Researchers work to provide faster, more effcient software for Air Force Published Jan. 27, 2010 By Maria Callier Air Force Office of Scientific Research ARLINGTON, Va. (AFNS) -- Researchers at the University of Nebraska-Lincoln are working to increase the efficiency of the software-testing process across Air Force systems by addressing the issue of faulty software. A recent breakthrough in the work of lead researcher Dr. Myra Cohen and her team has resulted in an algorithm 300 times faster at generating tests. The project, funded in part by an Air Force Office of Scientific Research Young Investigator Award and through a National Science Foundation Early CAREER Award, is of particular interest to the military because of the potential to reduce errors in theater. This technology also will be helpful to the private sector where some agencies are reporting financial losses of up to $50 billion per year because of poor software. "Software failures have the potential to cause financial, environmental or bodily harm," said Doctor Cohen. "Our techniques will help to improve the quality of software in the military to help ensure that those systems behave properly in the field." Her project, called "Just Enough Testing," aims to re-use test results across different systems that share similar sets of features so the time to test a single system is reduced "The ultimate goal of research like this is not just to reduce software testing costs, but to do so while maintaining or even increasing confidence in the tests themselves," said AFOSR Program Manager Dr. David Luginbuhl, who is overseeing Doctor Cohen's work. Large and complex families of software systems are common, and within them, groups of interacting features may cause faults to occur. The scientists have examined ways to ensure that faults are found earlier and more often in these types of systems. "Although algorithms exist that can produce samples for testing, few can handle dependencies between features," Doctor Cohen said. "Either they run slowly or they select very large test schedules, which means that testing takes too long." Doctor Cohen expects that as the product lines are used to produce large numbers of systems, it will be possible to deploy newer ones at a faster rate and with less chance of failure.