An Extended Algorithm using a Divide-and-Rule Approach for Boundary Value Analysis and Equivalence Class Partitioning

An extended algorithm using a divide-and-rule approach is proposed in this paper. Instead of generating test cases by only using Boundary Value Analysis and an experience-based technique for combination of input variables with functional dependency like the original algorithm, the extended algorithm applies both Boundary Value Analysis and Equivalence Class Partitioning techniques as well as various techniques for combination of input values. In addition, a new tool provides advantages when compared with the original tool. It provides users with more choices in generating test cases.

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Publication Details

Journal
Journal on Information Technologies & Communications
Published
2024-10-11
DOI
https://doi.org/10.32913/mic-ict-research-vn.v2024.n3.1311
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

An Extended Algorithm using a Divide-and-Rule Approach for Boundary Value Analysis and Equivalence Class Partitioning

Cong Danh Nguyen
Journal on Information Technologies & Communications
Industrial Vision Systems and Defect Detection
article

An Extended Algorithm using a Divide-and-Rule Approach for Boundary Value Analysis and Equivalence Class Partitioning

Cong Danh Nguyen
article en

Abstract

An extended algorithm using a divide-and-rule approach is proposed in this paper. Instead of generating test cases by only using Boundary Value Analysis and an experience-based technique for combination of input variables with functional dependency like the original algorithm, the extended algorithm applies both Boundary Value Analysis and Equivalence Class Partitioning techniques as well as various techniques for combination of input values. In addition, a new tool provides advantages when compared with the original tool. It provides users with more choices in generating test cases.

Journal on Information Technologies & Communications
Can Tho University (VN)
Openalex Percentile: Top 74%
Industrial Vision Systems and Defect Detection
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