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Functional Dependency Detection for Integration Test Cases
Publication Type:
Conference/Workshop Paper
Venue:
The 18th IEEE International Conference on Software Quality, Reliability and Security
Abstract
This paper presents a natural language processing
(NLP) based approach that, given software requirements specification,
allows the functional dependency detection between
integration test cases. We analyze a set of internal signals to
the implemented modules for detecting dependencies between
requirements and thereby identifying dependencies between
test cases such that: module 2 depends on module 1 if an output
internal signal from module 1 enters as an input internal signal
to the module 2. Consequently, all requirements (and thereby
test cases) for module 2 are dependent on all the designed
requirements (and test cases) for module 1. The dependency
information between requirements (and thus corresponding
test cases) can be utilized for test case selection and prioritization.
We have implemented our approach as a tool and the
feasibility is evaluated through an industrial use case in the
railway domain at Bombardier Transportation, Sweden.
Bibtex
@inproceedings{Tahvili5143,
author = {Sahar Tahvili and Marcus Ahlberg and Eric Fornander and Wasif Afzal and Mehrdad Saadatmand and Markus Bohlin and Mahdi Sarabi},
title = {Functional Dependency Detection for Integration Test Cases},
month = {July},
year = {2018},
booktitle = {The 18th IEEE International Conference on Software Quality, Reliability and Security },
url = {http://www.es.mdu.se/publications/5143-}
}