Learning to Prioritize Test Cases for Computer Aided Design Software via Quantifying Functional Units

Computer Aided Design (CAD) is a family of techniques that support the automation of designing and drafting 2D and 3D models with computer programs. CAD software is a software platform that provides the process from designing to modeling, such as AutoCAD or FreeCAD. Due to complex functions, the qua...

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Bibliographic Details
Published in:Applied sciences 2022-10, Vol.12 (20), p.10414
Main Authors: Zeng, Fenfang, Liu, Shaoting, Yang, Feng, Xu, Yisen, Zhou, Guofu, Xuan, Jifeng
Format: Article
Language:English
Subjects:
Automation
CAD
CAD software
Computer aided design
Computer aided testing
Computer programs
Drafting software
feature engineering
manufacturing software
Model testing
Software
Software development
Software quality
Software testing
Software upgrading
test case prioritization
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Summary:Computer Aided Design (CAD) is a family of techniques that support the automation of designing and drafting 2D and 3D models with computer programs. CAD software is a software platform that provides the process from designing to modeling, such as AutoCAD or FreeCAD. Due to complex functions, the quality of CAD software plays an important role in designing reliable 2D and 3D models. There are many dependencies between defects in CAD software. Software testing is a practical way to detect defects in CAD software development. However, it is expensive to frequently run all the test cases for all functions. In this paper, we design an approach to learning to prioritize test cases for the CAD software, called PriorCadTest. The key idea of this approach is to quantify functional units and to train a learnable model to prioritize test cases. The output of the approach is a sequence of existing test cases. We evaluate PriorCadTest on seven modules of an open-source real-world CAD project, ArtOfIllusion. The Average Percentage of Fault Detect (APFD) is used to measure the effectiveness. Experimental results show that the proposed approach outperforms the current industrial practice without test case prioritization.
ISSN:2076-3417
2076-3417
DOI:10.3390/app122010414