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» Genetic Algorithms for Randomized Unit Testing
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TSE
2011
144views more  TSE 2011»
12 years 11 months ago
Genetic Algorithms for Randomized Unit Testing
—Randomized testing is an effective method for testing software units. Thoroughness of randomized unit testing varies widely according to the settings of certain parameters, such...
James H. Andrews, Tim Menzies, Felix Chun Hang Li
KBSE
2007
IEEE
13 years 11 months ago
Nighthawk: a two-level genetic-random unit test data generator
Randomized testing has been shown to be an effective method for testing software units. However, the thoroughness of randomized unit testing varies widely according to the settin...
James H. Andrews, Felix Chun Hang Li, Tim Menzies
GECCO
2005
Springer
159views Optimization» more  GECCO 2005»
13 years 10 months ago
Using evolutionary algorithms for the unit testing of object-oriented software
As the paradigm of object orientation becomes more and more important for modern IT development projects, the demand for an automated test case generation to dynamically test obje...
Stefan Wappler, Frank Lammermann
GECCO
2006
Springer
213views Optimization» more  GECCO 2006»
13 years 8 months ago
Evolutionary unit testing of object-oriented software using strongly-typed genetic programming
Evolutionary algorithms have successfully been applied to software testing. Not only approaches that search for numeric test data for procedural test objects have been investigate...
Stefan Wappler, Joachim Wegener
KBSE
1997
IEEE
13 years 9 months ago
Genetic Algorithms for Dynamic Test Data Generation
In software testing, it is often desirable to find test inputs that exercise specific program features. To find these inputs by hand is extremely time-consuming, especially whe...
Christoph C. Michael, Gary McGraw, Michael Schatz,...