Introduction - If you have any usage issues, please Google them yourself
In a unit test of software testing, you need to find test data (function parameter values) that satisfy a certain coverage, such as branching coverage, to determine whether the measured function is buggy. The source program USES the global optimization feature of genetic algorithm to realize the automatic generation of test data without manual input parameter value. The test function in the program USES trigonometric functions. The source code USES c ++ to realize GA's optimization process, and annotate the necessary comments, and the results can be solved very quickly.
Packet : 89346517sga_for_testing.rar filelist
SGA for testing\CProgramTested.cpp
SGA for testing\CProgramTested.h
SGA for testing\Debug
SGA for testing\Inputvalue.cpp
SGA for testing\Inputvalue.h
SGA for testing\ReadMe.txt
SGA for testing\Resource.h
SGA for testing\SGA for testing.aps
SGA for testing\SGA for testing.clw
SGA for testing\SGA for testing.cpp
SGA for testing\SGA for testing.dsp
SGA for testing\SGA for testing.dsw
SGA for testing\SGA for testing.h
SGA for testing\SGA for testing.ncb
SGA for testing\SGA for testing.opt
SGA for testing\SGA for testing.plg
SGA for testing\SGA for testing.rc
SGA for testing\SGAlib.cpp
SGA for testing\SGAlib.h
SGA for testing\StdAfx.cpp
SGA for testing\StdAfx.h
SGA for testing\testing SGA Optimizer.txt
SGA for testing\Triangle.cpp
SGA for testing\Triangle.h
SGA for testing\分支全面覆盖数据.txt
SGA for testing\分支全面覆盖数据2.txt
SGA for testing\分支全面覆盖数据3.txt
SGA for testing\没有产生分支全面覆盖的数据.txt
SGA for testing