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Measuring the "Good" in "Good Enough Testing" The theory of "good enough" software requires determining the trade off between delivery date (schedule), absence of defects (quality), and feature richness (functionality) to achieve a product which can meet both the customer's
needs and the organization's expectations. This may not be the best approach for pacemakers and commercial avionics software, but it is appropriate for many commercial products. But can we quantify these factors? Gregory Pope
does. Using the COQALMOII model, Halstead metrics, and defect seeding to predict defect insertion and removal rates; the Musa/Everette model to predict reliability; and MatLab for verifying functional equivalence testing, Greg
evaluates both quality and functionality against schedule.
- Review how to measure test coverage
- Discover the use of models to predict quality
- Learn what questions you should ask customers to determine "good enough"
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Gregory Pope, Lawrence Livermore National Laboratory
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Peanuts and Crackerjacks: What Baseball Taught Me about Metrics Because people can easily relate to a familiar paradigm, analogies are an excellent way to communicate complex data. Rob Sabourin uses baseball as an analogy to set up a series of status reports to manage test projects, share results with stakeholders, and measure test effectiveness. For
test status, different audiences-test engineers, test leads and managers, development managers, customers, and senior management-need different information, different levels of detail, and different ways of looking at data. So, what "stats" would you put on the back of Testing Bubble Gum
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Robert Sabourin, AmiBug.com Inc
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Achieving Meaningful Metrics from Your Test Automation Tools In addition to the efficiency improvements you expect from automated testing tools, you can-and should-expect them to provide valuable metrics to help manage your testing effort. By exploiting the programmability of automation tools, you can support the measurement and reporting aspects of your department. Learn how Jack Frank employs these tools with minimal effort to create test execution
status reports, coverage metrics, and other key management reports. Learn what measurement data your automation tool needs to log for later reporting. See examples of the operational reports his automation tools generate, including run/re-run/not run, pass/fail, percent complete, and percent of overall system tested. Take with you examples of senior management reports, including Jack's favorite, "My Bosses' Boss Test Status Report"-names will be changed to hide the guilty. Regardless of the
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Jack Frank, Mosaic Inc
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A Small Matter of Metrics Think you’re ready to launch your new metrics program? Think again. Find out how conducting a trial measurement program on yourself first can give you valuable insights and understanding. Learn about the value and limits of measurement, gain knowledge into why many software measurement efforts fail, and prepare yourself for launching a successful program.
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Guerilla Software Metrics: Leaving the Developers Alone This presentation describes an approach to initiating and conducting a metrics program that takes advantage of existing measurement/tracking infrastructure without adding significant extra tasks and reporting responsibilities. Scott Duncan identifies three areas where measurement data may already exist. Learn how to work with management and staff in these areas to make use of the data being collected.
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Scott Duncan, SoftQual Consulting
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A Metrics Dashboard for IT Project Reporting Tom Olenick described the activities performed to design, develop, deploy, and maintain a Project Management Metrics Dashboard across the IT organization of a major Chicago-based securities organization. Learn how this metrics dashboard was used to facilitate project status tracking for IT management and to provide a basis for improving the efficiencies of software development activities and estimation.
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Thomas Olenick, Olenick & Associates
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