DocumentCode
1688413
Title
An Approach to Regression Test Selection of Adaptive EFSM Tests
Author
Guo, Bo ; Subramaniam, Mahadevan ; Guo, Hai-Feng
Author_Institution
Comput. Sci. Dept., Univ. of Nebraska-Omaha, Omaha, NE, USA
fYear
2011
Firstpage
217
Lastpage
220
Abstract
A formal approach to automatically building a regression test suite whose tests are guaranteed to exercise a given set of system changes is proposed. Given a test and a change, the approach analyzes the test description to provably predict whether or not the test will exercise the change. Adaptive tests whose descriptions involve multiple control paths and support values over commonly used data types are considered. We introduce fully-observable adaptive tests whose descriptions contain all the relevant information about their executions. A structural invariant generated from a test description identifies fully-observable tests and is used to develop a procedure to automatically select tests exercising changes.
Keywords
finite state machines; regression analysis; adaptive EFSM test; extended finite state machines; fully-observable adaptive test; regression test selection; Adaptation models; Adaptive systems; Concrete; Distance measurement; Educational institutions; Impedance matching; Testing; Extended Finite State Machines; Regression Test Selection; Theorem Proving;
fLanguage
English
Publisher
ieee
Conference_Titel
Theoretical Aspects of Software Engineering (TASE), 2011 Fifth International Symposium on
Conference_Location
Xi´an, Shaanxi
Print_ISBN
978-1-4577-1487-0
Type
conf
DOI
10.1109/TASE.2011.39
Filename
6042082
Link To Document