Enhancing Genetic Algorithm with Cumulative Probabilities to Derive Critical Test Scenarios from Use-Cases

2014 ◽  
pp. 286-299
Author(s):  
An T. Tran ◽  
Tho T. Quan ◽  
Thuan D. Le
Keyword(s):  
Genetic Algorithm ◽  
Use Cases ◽  
Critical Test ◽  
Test Scenarios ◽  
Cumulative Probabilities

scholarly journals A Test Cases Generation Method for Industrial Control Protocol Test

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Wenli Shang ◽  
Guanyu Zhang ◽  
Tianyu Wang ◽  
Rui Zhang
Keyword(s):  
Genetic Algorithm ◽  
Use Cases ◽  
Test Cases ◽  
Industrial Control ◽  
Important Indicator ◽  
Fitness Functions ◽  
Modbus Protocol ◽  
Dispersion Degree ◽  
Important Research Topic ◽  
Population Dispersion

The coverage of test cases is an important indicator for the security and robustness test of industrial control protocols. It is an important research topic to complete the test with less use cases. Taking Modbus protocol as an example, a calculation method of case similarity and population dispersion based on weight division is proposed in this paper. The method can describe the similarity of use cases and the dispersion degree of individuals in the population more accurately. Genetic algorithm is used to generate and optimize test cases, and individual similarity and population dispersion are used as fitness functions of genetic algorithm. Experimental results show that the proposed method can increase the population dispersion by 3.45% compared with the conventional methods and effectively improve the coverage of test cases.

A Method of Testing Generation Based on Prioritized Pair

2012 ◽  
Vol 241-244 ◽  
pp. 2696-2700
Author(s):  
Yu Wang ◽  
Hao Wu ◽  
Zhen Yu Sheng
Keyword(s):  
Genetic Algorithm ◽  
Detection Rate ◽  
Test Methods ◽  
Limited Resources ◽  
Test Case ◽  
Test Cases ◽  
Test Coverage ◽  
Combinatorial Testing ◽  
Critical Test ◽  
Generate Pair

Combinatorial testing has lots of test cases, but software testers hope to get the best test coverage with the smallest test case suite. For the scale of produced test cases is so large that researchers have considered the implementation of the critical test cases. This article researches the classic combinatorial test methods and proposes methods to generate pair-wise testing cases with a priority. Firstly, we design formulas to compute the weights of priorities. Secondly, we adopt a greed algorithm to solve the combinatorial testing problems. Furthermore, we integrate the greed strategy into a genetic algorithm to improve the efficiency. It improves the testing efficiency while securing the detection rate of defects under limited resources.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
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