Test Design & Analysis
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Systems are growing more complex and are developed at high stakes. With unprecedented complexity, effective test engineering plays an essential role in development. Student groups participate in a detailed practical exercise designed to demonstrate the application of testing tools and methods for system evaluation.
This three-day course is designed for military and commercial program managers, systems engineers,test project managers, test engineers, and test analysts. The focus of the course is giving individuals practical insights into how to acquire anduse data to make sound management and technical decisions in support of a development program. Numerous examples of test design or analysis “traps or pitfalls” are highlighted in class. Many design methods and analytic tools are introduced.
What You Will Learn:
- Concepts of test design and analysis
- Understanding the requirements
- How to know what criteria to use
- Designing effective use of statistics in data gathering
- How to conduct the test to get the right results.
- Evaluating the results vs. expected.
- The Nine Best Practices of T&E
- Testing and Evaluation. Basic concepts for testingand evaluation. Verification and validation concepts.Common T&E objectives. Types of Test. Context and relationships between T&E and systems engineering. T&E support to acquisition programs. The Test and Evaluation Master Plan (TEMP).
- Testability. What is testability? How is it achieved? What is Built in Test? What are the types of BIT and how are they applied?
- A Well Structured Testing and Evaluation Program. What are the elements of a well structuredtesting and evaluation program? How do the pieces fittogether? How does testing and evaluation fit into thelifecycle? What are the levels of testing?
- Needs and Requirements. Identifying the need for a test. The requirements envelope and how the edge of the envelope defines testing. Understanding the design structure. Stake holders, system, boundaries, motivation for a test. Design structure and how it affects the test.
- Issues, Criteria and Measures. Identifying the issues for a test. Evaluation planning techniques. Other sources of data. The Requirements Verification Matrix. Developing evaluation criteria: Measures of Effectiveness(MOE), Measures of Performance (MOP). Test planning an alysis: Operational analysis, engineering analysis, Matrix analysis, Dendritic analysis. Modeling and simulation for test planning.
- Designing Evaluations & Tests. Specific methods to design a test. Relationships of different units. Input/output analysis – where test variable come from, choosing what to measure, types of variables. Review of statistics and probability distributions. Statistical design oftests – basic types of statistical techniques, choosing the techniques, variability, assumptions and pitfalls. Sequencing test events – the low level tactics of planning the test procedure.
- Conducting Tests. Preparation for a test. Writing the report first to get the analysis methods in place. How to work with failure. Test preparation. Forms of the test report. Evaluating the test design. Determining when failure occurs.
- Evaluation. Analyzing test results. Comparing results to the criteria. Test results and their indications of performance. Types of test problems and how to solve them. Test failure analysis – analytic techniques to find fault. Test program documents. Pressed Funnels Case Study – How evaluation shows the path ahead.
- Testing and Evaluation Environments. 12 common testing and evaluation environments in a system lifecycle, what evaluation questions are answered in each environment and how the test equipment and processes differ from environment to environment.
- Special Types and Best Practices of T&E. Survey of special techniques and best practices. Specialtypes: Software testing, Design for testability, Combined testing, Evolutionary development, Human factors, Reliability testing, Environmental issues, Safety, Live fire testing, Interoperability. The Nine Best Practices of T&E.
- Emerging Opportunities and Issues with Testing and Evaluation. The use of prognosis and sense and respond logistics. Integration between testing and simulation. Large scale systems. Complexity in tested systems. Systems of Systems.
Dr. Scott Workinger has led projects in Manufacturing, Eng. & Construction, and Info. Tech. for 30 years. His projects have made contributions ranging from increasing optical fiber bandwidth to creating new CAD technology. He currently teaches courses on management and engineering and consults on strategic issues in management and technology. He holds a Ph.D. in Engineering from Stanford.
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