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Tuesday, April 30, 2013 - 1:00pm - 4:30pm
Half-day Tutorials

How to Actually DO High-volume Automated Testing

In high volume automated testing (HiVAT), the test tool generates the test, runs it, evaluates the results, and alerts a human to suspicious results that need further investigation. What makes it simple is its oracle—run the program until it crashes or fails in some other extremely obvious way. More powerful HiVAT approaches are more sensitive to more types of errors. They are particularly useful for testing combinations of many variables and for hunting hard-to-replicate bugs that involve timing or corruption of memory or data. Cem Kaner presents a new strategy for teaching HiVAT testing. Instead of describing what has been done, Cem is creating open source examples of the techniques applied to real (open source) applications. These examples are written in Ruby, making the code readable and reusable by snapping in code specific to your own application. Join Cem Kaner and Carol Oliver as they describe three HiVAT techniques, their associated code, and how you can customize them.

Cem Kaner, Florida Institute of Technology

Cem Kaner is a professor of software engineering at Florida Institute of Technology and director of FIT’s Center for Software Testing Education & Research. Cem teaches and researches in software engineering—software testing, software metrics, and computer law and ethics. In his career, he has studied and worked in areas of psychology, law, programming, testing, technical writing, sales, applying what he learned to the central problem of software satisfaction. Cem has done substantial work on the development of the law of software quality.

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Carol Oliver, Florida Institute of Technology

Carol Oliver is a doctoral student in the Center and leader of the HiVAT project. She has more than a decade of experience as a tester, most recently as Lead QA Analyst supporting infrastructure technology services at Stanford University. For most of her career, Carol has been the lone tester supporting more than a dozen database-driven middleware and web applications, all of which needed to cooperate with each other and several different infrastructure services simultaneously.

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