Since controller applications must typically satisfy real-time constraints while manipulating real-world variables, their implementation often results in programs that run ex-tremely fast and manipulate numerical inputs and outputs. These characteristics make them particularly suitable for test case generation. In fact a number of test cases can be easily created, due to the simplicity of numerical inputs, and executed, due to the speed of computations. In this paper we present G-RankTest, a technique for test case generation and prioritization. The key idea is that test case generation can run for long sessions (e.g., days) to accurately sample the behavior of a controller application and then the generated test cases can be prioritized according to different strategies, and used for regression testing every time the application is modified. In this work we investigate the feasibility of using the gradient of the output as a criterion for selecting the test cases that activate the most tricky behaviors, which we expect easier to break when a change occurs, and thus deserve priority in regression testing.
Mariani, L., Riganelli, O., Santoro, M., Ali, M. (2012). G-RankTest: Regression Testing of Controller Applications. In Proceedings of the 7th International Workshop on Automation of Software Test (AST) (pp.131-137). IEEE [10.1109/IWAST.2012.6228981].
G-RankTest: Regression Testing of Controller Applications
MARIANI, LEONARDO;RIGANELLI, OLIVIERO;SANTORO, MAURO;
2012
Abstract
Since controller applications must typically satisfy real-time constraints while manipulating real-world variables, their implementation often results in programs that run ex-tremely fast and manipulate numerical inputs and outputs. These characteristics make them particularly suitable for test case generation. In fact a number of test cases can be easily created, due to the simplicity of numerical inputs, and executed, due to the speed of computations. In this paper we present G-RankTest, a technique for test case generation and prioritization. The key idea is that test case generation can run for long sessions (e.g., days) to accurately sample the behavior of a controller application and then the generated test cases can be prioritized according to different strategies, and used for regression testing every time the application is modified. In this work we investigate the feasibility of using the gradient of the output as a criterion for selecting the test cases that activate the most tricky behaviors, which we expect easier to break when a change occurs, and thus deserve priority in regression testing.File | Dimensione | Formato | |
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