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Functional Dependency Detection for Integration Test Cases



Sahar Tahvili, Marcus Ahlberg , Eric Fornander , Wasif Afzal, Mehrdad Saadatmand, Markus Bohlin, Mahdi Sarabi

Publication Type:

Conference/Workshop Paper


The 18th IEEE International Conference on Software Quality, Reliability and Security


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.


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 = {}