability • A tool for measuring Process Capability • Process Capability - inherent variation in the process in relation to the specification limits • The smaller the process variation the better the process’s capability • Process Capability is a difficult thing to estimate in software projects, however Control Charts are a useful quality management tool.

13. Control Chart • Types of control charts • X-bar - sample averages • S chart - standard deviations • Median chart - individuals • P chart - proportion nonconforming • NP chart - number nonconforming • C chart - number nonconformities • U chart - nonconformities per unit • Most appropriate to SW Engineering • P chart - when percentages are involved • U chart - when defect rates are involved

14. Control Chart • Control limits must be calculated and included on the chart • Different ways of calculating control limits exists. • Historical data • Weighted averages • Standard Deviations • SW metrics that can be control charted • Defects per component/KLOC (fig. 5.12 p. 146) • Phase effectiveness (fig. 5.14 p. 147) • Backlog Management Index

15. Cause-Effect Diagram • Also known as a Fishbone Diagram • Not widely used in SW development • Graphically relates causes and effects • Effect can be a positive or negative characteristic • Examples • Register Allocation Defects (negative) fig. 5.15 p. 148 • Effective Inspections (positive) fig 5.16 p. 149

16. Seven Basic Quality Tools Summary • Statistical tools (scientific methods) are used heavily in manufacturing, and are slowly being incorporated into SW engineering. • Some tools can be used together effectively: • Pareto Diagrams, Cause-Effect Diagrams, and Scatter Diagrams, can be used together to identify dominant problems and their root causes. • Control Charts can be used to monitor process stability.

17. Seven Basic Quality Tools Summary • Keys to a tool’s value: • Consistent use • Pervasive use • Automation • Integration • As a tool for process improvement

18. Seven Basic Quality Tools Summary • Ishikawa’s Tools a.k.a. “Seven Old Tools” • Other tools - “Seven New Tools” • Affinity Diagram • Relations Diagram • Tree Diagram • Metric Chart • Matrix Data Analysis Chart • Process Decision Program Chart • Arrow Diagram