Model-Based Statistical Testing of a Cluster Utility

Abstract. As High Performance Computing becomes more collaborative, software certification practices are needed to quantify the credibility of shared applications. To demonstrate quantitative certification testing, Model-Based Statistical Testing (MBST) was applied to cexec, a cluster control utility developed in the Network and Cluster Computing Group of Oak Ridge National Laboratory. MBST involves generation of test cases from a usage model. The test results are then analyzed statistically to measure software reliability. The population of cexec uses was modeled in terms of input selection choices. The J Usage Model Builder Library (JUMBL) provided the capability to generate test cases directly as Python scripts. Additional Python functions and shell scripts were written to complete a test automation framework. The resulting certification capability employs two large test suites. One consists of “weighted” test cases to provide an intensive fault detection capability, while the o...

• Type: Conference
• Year: 2005
• Where: ICCS
• Authors: W. Thomas Swain, Stephen L. Scott
• Keywords: ICCS 2005, Random Test Cases, Test Cases, Usage Model