A Mutation Analysis Based Model Clone Detector Evaluation Framework
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Authors
Stephan, Matthew
Date
2014-08-25
Type
thesis
Language
eng
Keyword
Software Engineering , Model Clone Detection , Tool Evaluation , Model Driven Engineering
Alternative Title
Abstract
Model-Driven Engineering is becoming increasingly prevalent and mature. As
software projects developed through this methodology age, the need for analysis
of Model-Driven projects becomes imperative. One form of analysis is Model Clone
Detection, which involves finding similar or identical model fragments in a
given context. There are a number of techniques intended for Model Clone
Detection and for different types of models.
One hindrance to the growth of this field is the ability to objectively and
quantitatively compare different model clone detectors and settings of the same
detector.
In this thesis, our original contribution to knowledge includes a framework
utilizing Mutation Analysis to evaluate and compare model clone detectors. It
is our proposition that, through distinguishing edit operations on models as
mutations, we can create such a framework. In order to demonstrate the
plausibility of our framework, we develop a Simulink implementation of the
framework.
We begin by outlining our initial, qualitative, attempts evaluating our
Simulink model clone detector. This includes challenges encountered
that are addressed by our framework. We outline the framework and describe each
step in its process in an example-driven manner through creation of a framework
prototype that works on Simulink model clone detectors. We choose Simulink
because it is the most mature form of Model Clone Detection, it is of interest
to our industrial partners, and we previously created a Simulink model clone
detector. An additional contribution is a taxonomy of Simulink model mutations
intended to inject the various types of model clones, while still being
representative of realistic Simulink model evolution, which we verify through a
case study. We run our Simulink framework prototype on leading Simulink clone
detectors to ascertain their recall and precision. We observe high recall for
Simone, lower recall for ConQAT because it is intended for only a subset of
clone types, and high precision for both tools.
It is our hope that having such a framework in place will help facilitate gains
in Model Clone Detection research as engineers in this area can now refine their
own tools and new detectors can be compared against existing ones.
Description
Thesis (Ph.D, Computing) -- Queen's University, 2014-08-25 15:17:07.971
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