=Paper=
{{Paper
|id=Vol-1753/paper2
|storemode=property
|title=Combining Model-driven and Capability- driven Developments: A Case Study of Industrial Symbiosis
|pdfUrl=https://ceur-ws.org/Vol-1753/paper2.pdf
|volume=Vol-1753
|authors=Christina Stratigaki,Pericles Loucopoulos,Antonis Migiakis,Yannis Zorgios
|dblpUrl=https://dblp.org/rec/conf/wecwis/StratigakiLMZ16
}}
==Combining Model-driven and Capability- driven Developments: A Case Study of Industrial Symbiosis==
https://ceur-ws.org/Vol-1753/paper2.pdf
Proceedings of CBI 2016 Industrial Track
Combining Model-driven and Capability-driven Developments
A Case Study of Industrial Symbiosis
Christina Stratigaki Pericles Loucopoulos Antonis Migiakis Yannis Zorgios
CLMS (UK) Ltd CLMS (UK) Ltd CLMS (UK) Ltd CLMS (UK) Ltd
London, United Kingdom London, United Kingdom London, United Kingdom London, United Kingdom
c.stratigaki@clmsuk.com periloucopoulos@clmsuk.com a.migiakis@clmsuk.com yz@clmsuk.com
Abstract
This paper reports on a practical case that involved the confluence of an industrial
software development platform, based on the model-driven development paradigm and a
research methodology and prototype set of tools, based on the notion of capability. The
focus of the application is the development of a web-based industrial symbiosis platform.
The outcome is an example of a successful alignment of business-facing aspects with
those informatics constructs that ensure alignment of between goals and processes of an
enterprise with its support IT system.
1 Context of the Case
This paper reports on an industrial case that has been developed using a combination of (a) an existing software development
platform based on the Model Driven Architecture (MDD) paradigm1 and (b) the method and tools that have arisen as a result
of a project2 funded by the European Commission. This industrial case was carried out by CLMS (UK) Ltd, a software
technologies company.
The work reported in this paper involved a software service from the area of industrial symbiosis, henceforth referred to as
i-symbiosis. This is essentially a specialized capability that acts as “enabler of web industrial symbiosis”.
Industrial symbiosis (IS) is an association between two or more industrial actors in which the wastes or by-products of one
become the raw materials for another. This collaboration between two or more companies is called a synergy. Industrial
symbiosis brings together companies from different business sectors, with the aim to improve cross-industry resource
efficiency through the commercial trading of: waste materials, energy and water, sharing of processes and assets such as
logistics and expertise.
As a result, waste across a wide range of industrial activities, including chemicals, plastic, biomass, electronic and plastic, is
reduced, and costs in raw materials, waste discharge and energy consumption are saved. Traditionally, experts and consultants,
involving highly complex, labor-intensive and error-prone tasks that often lead to problematic and sub-optimal reuse of
available resources, performed industrial symbiosis mediation process for the matching between producers and consumers
manually.
For the i-symbiosis service we considered such an exchange amongst firms as being organized "virtually" across a broader
region, taking into consideration three contextual factors that are key to industrial symbiosis, namely those of location,
resources and legislation. The key phases of i-symbiosis are depicted in Figure 1.
Figure 1 IS Key phases
Waste providers must insert to the platform their available resources and their type along with other resource-details (Phase
1 & Phase 2). In the 3rd phase, the waste provider searches for interesting parties (waste engagers). An industrial symbiosis
1
This platform is a proprietary platform for the CLMS (UK) Company, known as zAppDev, details of which can be found in http://www.zappdev.com.
2
Information about this project, known as CaaS (Capability as a Service) can be found in http://caas-project.eu.
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Proceedings of CBI 2016 Industrial Track
platform has to match automatically the provided type of resources to suitable exchange resources and track the available
industries, which can act as resource engagers. After the matching process, the waste provider selects one or more of the
available matching results to start a synergy. Within the Synergy collaboration, the two interesting parties (waste providers and
waste engagers) negotiate about the waste exchange. The last stage in the platform is to report the status of the synergy.
Whether successful or not, a report is created which demonstrates the synergy timeline and the arguments supporting either the
success or the failure of the synergy. By the end of this industrial symbiosis workflow, the platform creates a “case study” upon
the synergy collaboration based on the report.
We considered the provision of service of i-symbiosis as being possible through the capability “enabler of web industrial
symbiosis”. This was further analyzed in terms of three capabilities: (a) determining relevance rating, (b) resource description
and classification and (c) compliance with regulations. For (a) automated adjustments were considered based on location
context; for (b) semi-automated adjustments were considered towards resource monitoring; and finally for (c) manual
adjustments were considered for legislation handling.
2 The Business Environment of CLMS
2.1 Introduction of CLMS (UK) Ltd
CLMS (UK) Ltd was established in 1998 with a vision to simplify business change management, with specific focus on IT
Systems. CLMS design and produce business-driven IT systems based on an agile methodology and with the ability of
maintaining their services and to be constantly aligned with cutting edge technology trends.
All development activities are driven by models that capture business semantics and provide a clear overview of every
component of the application. By using models and process logic descriptions, CLMS achieve to offer customized and tailored
services. They provide to their clientele a variety of services, including ERPs and cloud-based ecosystem solutions.
The “philosophy” of CLMS is to continuously improve the services they provide through an increased level of their
capabilities. At the same time, the knowledge and experiences they gain from the delivery of these enhanced services, directly
impacts, informs and evolves their own capabilities. This feedback causality loop is the CLMS meta-capability that it strives to
maintain in all of its business activities. It is a continuous capability development and improvement cycle that is facilitated and
indeed it is embodied in a specific platform, namely that of the zAppDev platform.
Therefore, by participating in the CaaS project, CLMS strives to enhance their capabilities, specifically those that relate to
their core products and services that are embedded in the zAppDev platform.
2.2 Introduction to zAppDev
zAppDev is a cloud-based application development environment. It supports high-level modeling, design validation and code
generation in order to automate repetitive tasks and produce consistent applications for multiple platforms. Changes in the
design and technology are incorporated fast through an automation engine, using model compiler templates. zAppDev
facilitates IT and business teams’ collaboration; applications can be tested immediately after each build. Their clients can test
their application from day one and throughout the design and development life cycle.
zAppDev is model driven. It provides a complete integrated approach for modeling business requirements, workflows,
business logic, data and web services, and user interfaces, and automatically generates the complete software application from
these models. zAppDev is quite different from other application development frameworks (e.g. Ruby on Rails), because it is
not tied to a particular programming language, and/or type of application that it can produce.
Because zAppDev is model driven, CLMS is able to provide complete integrated solutions to a large variety of domains.
With each domain analysis and implementation, zAppDev can adopt extra features of functionality within it and evolve as a
software platform (as mentioned already about the CLMS business capability development).
Consequently, zAppDev itself offers to CLMS the key features of: reusability, customizability, adaptability, and
extendibility.
In summary zAppDev offers:
1. Platform independence
2. Incremental instantly-adaptive development
3. Integrated Architecture Governance and Flexible Application Life-Cycle Management
2.3 Introduction to CaaS
The CaaS project proposes a capability-driven approach to business and IT development in order to produce solutions capable
of fitting to changing business contexts and at the same time taking the advantage of emerging technology solutions. From the
business perspective, we define capability as an ability to continuously deliver business value in dynamically changing
circumstances [1]. From the technical perspective, capability delivery requires dynamic utilization of resources and services in
dynamically changing contexts.
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Proceedings of CBI 2016 Industrial Track
The overall ethos of the CaaS project is to create an integrated approach consisting of methods, tools and reusable best
practices that allow digital enterprises to take advantage of changes in business context and technologies.
The main contribution is a new methodology for joint digital business and information system development referred as the
capability driven development (CDD). The CDD provides the means for coping with a variety of business execution
alternatives and for adjusting business delivery according to changes in the operating context.
The conceptual elements surrounding capability, are based on the core concepts of Enterprise Modeling e.g. [2, 3] with
extensions that offer opportunities for a greater and a more in-depth analysis [4, 5]. Figure 2 depicts the interrelations among
business capability entity with already known concepts such as business goals, KPIs, business processes, context, resources
etc.
Figure 2 The ‘capability’ meta-model
A capability development environment is also established. The main components of the environment are3:
• Capability Design Tool (CDT): a graphical modelling tool for supporting the creation of models (goal models,
process models, concept models, context models, business processes and capability models) according to the
capability meta-model.
• Capability Context Platform (CCP): The context platform is a platform for gathering the context information
defined in a context model and distributing it to the CNA.
• Capability Delivery Navigation Application (CNA): a web application that imports the capability models
defined in the CDT in order to monitor the described context. CNA connects to the context platform to monitor
the capability context, informs the capability analyst and business services manager about current KPIs and
handles run-time capability adjustments.
• Capability Delivery Application (CDA): A CDA represents the business application or service used to support
the capability delivery.
A high-level architecture design of how these components are related is shown in Figure 3. It describes interaction between
essential components of the system: CDT as design-time tool, CNA and CCP as general runtime support, CDA and custom
data providers developed for each use-case.
Figure 3 CDD Architecture Design4
3
Described in D5.3: Final Version of CDD Methodology, Deliverable of CaaS Project, 31st of May, 2016
4
Architecture Design is taken from D6.6: CDD Environment Documentation, Deliverable of CaaS Project, 29th of April, 2016
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Proceedings of CBI 2016 Industrial Track
3 Designing of the I-symbiosis Platform
CLMS aimed to implement an industrial symbiosis platform which would improve industrial symbiosis by automating the
process of mixing and matching the interests of different actors in the symbiotic waste resource chain, and would provide
knowledge-based support for managing resources and finding compatible ones. The platform should be able to suggest
compatible matches to a company and facilitate the creation of Synergies for these matches.
At the core of the platform needs to be the industrial symbiosis semantic repository, which is based on knowledge graphs
instead of relational databases. The knowledge management of resources is more efficient due to machine learning
architectures and it is increasing the time of response within the system during the matching process while simultaneously the
repository of resources will distinctly increase.
Through the industrial symbiosis web portal, users will be able to register to the system, access and enter information about
resources, locations, their interests etc. in a user-friendly way, through maps, graphs, and wizards. Concepts and properties
from the industrial symbiosis ontology will be used to guide users through the navigation and registration processes, and the
information registered through the portal will be stored in the semantic component. Various types of user queries for finding
contacts, companies, and resource matches will be supported.
User profiles along with information extracted from the semantic repository will be used by the matchmaker service, which
computes intelligent matches between production and demand for industrial waste through a highly sophisticated algorithm.
Optimal sets of possible collaborations between businesses will be produced by calculating the similarity between resources
and technologies with respect to the distance between these concepts in the domain ontology.
The results calculated by the matchmaker will be presented to the user through appropriate views at the portal. Business
users will be able to monitor and manage the established synergies lifecycle, e.g., access other participants’ resources and
information, or block the progress of a synergy. A number of metrics, such as landfill diversion, water savings, and CO2
reduction, will be used to evaluate the performance and activity of synergies. These metrics will be available by the
participating organizations, and they could be updated during a synergy’s lifecycle.
Through a notifications system, industrial symbiosis practitioners will be notified about important changes in the synergies
in which they will participate. Aggregated information and statistical reports about the synergies, sites, companies etc. will be
also generated by the platform.
A use-case diagram representing the aforementioned description is depicted in Figure 4.
Figure 4 Industrial symbiosis use case diagram (Synergy sub-case)
The user groups of industrial symbiosis platform are the following:
• Waste producer
• Buyer
• Solution provider (Technology provider)
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Proceedings of CBI 2016 Industrial Track
4 Enhancing CLMS Capabilities Thorugh a Confluence of zAppDev and CaaS
4.1 Identify CLMS’ capabilities on a business level
Their capabilities are defined as such, because they are the result of the combination of resources, skills and business goals (e.g.
Domain Modelling, Cloud Migration etc.). For delivering those capabilities, CLMS as a software house uses state of the art
technologies such as Knowledge Models and REST/SOAP services. The collaboration of capabilities with technologies are
providing CLMS services to their clientele (e.g. industrial symbiosis ecosystem).
All of these capabilities are met through zAppDev. zAppDev is a cloud-based application development environment. It
supports high-level modelling, design validation and code generation in order to automate repetitive tasks and produce
consistent applications for multiple platforms.
In these terms, the main business capability of CLMS is the M_CAP1 Adaptive and Extensible Software Development. This
top business capability can be analyzed in terms of the sub-capabilities depicted in Figure 5.
Figure 5 Capability diagram of CLMS
Each sub-capability is responsible for the delivery of one or several business services. An excerpt of that kind of
interrelation is presented in TABLE 1.
TABLE 1 Capabilities and Services of CLMS
Services Capabilities
ERP Solutions S_CAP1 Architecture Design
S_CAP2 Domain Analysis
S_CAP3 Application
Development
Industrial Symbiosis S_CAP3 Application
Ecosystem Development
S_CAP4 Continuous
Engineering
Maritime Connectivity S_CAP4 Continuous
Infrastructure Engineering
S_CAP5 Integration APIs
Connectivity Infrastructure
Bank Enterprise S_CAP8 IT Change
Management
S_CAP9 Software
Development as a Service
4.2 I-symbiosis capability driven analysis
For the implementation of industrial symbiosis platform, CLMS makes use of a set of capabilities that is composed of internal
and external capabilities as shown in Figure 6. The collaboration of these capabilities, apart from delivering the service of
industrial symbiosis, are creating a new capability for CLMS, the “Enabler of web industrial symbiosis”, see Figure 6. Because
zAppDev is adaptive and it is knowledge dependent, it “absorbs” all the knowledge, which was concluded from the
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Proceedings of CBI 2016 Industrial Track
combination of the set of the initial capabilities. The new capability for CLMS can be described as acting as the enabler of
industrial symbiosis through a web based platform. This capability will be further analyzed into sub-capabilities.
Figure 6 CLMS capabilities used for the industrial symbiosis capability
The goal model presented in Figure 7, is combining high level business goals which represent the philosophy of CLMS and
specific use case goals which are setting the framework of implementing the industrial symbiosis platform. Thus, the goal
models reflect the desired changes to be performed to improve the platform.
In order for CLMS to expand the industrial community regarding the synergies, they intend to introduce a web platform for
industrial symbiosis (CLMS GIS3) and implement its functionalities with respect to the key concepts and goals of IS theory. In
this holistic approach, they desire to face the various contextual factors that will possibly change the flow of i-symbiosis
functionality (CLMS GIS12). Three goals are supporting the notion of context awareness which are introducing the main
context elements of the desired platform: Resources, Location, and Legislation.
CLMS GIS14 is supported by two other goals. The first one refers to the designing of a resource repository (CLMS GIS17).
In the platform the resource repository is designed with the use of knowledge graphs (CLMS GIS10). The use knowledge of
graphs allows the platform to be adaptive and extendable in terms of adding new nodes in the existing graphs (resources in our
case). The second goal supporting a knowledge graph repository is the use of patterns-templates (CLMS GIS18) for resource
management. Giving an example, the platform is able to respond and function in different locations with different types of
resources which may not be registered to the knowledge graphs. zAppDev already supports the use of existing templates in
order to integrate “new knowledge”. In this terms, when a new type of resource is inserted, through the use of templates a new
node will be imported to the knowledge graph while the matching algorithm will incorporate the new details for managing the
new resource. The matching process is based on a machine learning algorithm (CLMS GIS9) which will be evaluated against
the existing data in the knowledge graph.
The design of the i-symbiosis platform also concerns the enhancement of monitoring the synergies process. The added
value to the monitoring will be the enablement, in a more active fashion, of the role of facilitator (CLMS GIS8). The facilitator
(i.e. the platform) is obliged to monitor a synergy from its start and provide continuous guidance to the involved industries. It is
also be assigned with the role of handling deadlocks through the synergy collaboration and confirm the end of a synergy either
successful or not. These responsibilities are extremely critical during a synergy and CLMS is mostly oriented to not fully
automate them. A third party, e.g. the responsible municipality of the two interesting companies may be in charge for
executing the activities of the facilitator and the platform will be assisting it.
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Proceedings of CBI 2016 Industrial Track
Goal CLMS G1
To provide
integrated applications
Goal CLMS G2 Goal CLMS G3 Goal CLMS G9
To support the clientele throughout To assist different enterprise To design new modules
the delivery of services domains for existing systems
Goal CLMS GIS1
Goal CLMS G16 Align with the key concepts and
To maintain the delivered goals of IS
applications up to date
Goal CLMS GIS2
Introduce to each industry the
ability to exchange resources
virtually
Goal CLMS GIS3
Introduce a web platform for
Industrial Symbiosis (IS)
Goal CLMS GIS5 Goal CLMS GIS6 Goal CLMS GIS7 Goal CLMS GIS8
Enable matching between Design a resource repository Introduce a functional user Introduce monitoring of
partners following IS relevance interface Synergies
Goal CLMS GIS9 Goal CLMS GIS10 Goal CLMS GIS11
Introduce the matching Introduce knowledge graphs Introduce the role of facilitator
algorithm technologies
Goal CLMS GIS12 Goal CLMS GIS13
Introduce a context dependent Introduce real data of
environment resources
Goal CLMS GIS14 Goal CLMS GIS15 Goal CLMS GIS16
Introduce resource context Introduce location context Introduce legislative context
awareness awareness awareness
Goal CLMS GIS17 Goal CLMS GIS18
Introduce a knowledge data Introduce patterns template for
graph for resource repository resource management
Figure 7 Goal model for i-symbiosis platform
The capability selected for further analysis and improvement where the “Enabler of web industrial symbiosis”. This
capability encompasses the CLMS capabilities and the capacity of providing a web based platform, the i-symbiosis platform.
This is shown schematically in Figure 8. CDA in this application is the i-symbiosis platform, which is developed with
zAppDev. CDA is communicating with the CNA application where adjustment information is exchanged. In our case CDA is
also functioning as a data provider to CCP by continuously sending data to the context platform.
Figure 8 i-symbiosis platform linked to the CDD environment
Based on the three contextual factors that can affect the industrial symbiosis (location, resources, legislation), we analyze
three scenarios where the CDD tools should enable the monitoring and enhancement of the existing capabilities. In each
scenario, CDD tools will help in three different levels: automated adjustments, semi-automated adjustments and manual
adjustments. The three scenarios led to the identification of three sub-capabilities, see Figure 9.
The combination of i-symbiosis platform with the CaaS tools is represented in Figure 10.
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Proceedings of CBI 2016 Industrial Track
Figure 9 Overview of the four identified capabilites of the i-Symbiosis platform
Resource CCP CNA CDA
(i-Symbiosis
context
platform)
Location
context Run time
Measurable adjustment
Legislation properties information
context
Figure 10 CDD tools and the i-symbiosis platform
4.3 Semi-automated Adjustments towards Resource Monitoring
In this section we will demonstrate one of the three scenarios identified which is about applying semi-automated adjustments
towards resource monitoring.
4.3.1 Design and Analysis with the CDD Concepts
The “Resource description and classification” capability enables the detailed description of resources in order to enable a better
match between organizations.
The CDA of i-symbiosis according to the industrial symbiosis process is checking the compatibility of resources during the
match making procedure. The successful resource compatibility is essential for every possible synergy between two
organizations. The description of resources to exchange can impact the number of possible synergies (matches). If the quality
of the resource descriptions is low, there will (eventually) be difficulty to perform matching/create synergies. This in turn will
eventually lead to the loss of the capability. The effect of using CDD in resource monitoring would be the early detection of
loss in matching power.
The context, in terms of resource description and number of successful matches, can be monitored (using CCP and CNA).
This could trigger a manual procedure for capability re-design if the values are below a certain level. For example, the
attributes for describing the resource may need to be changed manually.
Similar to the first scenario, TABLE 2 describes the basic CDD concepts for this resource monitoring scenario.
TABLE 2 CDD concepts for the 2nd Scenario
CDD Use Case
Concepts
Capability Capability 1:Enabler of Web Industrial Symbiosis
Capability 1.2: Resource description and classification
Goal Create and support a network for Industrial Symbiosis
(Capability 1)
Hava a high quality of the resource descriptions (Capability
1.2)
KPIs Number of matches per entered resource
Number of attributes used per resource matching
Context Context Context Measurable
element elements Properties
range
Poor (0- Matching health Relative amount of
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Proceedings of CBI 2016 Industrial Track
CDD Use Case
Concepts
20%), successful matches
Stable (20-
50%),
Good (50-
65%),
Very Good
(65-100%)
Process
Process P1) Unchanged process (see above)
Variants P2) Introduce a manual design process to improve the
resource description. This process could be triggered by a
poor matching health.
4.3.2 Implementation with the CaaS Tools
For the i-symbiosis platform, the initial concept is to be able to check the compatibility of resources during the match making
procedure. The successful resource compatibility is essential for possible synergy between two organizations.
The description of resources to exchange can impact the number of possible synergies (matches). If the quality of the
resource descriptions is low, there will (eventually) be difficult to perform matching/create synergies. This in turn will
eventually lead to the loss of the capability. The effect of using CDD in resource monitoring would be the early detection of
loss in matching power.
By using the CDD approach the context, in terms of resource description and number of successful matches, is monitored
(using CCP and CNA). This triggers a manual procedure for capability re-design if the values are below a certain level. For
example, the attributes for describing the resource may need to be changed manually.
Figure 11 shows the proposed technical implementation for this scenario.
In the architecture, the following interactions occurs:
• The CDA continuously send information about the number of successful matches to the CCP. This is done
through a data provider.
• The CCP send the context information further to the CNA.
• The CCP send the context information to the CNA.
• The CNA can, based on the context information, calculate if the information deviates from a certain set
threshold. For this implementation an adjustment calculation will be implemented in the CNA. This is done
to use the CNA adjustment features.
• A manager can use the CNA to monitor indicators related to the matching information. This is done to ensure
that the system is running according to the set business goals.
CLMS
CCP Context information
(aggregated) CNA Indicator
Adjustment Indicator monitoring
(calculation) display
Manager
Context information
• Relative amount of
successful matches Data Matching CDA
provider algorithm (i-symbiosis
platform)
Figure 11 Overview of the technical architecture for resource description
The calculation of the relative amount of successful matches was implemented using a data provider in the CDA. CDA (i-
symbiosis platform) has an implemented API REST service that sends, with interval time set to 1 day, the percentage of
successful matches achieved. The threshold for monitoring this amount was 25%. Therefore the context element range for our
context element CE2: Amount of successful matches was set in 25-100%. If the amount is within the specific range the status
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Proceedings of CBI 2016 Industrial Track
of capability in the CNA is shown as “working”. Otherwise a red indication is shown where the status is represented as “not
working” (see in Figure 12).
Figure 12 CNA context element for monitoring matches
The CNA indicator display for the specific context element “Amount of successful matches” is shown in the figure below
(Figure 13).
Figure 13 CNA dashboard display amount of successful matches
5 Lessons Learned
This paper presents the analysis and initial capability designs of the industrial symbiosis (i-symbiosis) application at CLMS.
The i-symbiosis business application is realized by the zAppDev Model Driven Development tool that CLMS owns and uses
for collaborative information system development for its customers. The use case at CLMS hence exemplifies a business
scenario when an organizational capability (industrial symbiosis) needs to be supported by a custom-made capability delivery
application (i-symbiosis platform).
The analysis and implementation presented in this paper lead to interesting points for discussion.
The capability driven analysis of CLMS on a business level defined their strengths and ‘possessions’ in terms of resources,
setting of business goals and identification of business processes. The declaration of their capabilities and the kinds of
technologies that are currently using led into how those capabilities turn into a business output for them. The business analysis
was also useful for identifying how the available technologies can be combined and how flexible their software development
environment is, to adopt new ones.
We realized that the setting of business capabilities can be further analyzed to the sub capabilities of each use case or
business output served by CLMS.
The selection of i-symbiosis platform as the exemplary work was not selected by chance. CLMS intended to create the
platform in a way that the context aspect of the industrial symbiosis theory is included to the design and implementation phase.
CDD methodology and the tools provided within the CaaS project, takes into consideration the context awareness.
During the analysis of i-symbiosis use case, the CDD methodology contributed to the definition and evaluation of the
assets, capacities and abilities that CLMS possess in general. The thorough description of their business capabilities brought to
the forefront the unique elements and features that their software development tool, zAppDev, has to offer. zAppDev is an
innovative web-based software development tool for developing integrated and complete software solutions and applications
The fact that it is an MDD tool made the analysis even more interesting, since zAppDev already embraces various elements of
this particular methodology regarding the CDD phase.
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Proceedings of CBI 2016 Industrial Track
Model driven environments share common ground with the CDD concepts since they are both aligned with various
modelling concepts. It is only logical to further examine their interrelationships and any correspondence of concepts in order to
combine their individual characteristics into an integrated approach. However, the models used in CDD have a focus on
describing capabilities, their contexts, goals etc., while models developed according to the MDD principles focus on
components of software systems, such as, data objects, information management procedures, user interface components etc.
CDD does not include specific methods and tools for the detailed creation of information systems. Thus, combining the CDD
approach with MDD gives the possibility to have support for capability analysis and monitoring (provided by CDD) and the
detailed implementation of information system (provided by MDD).
The overall aim of using zAppDev or similar MDD tools in congruence with CDD is to support its applicability to
enterprises that require capability designs but lack software to achieve context dependent capability delivery. To address
dynamic requirements of today’s business environments, one should go beyond static design of services that are aligned to
organizational objectives and business requirements. It is our premise that the confluence of MDD and CDD offers many
advantages to the alignment of businesses and IT solutions.
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