Shrinking a Database to Perform SQL Mutation Tests Using an Evolutionary Algorithm

被引：0

作者：

Loureiro Moncao, Ana Claudia B. ^{[1
]}

Camilo-Junior, Celso G. ^{[1
]}

Queiroz, Leonardo T. ^{[1
]}

Rodrigues, Cassio L. ^{[1
]}

Sa Leitao-Junior, Plinio de ^{[1
]}

Vincenzi, Auri M. R. ^{[1
]}

机构：

[1] Univ Fed Goias, Inst Informat, Goiania, Go, Brazil

来源：

2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2013年

关键词：

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper tries to combine SQL mutation testing techniques with evolutionary computation aiming to improve the test data to SQL instructions. Based on a heuristic perspective it presents an approach that uses Genetic Algorithms (GA) to select tuples from an original database trying to reduce this one in an effective data set. The goal is to find a reduced data set which is able to detect a large number of faults in the SQL instructions of a given application. During the evolutionary process, the analysis of mutants is used to assess each set of data test selected by GA. The results obtained from experiments reveal a good performance using GA metaheuristic.

引用

页码：2533 / 2539

页数：7

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