Abstract:
The notation of state machines is widely adopted as a
formalism to describe the behaviour of systems. Usually, multiple state machine
models can be developed for the very same software system.
Some of these models might turn out to be equivalent, but, in many cases,
different state machines describing the same system also differ in their level
of abstraction.
In this paper, we present an approach to actually measure the abstractness
level of state machines w.r.t. a given implemented software system. A state
machine is considered to be less abstract when it is conceptionally closer to
the implemented system. In our approach, this distance between state machine and
implementation is measured by applying coverage criteria known from software
mutation testing.
Abstractness of state machines can be considered as a new metric. As for other
metrics as well, a known value for the abstractness of a given state machine
allows to assess its quality in terms of a simple number.
In model-based software development projects, the abstract metric can help to
prevent model degradation since it can actually measure the semantic distance from the
behavioural specification of a system in form of a state machine to the current
implementation of the system.
In contrast to other metrics for state machines, the abstractness cannot be
statically computed based on the state machine's structure, but requires to execute
both state machine and corresponding system implementation.
The article is published in the author’s wording.
Keywords:model-based software development, metric, state machine, mutation testing.
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