Qualitative and Quantitative Assessment of Integration Testing for Model-Based Software in the Automotive Industry
Abstract
Background: Integration testing of vehicle software in the automotive industry
relies heavily on simulation models. As they replicate actual vehicle functions
in the testing process, they increase in size and amount of interconnectivity as
rapidly as the actual functions. Valid simulation models are a precondition for
valid integration testing. Hence, assessment of the models is of high importance
in industry. At the same time, assessment approaches for model-based software
validated in industry are scarce.
Objective: The goal of this thesis is to assess current integration testing in the
automotive industry and extend the validation of simulation models. Accordingly,
we aim to collect insights from the practitioners in the eld, including
elicitation of actual challenges in the industry, state-of-the-practice processes,
and assessments of applicability for validation approaches.
Method: To achieve the objectives we combine quantitative and qualitative
research methods including interviews, workshops, surveys, literature reviews,
software measurements, correlation analysis, and statistical tests. In ve studies
attached with this thesis we combine multiple research methods to achieve high
validity and to ensure all presented approaches are applicable in industry.
Results: We elicited and categorized challenges from practitioners in practice,
particularly in the eld of integration testing for automotive software and
analyze the current software development process. We present measurement
results from complexity and size metrics, as a rst assessment of the models.
In addition to single measurements, we show how to evaluate software measurement
results collected over time and how they can be related to model quality.
We show that outlier analysis can help detecting impactful observations in the
model development process. Furthermore, we found ve approaches for the
prediction of software model growth data and elaborate on their strengths and
weaknesses, in practice. Next to providing actual approaches, we present practitioners
expectations towards maintainability measurements and measurement
predictions.
Conclusion: In this work we contribute to the understanding of concrete
challenges in industry, we describe current processes, and provide approaches
applicable in industry to address elicited challenges. With our work we improve
the current assessment of validity of simulation models in integration testing
in the automotive industry.
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Date
2016Author
Schröder, Jan
Keywords
Software Engineering
Industrial Case Studies
Empirical Research
Validation
Software Quality
Technical debt
Software Metrics
Maintainability
Publication type
licentiate thesis
Series/Report no.
Technical Report No.
139D
Language
eng