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Combinatorial Software Testing

“Combinatorial testing can detect hard-to-find software faults more efficiently than manual test case selection methods.”

Developers of large data-intensive software often notice an interesting—though not surprising—phenomenon: When usage of an application jumps dramatically, components that have operated for months without trouble suddenly develop previously undetected errors. For example, newly added customers may have account records with an oddball combination of values that have not been seen before. Some of these rare combinations trigger faults that have escaped previous testing and extensive use. Alternatively, the application may have been installed on a different OS-hardware-DBMS-networking platform. Combinatorial testing can help detect problems like this early in the testing life cycle. The key insight underlying t-way combinatorial testing is that not every parameter contributes to every fault and many faults are caused by interactions between a relatively small number of parameters.

An Interview with Computer Scientist – D. Richard Kuhn about applications development of combinatorial research.

D. Richard Kuhn - Computer Scientist, National Institute of Standards & Technology

LogiGear: How did you become interested in developing applications for combinatorial research? What led you to it personally, and what did you find fascinating about it?

Mr. Kuhn: About 12 years ago Dolores Wallace and I were investigating causes of software failures in medical devices. About that time, Raghu Kacker in our math division introduced me to some work on the design of experiments and testing, which had been done by a colleague of his at Bell Labs. The idea behind these methods was that some failures only occur as a result of an interaction between components. For example, a system may correctly produce error messages when space is exhausted or when input rate exceeds some limit, but crashes only when these two conditions are both true at the same time. Pairwise testing has been used for a long time to catch this sort of problem.

Computer Scientist – D. Richard Kuhn will provide some insights on how to become a software tester and shares his interest in combinatorial testing.

D. Richard Kuhn - Computer Scientist, National Institute of Standards & Technology

LogiGear: How did you get into software testing? What did you find interesting about it?

Mr. Kuhn: About 10 years ago Dolores Wallace and I were investigating the causes of software failures in medical devices, using 15 years of data from the FDA. About that time, Raghu Kacker, in NIST’s math division, introduced me to some work that his colleague at Bell Labs, Sid Dalal, had done on pairwise and interaction testing for software. The idea behind these methods is that some failures only occur as a result of interaction between some components. For example, a system may correctly produce error messages when file space is exhausted or user input exceeds some limit, but crashes only when these two conditions are both true at the same time.

Professor Jeff Offutt provides some insight to LogiGear Magazine on how to become a software tester

Professor Jeff OffuttJeff Offutt – Professor of Software Engineering in the Volgenau School of Information Technology at George Mason University – homepage – and editor-in-chief of Wiley’s journal of Software Testing, Verification and Reliability,

LogiGear: How did you get into software testing? What do you find interesting about it?

Professor Offutt:
When I started college I didn’t know anything about computers. I was a math major and in my first semester, my adviser convinced me to take an introductory programming course that was being specialized for math majors. Programming was taught in the business department, so a math-focused class was quite different and the faculty wanted to make sure enough students took it.