An effective selective assembly model for spinning shells based on the improved genetic simulated annealing algorithm (IGSAA)

2022 ◽  
Author(s):  
Hu Zhou ◽  
Qiwei Zhang ◽  
Chongjun Wu ◽  
Zhen You ◽  
Yao Liu ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Assembly Model ◽  
Selective Assembly ◽  
Genetic Simulated Annealing Algorithm ◽  
Annealing Algorithm

scholarly journals Fault Localization Based on Hybrid Genetic Simulated Annealing Algorithm

2021 ◽  
Vol 28 (2) ◽  
pp. 101-109
Keyword(s):  
Simulated Annealing ◽  
Software Testing ◽  
Simulated Annealing Algorithm ◽  
Search Algorithm ◽  
Fault Localization ◽  
Good Effect ◽  
Test Case ◽  
Genetic Simulated Annealing Algorithm ◽  
Starting Point ◽  
Annealing Algorithm

Software testing is an important stage in the software development process, which is the key to ensure software quality and improve software reliability. Software fault localization is the most important part of software testing. In this paper, the fault localization problem is modeled as a combinatorial optimization problem, using the function call path as a starting point. A heuristic search algorithm based on hybrid genetic simulated annealing algorithm is used to locate software defects. Experimental results show that the fault localization method, which combines genetic algorithm, simulated annealing algorithm and function correlation analysis method, has a good effect on single fault localization and multi-fault localization. It greatly reduces the requirement of test case coverage and the burden of the testers, and improves the effect of fault localization.

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