Talks and Poster Presentations (with Proceedings-Entry):

K. Meixner, D. Winkler, S. Biffl:
"Supporting Domain Experts by using Model-Based Equivalence Class Partitioning for Efficient Test Data Generation";
Talk: 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2019), Zaragoza, Spain; 2019-09-10 - 2019-09-13; in: "Proceedings of the 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2019)", IEEE, (2019), ISBN: 978-1-7281-0304-4.

English abstract:
Production Systems Engineering (PSE)
faces a growing complexity of software, i.a., due to increasing
capabilities of the hardware, requiring efficient approaches for
designing test data and test cases. Apart from this, for longrunning legacy systems where often no tests are available
tests need to be added belatedly during system maintenance.
Equivalence Class Partitioning (ECP) can help to systematically
cluster test input and result data as a foundation for test case
definition. However, different tools and technologies in PSE often
hinder the precise definition and creation of Equivalence Classes
(EC) based on the existing source code. Objective. In this paper,
we present a model-based approach for deriving ECs based on
abstract representations of existing source code and evaluate the
approach in a real-world industry use case. Method. We build
on best-practices from software testing for developing a modelbased approach for deriving ECs as a foundation for test data
and test case generation and on the Abstract Syntax Tree (AST)
to describe the structure of the underlying source code. Results.
First results were promising in the evaluation use case to improve
test activities by systematically deriving test data and test cases
based on ECs. Conclusions. We observed additional benefits, such
as increased test coverage and capabilities for testing error cases.

Production Systems Engineering, Model-based Testing, Software Testing, Equivalence Class, Abstract Code Representation

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.