Improved Software Testing With The Use Of Metrics
(CSTP elective)
Alfred Sorkowitz
This tutorial counts as one day of training towards the Certified Software Test Professional requirements.

Course Description

Software Metrics can aid in improving your organizations Testing Process by (1) providing insight and early visibility into the "real" status of the testing effort, and (2) aid in making assessments as to whether progress, productivity and quality goals are being met. This tutorial presents a practical guide on how to start taking advantage of these new tools/techniques to aid in improving the testing process. These metric based tools and techniques have successfully been used by (1) software test teams, (2) software developers and, (3) SQA/IV&V staffs.

What you will learn:

• An overview of Software Quality Goals, Criteria and Metrics
• A set of government/industry "best practices" metrics with numerous examples, variations, and case studies. These metrics can track the "real status", quality, and productivity of the testing effort, as well as provide an indication of future problems
• Software Complexity Metrics: A new Structured Testing methodology that uses metrics to aid in (1) developing software that is easier to test and maintain, and (2) selecting an appropriate set of paths for more thorough testing
• Testing: An overview of testing concepts and principles. This includes a metrics-based testing procedure that can aid in improving the quality of unit testing
• How to integrate software metrics into the testing process

Audience

A practical overview of metrics-based testing designed for technical and managerial professionals concerned with improving quality, performance, and productivity of software testing.

This tutorial is designed for Intermediate/advanced level professionals.

Improved Software Testing with the Use of Metrics

Section One

Introduction

An introduction to software testing, and the use of selected metrics. This section will also cover the following topics:

• The Cost of Inadequate S/W Testing
• Crises-Driven Development
• Software Growth
• Problems due to Growth in Size
• How S/W Metrics can aid in Testing

Section Two

Testing and Metrics

A number of recent studies have shown that the various testing phases can account for up to 50% of the total resources spent for developing a software system. In spite of this large investment, little systematic attention has been paid to this phase of the software life cycle. This section will cover the following topics:

• High cost of testing
• What is testing ?
• Problems in testing
• How much testing is enough
• Use of automatic tools to increase the quality of testing
• A metrics-based testing procedure, to increase the quality of unit testing, that is easy to implement, and works
• A review of testing principles and good practices

Section Three

Software Metrics

This section will cover a set of "best practices" metrics with numerous examples and variations, that can be utilized in the Software Testing phase. You will learn how to set-up, use, and analyze these metrics. A number of real-life Case Studies, will cover the analysis of scenarios utilizing a combination of metrics, their interactions, as well as corrective action.

• Software Quality Goals, Criteria and Metrics
• CSU (Unit Testing) Progress Metrics
• Depth of Testing Metrics
• Branch/Statement Testing Coverage
• System Testing Progress metrics
• Fault Tracking Metrics
• Defect Containment Metrics
• S/W Size
• Test Team Personnel Metrics
• Software measurement principles
• Measurement guidelines
• SEI Core Metrics
• Case Studies

Section Four

Software Complexity Metrics

A major problem in software development is the creation of highly complex designs that are difficult to understand, and therefore costly to test and maintain. This section will discuss McCabes Complexity Metric, and a practical application of how it can be used to simply complexity that can result in appreciable savings in testing and maintenance costs.

• Software Complexity
• McCabes Complexity Metric
• Drawing a Flowgraph
• Computation of McCabes Metrics
• Properties of a Complexity Metric
• Using McCabes metric for identifying program paths for testing

Appendix A: Bibliography