=Paper=
{{Paper
|id=Vol-2118/iStar2018_paper_11
|storemode=property
|title=Goal-oriented Contextual Requirements Analysis in the Presence of Digital Stakeholders
|pdfUrl=https://ceur-ws.org/Vol-2118/iStar2018_paper_11.pdf
|volume=Vol-2118
|authors=Tharaka Ilayperuma,Jelena Zdravkovic
|dblpUrl=https://dblp.org/rec/conf/caise/IlayperumaZ18
}}
==Goal-oriented Contextual Requirements Analysis in the Presence of Digital Stakeholders==
https://ceur-ws.org/Vol-2118/iStar2018_paper_11.pdf
Goal-oriented Contextual Requirements Analysis in the
Presence of Digital Stakeholders
Tharaka Ilayperuma1 and Jelena Zdravkovic2
1
Department of Computer Science, University of Ruhuna, Matara, Sri Lanka
2
Department of Computer and Systems Sciences, Stockholm University,
Postbox 7003, 164 07, Kista, Sweden
sesath@dcs.ruh.ac.lk, jelenaz@dsv.su.se
Abstract. Deriving from diverse and vastly growing sources, digital data is
emerging as the essential resource to organizations, enabling them to by
enlarging their body of knowledge advance in highly demanding business
situations and markets. The means enabling holistic reasoning and modeling
business constellations including varieties of digital sources of data, and the
ranges of different contexts covering those data are therefore a challenge in the
modelling community. In this paper, we analyze the use of the core i* language
for supporting modeling of context-dependent business environments where the
contexts’ data is provided by digital actors. We have defined the mappings from
the main concepts for the domain of the investigation (such as digital sources,
context and capability) to the elements of the i* 2.0. We illustrated our proposal
by applying it on the service concerning roads maintenance.
Keywords: i*, Requirements, Context, Capability
1 Introduction
Digitizing business services is becoming a fundamental necessity. In many domains,
there are opportunities to derive better decisions by collecting and analyzing data
from diverse digital sources, such as web sites, mobile devices, social media and IoT,
such as in healthcare for accurate diagnosis, or for weather forecasting, maintenance
of industrial tools, energy consumption, transport, etc.
Traditionally, the Requirements Engineering (RE) discipline has been stakeholder-
driven, i.e. existing methods for elicitation of the requirements for embedded or
information systems rely on business organizations and individual stakeholders as the
main sources of information [1]. Tremendously increasing digital data sources, in
their versatile forms, facilitate a heightened level of awareness about business and
individual environments and conditions, which therefore promote them to be
considered as new types of active requirements’ sources.
In this context, a challenge concerns lack of the methods and tools for supporting
reasoning about system requirements in a way that would enable domain experts and
developers to mutually understand and communicate these requirements for
Copyright 2018 for this paper by its authors. Copying permitted for private and
academic purposes.
improvements of existing software solutions or for development of new ones. One
commonly discussed approach proposes to elicit motivations behind business models
using organizational goals [2].
In this position paper, we concisely analyze the use of the i* goal modeling
technique as a tool to support modeling and visualization of situational business
environments encompassing constellations of pervading physical and digital actors,
with the aim of elicitation of high-level system requirements capturing the data
resources provided by these actors, as well as the desired functionality related to these
data. Owing to i*’s ability for modeling the dependency links between different
entities, we have found the technique as also applicable for discovering new digital
actors (sources) in situations when goals and needed data resources are explicated.
The rest of the paper is organized as follows. Section 2 outlines a brief background
to data and context-driven requirements engineering. Section 3 presents the
theoretical proposal and illustrates it on the case concerning roads maintenance. A
discussion and concluding remarks are given in section 4.
2 Data and Context-driven Requirements Engineering
Today’s organizations operate in dynamically changing situational environments
(contexts). Having a continuous access to relevant, accurate and usable data is
therefore highly important for organizations, but in turn, it leads also to the
requirements to improve their information systems to be able to benefit from new and
often changed and updated data [3]. One methodological approach for dealing with
dynamic business contexts implemented by the means of information systems is
Capability Driven Development, CDD [4]. It is a methodology developed to support
continuous delivery of business capabilities (i.e. functions [5]) by being able to
capture and take advantage of changes in business context. The success of a business
and IS infrastructure is therefore highly tight to the ability to entirely fetching the
relevant surrounding business context and where digital data from IoT, mobile
devices, websites and other play a highly significant role as versatile, precise, accurate
and scalable information sources.
Goal-oriented approaches for analyzing contexts related to system development are
well elaborated in [4] and [6]. Differently from them, the aim of this small study is to
analyze the usability of the i* modeling language [7] (in particular, i* 2.0 [8]) for
enabling a core understanding and integration of the goals and available resources of,
in a varying context business constellation, involved physical and digital actors, for
enabling needed system capabilities.
3 A Requirements Analysis Framework using i*
In this section, we describe a lightweight i* framework for analyzing context-driven
requirements were the contexts’ data is obtained from digital sources.
As for the notion, for the purpose of this study, we consider i* 2.0 and its main
elements: Actor, Intentional elements and Dependency as the main archetypes. Actors
are autonomous entities aiming at achieving their goals in collaboration with other
actors; they could be further refined to roles (actors with domain behaviors) or agents
(actors with concrete physical manifestations). Goals, qualities, tasks and resources
are the intentional elements used for modeling the things wanted by actors.
Dependencies represent social relationships between actors in the way that one actor
depends on another actor for something that can be a resource, a task, a goal or a
quality. The i* language distinguishes two types of model views: Strategic
Dependency (SD) model showing the actors and the dependencies between them, and
Strategic Relational (SR) Model presenting a detailed view of the intentions of
involved actors.
The scope of this paper is to analyze how i* be used for modelling context-based
business environments in the presence of digital devices that provide resources to
fulfill the context-based goals. Thereby, we consider a business environment where a
User obtains the services of a System (IS) to fulfill his/her context-related resource
requirements or goals. The System that provides Services, has a set of context-based
goals and obtains data (resource) required to fulfill such goals from different types of
Digital Sources. As such the analysis would concern the possible mappings between
the concepts in the domain as described above and the i* 2.0 elements.
As a brief presentation of the framework usage, the figure below illustrates how
User (role) is for the fulfillment of his/her goal “Traffic info provided”, dependent
through an online Service (agent) for obtaining “Traffic related data” (resource) from
digital sources (actor, which can be refined further to a concrete source, i.e. agent).
Fig. 1: i* Strategic Dependency model for an automated traffic service
In Table 1 below, we summarize the mappings from the concepts in the domain of our
concern to the i* 2.0 modelling language.
Table 1 – Mapping rules
From To
Description
Concept i* element
Abstract characterization of People or
User Role organization types in the need for some
contextual data resources.
An automated service realizing the
Agent
Service requirements for the resources through its
(System)
goals and capabilities.
A mobile device, a website, or IoT that fulfills
Digital source Agent the goals related to a particular context of the
Service agent by its data resource(s).
Data Resource Information provided by a digital source.
Resource Service is dependent on Digital source for
Dependency Data (resource) to fulfill the service’s context-
Relationship
from Digital dependent goals
between Service
source
and Digital
(Agent) to
source
Service
(Agent)
A clear-cut desired condition of a role or an
Goal Goal
agent.
A state (condition) of a business pertinent to
Business Context Quality User, further referring/associated to goals of
Service.
A function of Service utilizing data resources,
Capability Task
to be developed and implemented.
To illustrate the guidelines for use of the proposed framework, we consider the case
of road maintenance under different weather circumstances (contexts) such as snowy,
icy and frosty road conditions, road damages, traffic disturbances, etc.
Step 1: Identify people and organizations having needs for the service
Driver is dependent on Road Service for a usable road conditions, such as “Snow is
cleared”, “Road is not slippery” (goals), as well as for the information regarding
traffic disturbances such as road construction details, traffic signal failures, objects
disturbing flow of traffic on roads (resource); this is summarized in Fig. 2 below.
Step2: Identify contexts for which Service capabilities are required.
Following [4] and [6] and Table 1, a context of interest can be defined as a condition
characterizing a situation pertinent to business users and therefore relevant to some
goals of the actor under concern. Following this, table 2 below summarizes the
identified contexts (represented as Quality in Fig. 2), related goals of the Road
Service agent, and needed capabilities (represented as tasks in Fig. 2).
Table 2: Contexts relevant for Road Service
Context Description
Traffic disturbance Depending on different types of traffic disturbances such as road
constructions, traffic signal failures, objects on road disturbing the
flow of traffic, service agent should be capable of delivering the
required capabilities (tasks in Fig. 2)).
Icy conditions Depending on the different temperature levels at the road surface, the
service agent should have the ability to carry out the capabilities
required to eliminate slippery conditions on roads (Fig. 2)
Snowy conditions Based on weather forecasts the service agent should be in a position
to give precise details to maintain road network free of snow (Fig. 2).
Step3: Based on the required capabilities of the service agent, determine digital
sources needed to deliver such capabilities.
Requirements for data resources of the identified capabilities (tasks) are analyzed to
determine the desired data resources and further the digital sources able to provide
these resources. Here the modeler should consider the required capabilities to link
them to the available devices, or introduce new sources by considering the resource
requirements. Additionally, the modeler can compose several digital sources to get
aggregated information. In table below and in Fig.2, we summarize the analysis of the
data resource dependencies of the Service agent (i.e. its tasks/capabilities).
Table 3: Resource dependencies for Road Service
Task Resource Digital Source
Update traffic Construction details – Handheld construction details reporter
info construction related work source
details are often published to
inform the disturbances to the
normal traffic flow
Report traffic Traffic light failure info – Traffic light with the ability of detecting
signal failures traffic light failure any possible alterations to its proper
information is published to functioning and reporting that to the
inform the drivers about Service agent
failures of automatic traffic
management in road networks
Analyze Weather data, Weather Composite Traffic camera or Weather
weather data, forecast, Road condition and and temperature sensor and Weather data
Collect Temperature – Weather data analyzer – The traffic cameras can
temperature, is required to forecast aggregate the functionalities of capturing
and Predict different weather conditions. weather information around road
road The surface level temperature networks. Specialized weather and
condition at road networks is useful to temperature sensors be used similarly.
determine icy conditions on Weather data analyzer having the is used
roads to forecast snowy conditions.
Report object Object data – objects on the Composite Traffic camera
details road disturbing flow of traffic
Fig. 2. i* Strategic Rational Model for the road maintenance service, with identified data
resource dependencies to digital sources for required service capabilities (tasks).
A brief discussion of the presented results, conclusions, and the plans for further
work are presented in the next section.
4 Discussion, Conclusions and Future Work
In this paper we have analyzed how the i* modeling language can be used to simply
and holistically model context-dependent business environments where the contexts’
data required for business capabilities is provided by digital actors. We have defined
the mappings from the main concepts for the domain of the investigation (such as
digital sources, context, capability) to the elements of the i* 2.0. Further, we have by
means of step-wised guidelines illustrated the use of the proposal on the case of the
road maintenance.
The motivation behind this study lies in the fact that the success of today’s
organizations highly rely to their ability for gathering different data from their
surroundings, and where the requirements for data accuracy, amount and the pace of
processing are constantly increasing. The i* modeling language provides the ability to
in a single view describe and integrate the relevant domain concepts for enabling
further development of information systems (services) capable to support different
business contexts. An important consideration in this domain of study refers to
system’s behavior at run-time. Using the i* technique, it is possible to define relevant
business contexts, needed data sources and capabilities, however, additional design is
needed to support switching of system’s capabilities for different contexts that are
changing over time. This challenge is for example explored by the CDD
methodology [4], which supports monitoring of the contexts by processing their data
and handling of capability adjustments when the monitoring indicates such changes in
the context requiring another capability.
For the near future work, we plan to investigate the integration of the emphasized
strengths of the i* technique in the domain of system’s requirements analysis with the
needed information for system’s run-time management for context adjustments.
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