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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Approach to Systematic Test Signal Definition for Operation Scenarios of Aircraft Systems</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>1st Dennis Hillig</string-name>
          <email>Dennis.Hillig@tuhh.de</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>2nd Frank Thielecke</string-name>
          <email>Frank.Thielecke@tuhh.de</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Institute of Aircraft Systems Engineering, Hamburg University of Technology (TUHH)</institution>
          ,
          <addr-line>Hamburg</addr-line>
          ,
          <country country="DE">Germany</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>-With rapidly increasing levels of automation, modern aircraft systems become increasingly complex. The designed solutions typically achieve multiple functions by using a highly integrated mix of hardware and software components. With regard to automation, particularly the number of software components increases. For verification and validation activities, such as testing, this intensifies the challenge to define all relevant scenarios to test a system's functionalities and particularly its robustness in the case of unusual, but realistic situations. Hidden failure cases might be missed. Additionally, it becomes infeasible to systematically define the test vectors to study a systems behavior thoroughly due to the immense test space. As a consequence, testing gets more workand time-intensive. This paper presents a stepwise model-based method to define and refine the stimulating part of the test scenarios in a systematic and modular manner to approach this challenge. The aim is to work out diverse and relevant operational scenarios to validate system functions and to set up realistic test vectors for these scenarios. The paper further focuses on the aim to facilitate automation and re-usability of scenario and functional signal elements to enable continuous testing at different stages of the development process. Concepts of a developed prototype are outlined as well. Finally, the current state of the method is discussed and an overview of the way forward is given. Index Terms-scenario testing, aircraft systems, test design</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>I. INTRODUCTION</title>
      <p>In recent years new digital and smart embedded system
solutions emerged at a very rapid pace. Such solutions are
increasingly used to optimize novel aerospace systems, which
integrate mechanical, mechatronical and software components,
through automation. However, the more capabilities and
functions these integrated intelligent solutions implement, the more
apparent the need becomes for new verification and validation
(V&amp;V) methods, that can handle the complexity. In particular
for safety-critical systems this is crucial. In that context,
classical approaches for the examination of system’s integrated
functions and safety, which rely significantly on manual testing
and expertise, are a limiting factor to new developments.
Testing in general is the mainly used V&amp;V method.
Scenariobased testing more specifically is one technique to assess
the operational, functional behavior at system and overall
aircraft level. Scenario-like analyses of technical systems are
also commonly used for demonstrations of functionality in
an operational context. Yet, two main challenges can be
identified, when the system complexity rises. Firstly, it
becomes difficult to find the relevant scenarios or operational
conditions. Secondly, the implementation of the realistic test
vectors complicates significantly.</p>
      <p>
        In order to approach this challenge for aircraft systems, a
methodical procedure for a structured and model-based scenario
definition was developed at the Institute of Aircraft Systems
Engineering of the Hamburg University of Technology. It
is intended to cope with the system’s complexity through
the main ideas of modularisation and hierarchical refinement.
The contribution is embedded into the activities to develop a
seamless avionics tool chain (s. [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]).
      </p>
      <p>The aim of the developed method is clarified with an example
use case of an air conditioning system in the following. Figure
1 shows an overview of the system under test (SUT) and
some interfacing elements, such as the aircraft’s environment
conditions, cabin loads and cockpit commands from the
overhead panel. The system is modeled in an open-loop manner
w.r.t. the interfacing elements. The actions of these interfacing
elements should be explicitly integrated in the scenario
definition. Given that the physical system was designed with a
representation as a physical model, and the control and monitor
(C&amp;M) functions (e.g. pressure control) were designed and
implemented, the scenario-based test has the following two
objectives: On one hand, the system hardware design should be
verified, e.g. in terms of sizing and functionality. On the other
hand, the software functions should be validated under realistic
operational scenario conditions. To achieve that, realistic input
signals or models of the interfacing elements are needed for a
given set of scenarios, which also have to be identified. This
task is not trivial, particularly as interfaces include numerous
continuous signals.</p>
      <p>The presented definition process should further facilitate
automation and reuse at different stages of the development.
With regard to the latter, system component models could
be replaced by real hardware, for example, and the scenarios
should still be applicable with minimal necessary adaptions.
A prototype editor for the presented mission scenario and
stimulating test signal definition was developed using
Matlab/Simulink. Applied concepts are integrated in the following
explanations. Specified information can also be captured as an
.xml exchange document.</p>
      <p>The paper firstly presents the fundamentals of scenario-based
testing and the applied mission-based scenario approach.
Subsequently the developed scenario definition process is
outlined. This includes an initial methodical overview as well
as the different fundamental steps being scenario specification,
system and environment definition and signal and component
implementation. Finally, a short conclusion is given and the
future work is described.</p>
    </sec>
    <sec id="sec-2">
      <title>II. FUNDAMENTALS</title>
      <sec id="sec-2-1">
        <title>A. Scenario Testing</title>
        <p>
          The classical scenario test approach can be categorized
as a specification-based test design technique (s. [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ]). As
equivalently called ”black-box testing” this means that
requirements, specifications or (interface) models etc. are used to
derive test cases without knowledge of the internal structure
of the tested system [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ]. In that respect scenario testing
focuses on sequences of interactions with interfacing systems
or components. In software testing literature, also user-centric
use cases are utilized equivalently to scenarios [
          <xref ref-type="bibr" rid="ref3">3</xref>
          ]. Other
specification-based testing methods contrarily mainly rely on
the systems input-output space for specification verification
e.g. by identifying possible input combinations or partitions
with equivalent behavior. Therefore, scenario testing is more
suitable to assess systems long-running (end-to-end) behavior
in a realistic operational situation. This story-like character
consequently attains motivational and meaningful context (s.
[
          <xref ref-type="bibr" rid="ref4">4</xref>
          ]) to discover hidden failures and their possible effects.
Models, e.g. formulated in formalisms like state charts or
sequence diagrams, are commonly used to describe the
possible interaction sequences. The typical scenario definition
procedure from [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ], towards which this work is oriented, can
be reduced to the following two steps:
1) Definition of one main scenario, that describes the
nominal sequence of actions
2) Derivation of alternative scenarios based on the given
main scenario.
        </p>
        <p>The latter can be diverse, as it includes foreseen operational
options, exceptions and intended or unintended incorrect
entries. Therefore, these scenarios are often further classified e.g.
as positive or negative w.r.t. whether the goal of the interaction
is expected to be achieved or not. A trivial aircraft example:
If the aircraft is on ground, it should not be possible to retract
the landing gear.</p>
        <p>As outlined here, scenario testing has the potential to assure
safer and more robust system-functions through the diversity
of realistic scenarios. Particularly automation functions could
be validated early. However, it is also clear that a systematic
test of the complete input-output space is not the goal. A
scenario targets one specific, but complex set of operations
and exploring all possible parameter variations would blow
up the number of test cases. Other approaches to black-box
testing probably perform better in this respect. Moreover, as
a black-box testing technique, coverage of all internal system
states is also not the primary intend where a structure-based
technique may be more suitable.</p>
      </sec>
      <sec id="sec-2-2">
        <title>B. Mission-Based Scenario Approach</title>
        <p>
          As aircraft systems are typically integrated subsystems of
the overall vehicle, the functional behavior is typically oriented
towards the flight mission. For that reason, an operational
scenario-based test approach was developed in [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ], which
models the flight mission in a state-chart as a sequence of
fundamental phases, that are represented as atomic states
along a scenario path. The major aim is to support the
overall system integration tests to observe coupling effects
between involved components and software functions. The
current application focuses on the use for simulation-based
pre-design investigations but the principal transferability to
final integration testing is desired. Therefore, the approach
intends to complement requirements-based test activities by
exploring the operational overall system behavior to uncover
undesired effects, with a particular desire to find interactions
between ATA chapters.
        </p>
        <p>
          The virtual test architecture from [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ] foresees the partition of
stimulating ’test cases’ though the scenario state-chart and the
evaluation, which is done by observing agent modules running
in parallel. These modules could check arbitrary functional
behavior or performance of the system. With this approach
it is possible to realistically set up operational tests, which
enable assessment the overall system’s functional behavior
during complete flight missions. As the integrated system
is investigated, multiple functional specification aspects and
operational sequences can be observed in an simultaneous
manner.
        </p>
        <p>
          The scenario concept presented in [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ] and [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ] uses
multisignal segments in time-series format from a segment library to
create continuous signal profiles for each phase. Test signals
set up for each phase separately are thereby composed to a
complete test vector representing the flight mission scenario.
To cover multiple scenarios, the concept allows branching of
the scenario paths. The time-continuous signal profiles defined
within the phase are complemented by parallel events that are
triggered at discrete test points during a phase. The events
could for example represent cockpit commands and can trigger
alternative phase transitions of the scenario path. This enables
the modeling of events such as an emergency during cruise and
resulting alternative flight phases, such as emergency landing
and evacuation.
        </p>
        <p>
          In [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ] and [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ] the outlined concept was successfully
demonstrated at a multi-functional fuel-cell system, which included
control and automation functions. However, the complex
scenario state-chart has to be created manually and is hardly
reusable. The presented method in this paper also applies the
same mission-based scenario approach. With the foundations
from [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ], the method tries to offer a more structured, modular
and reusable process for the definition of the stimulating
scenario state-chart, that can be automated further.
        </p>
      </sec>
      <sec id="sec-2-3">
        <title>C. Related Work</title>
      </sec>
      <sec id="sec-2-4">
        <title>1) Testing using Scenario-Based System Specifications:</title>
        <p>
          Several works in the recent past adressed the model-based
specification of system behavior in the form of scenarios and
the test activities on the basis of this specification. To clarify
the distinction in the light of scenario-based testing, some
works in that field are discussed in the following.
For the specification of reactive system behavior, message
sequence diagrams are often used in literature on software
engineering to visually define wanted and unwanted system
scenarios. This particularly applies in the context of testing.
One example is the standardized test specification language
TTCN-3 [
          <xref ref-type="bibr" rid="ref17">17</xref>
          ] with primary applications for communication
systems, which allows the formulation of test cases in the
form of sequence diagrams. It is pointed out in [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ], that
the formalism has the advantage to focus on inter-object
communication scenarios without having to specify the objects
internal behaviors. Moreover, extensions such as live sequence
charts (LSC) [
          <xref ref-type="bibr" rid="ref12">12</xref>
          ] exist, which allow the precise definition
of system specifications with different modalities, e.g. what
must and what may happen. Such sequence charts are also
extended in research to describe time constraints (s. [
          <xref ref-type="bibr" rid="ref11">11</xref>
          ]) or
generally visualize temporal properties such as linear temporal
logic (LTL) formulas (s. [
          <xref ref-type="bibr" rid="ref13">13</xref>
          ]).
        </p>
        <p>
          The work in [
          <xref ref-type="bibr" rid="ref10">10</xref>
          ] further demonstrates a way how automatic
test generation can be achieved with modal scenario
specifications. The approach allows the specification of multiple
sequence charts for the system functions that can be active
in parallel, if an initial sequence of the respective scenario
occurs. Due to the granularity of scenario definitions, the
method seems quite scalable. Moreover, a coverage criterium
was developed to minimize redundant scenario combinations
and thus the amount of test cases.
        </p>
        <p>However, the scenario approach of this work is principally
different. As mentioned in the previous section it should
complement the test activities on the basis of specified
requirements. Instead of using a specification model of the system
the presented approach models the stimulating environment
in an operational context on aircraft level. Expectations on
system’s behavior are not modeled in the current scenario
state-chart and must be evaluated in parallel observation
modules or manually in post processing. Reactive behavior
(and timeouts) may be used to model environment reactions
on system outputs. The presented approach is understood to
be more explorative and investigative in the sense to move
away from the scenarios that are explicitly defined through the
specification. It should be emphasized that running
scenariobased specification models in parallel to observe required
functional behavior is possible and intended but exceeds the
scope of this paper.</p>
        <p>
          2) Automotive Street Scenarios: In the context of the
validation of highly automated driving functions in the automotive
sector, the works in the context of the PEGASUS research
project [
          <xref ref-type="bibr" rid="ref15">15</xref>
          ] follow a similar operational scenario philosophy
as presented in this paper. Street scenarios, defined in a
standardized and structured format [
          <xref ref-type="bibr" rid="ref14">14</xref>
          ], include static content of
the street situation and dynamic elements such as moving cars
or pedestrians. The concept allows to execute the scenarios
at simulation as well as real world level. Scenarios can also
be to remodeled from real operation for further investigation.
Nevertheless, a difference for the application in the aircraft
domain is the diversity and number of systems in comparison
to the variety of traffic situation in the automotive sector.
        </p>
        <p>
          3) Signal Segments in Testing: In [
          <xref ref-type="bibr" rid="ref16">16</xref>
          ] a segment-based
approach is presented to generate complex signal inputs with
a low number of parameters for each segment. This principle
is similar to the definition of signal functions in the context of
this work. However, the work in [
          <xref ref-type="bibr" rid="ref16">16</xref>
          ] conducts a structural test
of automotive Simulink models using a search-based algorithm
and does not predefine operational scenarios.
        </p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>III. SCENARIO DEFINITION PROCESS</title>
      <p>The developed definition process pursues three basic
incentives following the modularization and hierarchy principles:
1) Easy set up and management of complex scenario tests
makes them less error prone and more complete for
increasingly complex systems.
2) Give context and improve automated analysis and
documentation by association of signal segments with
specific scenario story elements or actions of the SUT and
its interfacing environment elements.
3) Maximize the reuse of scenario tests and its elements to
reduce effort and make tests more comparable.</p>
      <p>The concrete concepts are discussed in the following.</p>
      <sec id="sec-3-1">
        <title>A. Methodical Process Overview</title>
        <p>The developed procedure is structured into 5 fundamental
steps. An overview of these methodical steps for the scenario
definition is depicted in Fig. 2. The steps can be grouped into
three types of activities: Scenario specification, system and
environment definition as well as signal assignment.
The first abstracts from the concrete system interface or signals
and tries to identify all relevant mission scenarios and their
logical sequence of phases and events. At the end of this
activity, the structural definition of the state chart is complete
and specified up to its basic phase elements and a graphical
representation can be produced (e.g. in Matlab/Simulink
Stateflow). Furthermore, different scenario test cases can now be
derived on the basis of the transition paths through the
statechart. However, as the basic phase states are still empty and
no interface signals are defined yet, the test cases cannot be
applied.</p>
        <p>The second activity defines the concrete SUT interface and its
environment elements. When finished, all interface signals for
the system under test are registered and grouped according
to potential environmental elements. These elements can be
represented as parallel states within a compound phase state.
The scenario test cases defined at this stage could be executed,
but do not exercise the scenarios correctly, as no signal profiles
are defined yet.</p>
        <p>The third and final activity assigns concrete signal profiles
to the defined signals. For each phase and each environment
element, sequences of signal segment models can be assigned.
For re-usability, these models could be linked from a library as
parameterized elements. In such way generic signal segments,
such as a ramp or set functions can be applied, as well as very
specific profiles such as the pressure sensor signal including
noise during an depressurization event.</p>
        <p>
          Following the signal assignment the scenario definition
process is completed. Enough information is gathered to create
executable scenario test cases. Due to the generic setup, an
export to arbitrary test languages is principally possible. The
implemented prototype realizes executable test cases as state
charts in Matlab/Simulink Stateflow and the use with Simulink
Test is foreseen. Furthermore the export to the state machine
notation SCXML [
          <xref ref-type="bibr" rid="ref7">7</xref>
          ] was tested, which is currently further
extended as a generic exchangeable test language in a research
project.
        </p>
        <p>A more detailed description for the concepts in each step is
presented in the following.</p>
      </sec>
      <sec id="sec-3-2">
        <title>B. Scenario Specification Layer</title>
        <p>The scenario specification layer has the intention to identify
and structure all relevant operational scenario conditions by
performing the two steps Scenario registration and Definition
of the scenario statechart.</p>
      </sec>
      <sec id="sec-3-3">
        <title>1) Scenario Registration (AC/System-level):</title>
        <p>In this initial step, the scenarios are registered by a
textual definition and classified. The primary classification is to
whether a scenario represents a nominal sequence of events
or an alternative one. Further classification of the latter e.g. as
positive, exception, negative and misuse with context to system
and aircraft functions still need to be worked out. Optionally
a classification for expected frequency of occurrence or links
to requirement elements can be inserted. Such additional
information should later be used for test case prioritisation
and filtering.</p>
        <p>For the mission-based scenario approach, two different
categories of scenarios were identified:</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>Aircraft mission scenarios</title>
      <p>System operational scenarios
The first includes scenarios such as nominal and alternative
flight phases (e.g. loiter in approach) or emergency descent.
The latter focuses on the system functions and exploits
different system operations or configurations and internal or external
failures.</p>
      <sec id="sec-4-1">
        <title>2) Stepwise Definition of the Scenario State-Chart:</title>
        <p>As a second step, each scenario is setup in one integrated
state chart structure. Scenarios are implemented by sequences
of phase states or event triggers, that could occur during
selected phases or phase groups (e.g. in flight) at defined test
points, or combinations. Firstly one flight-mission phase path
is defined for the main nominal scenario. This scenario should
equivalently represent the nominal system operation.
Subsequently the alternative scenarios can be defined by branching
the nominal scenario at a selected phase and proceeding with
alternative mission phases and by defining parallel trigger
events that mark the start of the scenario. Phase end conditions
could be defined textually for the transition between the
phase states, which then have to be refined by state chart
variables later. Scenarios can partially share a scenario phase
path and end by final phases or explicitly branching into
other scenario paths (e.g. alternative flight mission with the
same landing procedure). An implemented example for the
developed prototype is depicted in Figure 3 - 5. As shown in
Figure 4, a scenario path, such as the nominal flight mission
in the given example, can be constructed with regard to the
taken transition path. Alternatively, as depicted in 5 for the
emergency case, a tabular view of the state path could be
used. The second figure shows, how the alternative scenario
is constructed by branching out of the nominal one. This
structure-based editing can be further complemented by a
hierarchical tree view for all existing states, given on the
left side of the figures. In addition to this structural edition
of scenarios, the illustrated conceptual prototype realizes a
graphical state machine view in Matlab/Simulink Stateflow.</p>
        <p>As both perspectives are transferable, a graphical state chart as
depicted in Figure 3 can be set up easily by this hybrid editing
that combines graphical and structural information. Parallel
events can implement</p>
        <p>
          They occur at discrete test points during the phases. In the
current concept and in orientation to [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ], test points apply
for phases that have a fixed minimum execution time defined
(e.g. cruise time). By defining an integer sampling number for
each phase, the given time frame is partitioned in as many
parts, where each partitions beginning marks a test point. The
defined sampling number therefore has a significant effect on
the resulting count of test cases.
        </p>
        <p>Several parallel events could occur in sequence for one
scenario when suitable transition conditions are defined (e.g.
failure followed by a corrective cockpit action after a defined
time). However, it needs to be taken care that transitions to
other phases in between these events do not happen.</p>
        <p>A method still needs to be worked out how to consistently
define different scenarios, that are triggered subsequently.</p>
        <p>
          Based on the defined scenario state chart, scenario test cases
initial trigger for scenario paths, e.g. emergency, can by identified by traversing along the path and taking
trigger for usual phase-internal operations without effect into account the parallel events. An algorithm for automatic
on transitions (e.g. different cabin loads), path identification and subsequent test case generation was
trigger for failures (e.g. cabin smoke / fan failure) or presented in [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ] for scenario state charts in the format that
combinations. was adopted from [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ]. The test cases end at final phase states
or when the path loops. They are executable either by suitable
control mechanisms to enable specific paths for the holistic
state chart or by extracting unbranched scenario paths. The
first option was demonstrated in [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ].
        </p>
      </sec>
      <sec id="sec-4-2">
        <title>C. System and Environment Definition Layer</title>
        <p>The activities described in the section aim to define
structured objects in the environment of the system under test. This
should enable a more straight forward and reusable definition
of the signal profiles that are applied to the SUT interfaces for
each scenario phase.</p>
      </sec>
      <sec id="sec-4-3">
        <title>1) System Under Test (SUT) Interface Definition:</title>
        <p>Before defining the environmental elements, the actual
interface of the system under test has to be defined, which should
be used for the scenario test. This predominantly includes
the declaration of the SUTs’ input and output signals by
defining signal name, data-type, initial value for inputs and
units. Moreover, special inputs, such as fault trigger for system
model components, can be defined that may be needed to reach
certain scenarios. To be able to reuse the test scenarios at
different designed stages, all signals are symbolic variables
and abstract from real transmission mechanisms. If more
realistic transmission are needed, e.g. for hardware in the loop
(HITL) integration, specific drivers need to be set up outside
of the test definition process or manually integrated into the
SUT model. These drivers could be defined on a target test
system, such as dSPACE Scalexio, TechSAT ADS2 or Vector
test hardware, which provides the hardware interface e.g. to
send signals as CAN messages to real control modules in a
HITL test.</p>
        <p>The interface information could be loaded from an interface
document file, that may be available from a model-based
development process.</p>
      </sec>
      <sec id="sec-4-4">
        <title>2) Environment Component Definition:</title>
        <p>As a second step, the definition and categorization of
environmental elements is carried out. Each previously defined SUT
interface signal can subsequently be assigned to one interface
element. Furthermore, it is intended to allow the definition of
signal groups within environmental elements, if it is desired to
define a single maneuver or action in the environment that acts
on several signals. One example could be the use of two
redundant sensors or protocol-based signal groups. Based on the
given signal classification, parallel compound state processes
for every environmental element are inserted into each of the
scenario phases of the state chart structure. Similarly, single
signals or signal groups form parallel processes within these
compound states. In that way, sequences of actions or signal
profiles could be assigned completely separate for each signal
or signal group of each environmental element within each
flight phase. An example is visualized on the left side of Figure
6, which includes the environmental elements Cabin Loads,</p>
      </sec>
      <sec id="sec-4-5">
        <title>Environment, Flight Management and OVHD, that contains the signal Temp Demand.</title>
        <p>In the case that it is desired to include single mathematical
calculation models that apply continuously during the
complete mission irrespective of any scenario, a parallel process
to the scenario state chart is foreseen. For instance this could
be models that calculate the atmospheric pressure based on
a height profile that results from the scenario path. It should
be mentioned that in principal, these models could also be
set up outside of the state chart. The parallel calculation
model process can be structured with the same environment
component definition as for the phases. However, assigned
signals and signal groups are then excluded from the phases.
The modular setup as described prepares a structured and
realistic signal assignment and facilitate re-usability through
component libraries. Moreover, it creates context for reporting
and analysis.</p>
      </sec>
      <sec id="sec-4-6">
        <title>D. Signal and Component Implementation Layer</title>
        <p>Having defined the hierarchical structure of scenario phases
and groups of signals as environmental elements in the
previous steps, the concrete signal profiles are set up in this last
step. For each phase state, the information gathered before
includes the phase name, scenarios that include the phase,
applicable parallel events and it’s trigger for each scenario
and the environmental component structure.</p>
        <p>Based on this, sequences of signal functions and segments are
now assigned to the signal variables as defined in the previous
step. Following the objective of re-usability, a library concept
for parameterizable signal functions is used. Two fundamental
function types are foreseen:
(Atomic) basic functions, that have a representation for
the test system the scenario is intended to run on.
Higher level functions, that are state chart compounds
containing basic functions, states and transitions.</p>
        <p>
          The atomic function library should be fixed while higher
level functions for component models can be defined
individually as needed. The library concept makes it easier to
set up realistic scenarios by having (signal-based) interface
component models with parameters such as sensors including
noise, different atmosphere models etc. When assigning the
library elements to the scenario the function symbols have
to be mapped to the scenario signals. The sequence of library
elements for each signal is defined by an unbranched transition
path where a transition is taken after predefined times or
arbitrary expressions. The use of common atomic functions
at lowest level enables the translation of the test scenarios to
other test scripting languages (e.g. SCXML [
          <xref ref-type="bibr" rid="ref7">7</xref>
          ] in its extended
form or proprietary solutions). The assignment of parallel
calculation models is done in the same fashion as for the
phase signals. An example for the definition of sequential
linked basic functions is depicted in Figure 6 for a temperature
demand signal set from the flight deck during cruise phase.
The functional elements, which are all set functions in the
example, are defined and parameterized in a tabular form. The
depicted sequence of linked states, which creates the signal
shown on the right side, can then be automatically generated.
To complete the signal assignment, phase end conditions need
to be defined to trigger the transition to the next phase.
These could be already specified textually during the scenario
definition steps e.g. cruise time and emergency trigger event or
can be individually defined according to the assigned profile
(e.g. speed 0). For continuous signals care has to be taken,
that the steadiness is fulfilled when transitioning between the
phases. Useful mechanisms will still need to be worked out.
        </p>
      </sec>
    </sec>
    <sec id="sec-5">
      <title>IV. CONCLUSION AND FUTURE WORK</title>
      <p>In this paper, a structured procedure was presented to
collectively define flight mission-based scenarios in a
statechart formalism and refine them to create realistic signals for
test stimulation. The aim is the verification and validation of
integrated aircraft systems in an operational context. Due to the
mostly generic and modular approach, the complex scenario
definition can partitioned into small manageable parts. Hence,
the method would speed up the process and be reusable at
different stages of the system design. The definition of system
scenarios in the first step is as far as possible abstracted from
the concrete system implementations and can be set up
independently, early in the process. The approach of hierarchical
objects for signal groupings in the further modeling achieves a
highly reusable structure, which could be adapted easily with
regard to design changes. Finally, with the concept of basic
atomic signal functions as library elements, independence from
test automation systems can be reached, given that suitable
conversion mechanisms exist. However, the concept is yet to
be applied in a complete system test campaign.</p>
      <p>In future works, it still needs to be investigated, if the
scenario definition based on paths and parallel events is
mature enough to handle very large and complex systems or
if further mechanisms need to be developed. The procedure
was implemented as a prototype in Matlab/Simulink using
mixed hybrid graphical and structured editing, which was also
presented in this paper.</p>
      <p>Another open topic is the automatic evaluation of test runs. As
pointed out in the presentation of the mission-based scenario
approach, the defined scenario state-chart represents only the
stimulation part for the test execution. Therefore the definition
of parallel observer logics for evaluation is a major point to
be addressed. The evaluations could include specified system
functional or performance requirements.</p>
      <p>
        Moreover, open parameter definitions shall enable the
systematic exploration of specific scenarios. The transfer of resulting
system states over repetitive scenario runs is also considered
in that context, e.g. to assess wear effects. In that context, the
remodeling of realistic scenarios from operational data and
investigation of parameter variations is could be addressed.
The integration of operational recordings of signals from real
operations will also be worked out for this purpose. This
should expand the segment-based approach that was already
demonstrated in [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ].
      </p>
      <p>Finally, due to intend for automatic test execution the export
to common test automation engines should be investigated.</p>
    </sec>
    <sec id="sec-6">
      <title>ACKNOWLEDGMENT</title>
      <p>I would like to thank Martin Halle, Hauke Ho¨ ber and the
anonymous reviewers of the AvioSE’20 for valuable comments
on the draft version. The presented results are part of the work
in the research project AGILE-VT (contract code: 20X1730J),
which is supported by the Federal Ministry of Economic
Affairs and Energy in the national LuFo V-3 program.</p>
    </sec>
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