- author = "Jose Carlos {Bregieiro Ribeiro} and Mario Alberto Zenha-Rela and Francisco {Fernandez de Vega}",
- title = "A strategy for evaluating feasible and unfeasible test cases for the evolutionary testing of object-oriented software",
- booktitle = "AST '08: Proceedings of the 3rd international workshop on Automation of software test",
- year = "2008",
- pages = "85--92",
- address = "Leipzig, Germany",
- publisher_address = "New York, NY, USA",
- publisher = "ACM",
- keywords = "genetic algorithms, genetic programming, SBSE, Search-Based Test Case Generation, Evolutionary Testing, Object-Orientation, Strongly-Typed Genetic Programming, Software Engineering, Testing and Debugging| Testing tools, Verification",
- isbn13 = "978-1-60558-030-2",
-
URL = "
http://jcbribeiro.googlepages.com/ast12-ribeiro.pdf",
-
DOI = "
doi:10.1145/1370042.1370061",
- size = "8 pages",
-
abstract = "Evolutionary Testing is an emerging methodology for
automatically producing high quality test data. The
focus of our on-going work is precisely on generating
test data for the structural unit-testing of
object-oriented Java programs. The primary objective is
that of efficiently guiding the search process towards
the definition of a test set that achieves full
structural coverage of the test object.
However, the state problem of object-oriented programs requires specifying carefully ne-tuned methodologies that promote the traversal of problematic structures and difficult controlflow paths - which often involves the generation of complex and intricate test cases, that dene elaborate state scenarios.
This paper proposes a methodology for evaluating the quality of both feasible and unfeasible test cases - i.e., those that are effectively completed and terminate with a call to the method under test, and those that abort prematurely because a runtime exception is thrown during test case execution. With our approach, unfeasible test cases are considered at certain stages of the evolutionary search, promoting diversity and enhancing the possibility of achieving full coverage.",
- notes = "also known as \cite{1370061}",
