Modelling and Enterprises

The Past, the Present and the Future

Vinay Kulkarni

, Suman Roychoudhury

, Sagar Sunkle

, Tony Clark

and Balbir Barn

Tata Consultancy Services, Pune, India

Middlesex University, London, U.K.

Keywords: Modelling, Meta Modelling, Model-Driven Development, Enterprise Systems, Adaptation, Analysis,

Simulation.

Abstract: Industry has been practicing model-driven development in various flavours. In general it can be said that

modelling and use of models have delivered on the promises of platform independence, enhanced

productivity, and delivery certainty as regards development of software-intensive systems. Globalization

market forces, increased regulatory compliance, ever-increasing penetration of internet, and rapid advance

of technology are some of the key drivers leading to increased business dynamics. Increased number of

factors impacting the decision and interdependency amongst the key drivers is leading to increased

complexity in making business decisions. Also, enterprise software systems need to commensurately change

to quickly support the business decisions. The paper presents synthesis of our experience over a decade and

half in developing model-driven development technology and using it to deliver several business-critical

software systems worldwide.

1 INTRODUCTION

Business applications typically conform to a layered

architecture wherein each layer encapsulates a set of

concerns and interfaces with adjoining architectural

layers using a well-defined protocol. Typically, the

architectural layers are wired together by

middleware infrastructure that supports message

passing in a variety of architectures such as

synchronous, asynchronous, publish-subscribe etc.

As a result, developing a distributed application

demands wide-ranging expertise in distributed

architectures and technology platforms which is

typically in short supply. Large size of application

further exacerbates the problem. Moreover,

documenting critical design decisions is always

sacrificed at the altar of delivery deadlines.

Therefore maintenance of such systems becomes a

nightmare especially when some key members have

to leave the project or have to revisit a part of the

system that have not received attention for a long

time (Naur, 1985).

To address some of the challenges mentioned

above, we have been applying MDE techniques for

developing database-intensive enterprise systems

using high-level models (Kulkarni and Reddy,

2008). These models capture some of the critical

design decisions along multiple dimensions namely

functionality, technology and architecture. A set of

code generators transform these high-level models

into low-level implementation encoding the various

design decisions suitably. Thus, models help to shift

the focus of application development from code to a

higher level of abstraction promising enhanced

productivity and quality.

In the remaining part of the paper, we begin by

taking a look at the extent to which modelling is

practiced in enterprises today and various uses these

models are put to. We then discuss what sorts of

models will be required to meet the needs of future

enterprises and what uses can they be put to. Finally

we conclude by presenting an analysis of key

investigations necessary for realizing a model-driven

enterprise.

2 THE PAST

Models-as-pictures has probably been the most

common and widespread use of modeling techniques

in enterprises. Here, models provide a common

language for bridging business domain and software

Kulkarni V., Roychoudhury S., Sunkle S., Clark T. and Barn B..

Modelling and Enterprises - The Past, the Present and the Future.

DOI: 10.5220/0004310700950100

In Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development (MODELSWARD-2013), pages 95-100

ISBN: 978-989-8565-42-6

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

development worlds (Hailpern and Tarr, 2006).

Models-as-high-level-specifications has recently

witnessed increased following among practitioners

(Hailpern and Tarr, 2006); (Hutchinson et al., 2011).

Multiple variants of this usage are noticed, for

instance, Models are automatically transformed to

derive partial implementation to be taken to

completion using code-centric development

processes (known as code completion) with models

forgotten hereafter or maintained so that changes

introduced during code-completion can be taken

back automatically to models (known as round-trip-

engineering) (Medvidovic et al., 1999); and

complete implementation is derived from models

through model-transformation with models

remaining primary SDLC artefacts (Kulkarni and

Reddy, 2003). Models-as-executable-artefacts is the

least common of all usages and that too in niche

domains of life-critical systems (Rumpe, 2004).

Enterprises use IT systems principally to obtain

mechanical advantage through automation of

repetitive processes/tasks. As enterprises have

traditionally valued stability, IT systems have been

designed/architected so as to result in low

maintenance costs. The underlying assumptions

being: requirements of the IT system are fully

known a priori and they are unlikely to change

significantly during the lifetime of the application

(complete-knowledge-hypothesis). Change requests

are assumed to be few and far between, and each

change is assumed to have small ripple effect.

Therefore, high analysis/design cost for IT systems

is justifiable and acceptable as long as the

maintenance cost remains a tiny fraction of the

former. Under complete-knowledge-hypothesis it is

possible to know about foreseeable enough future

and encode this knowledge into the implementation

of IT systems using techniques such as

parameterization, decision look-up tables, lazy

instantiation, delayed binding etc. Thus, it shouldn’t

come as a surprise that Models-as-high-level-

specifications approach remains the most widely

adopted MDE approach by industry practice. Here,

the focus had been on coming up with modelling

languages (metamodels/DSLs etc) that are necessary

and sufficient for automatic derivation of IT system

implementation there from (France and Rumpe,

2007).

Model-based code generators compile the model

specifications into a desired implementation using

model-to-model (QVT, 2011) and model-to-text

(MOFM2T, 2008) transformations. The proven idea

of retargetable code generation helps deliver the

same model into multiple technology platforms as

long as care is taken to keep the model agnostic of

platform concerns. Moreover, model-to-model and

model-to-text transformation specification languages

enable declarative specification of a model-based-

code-generator which can either be interpreted for

code generation or execution (Kulkarni and Reddy,

2008).

3 THE PRESENT

Globalization forces and increased connectedness

have led to increased business dynamics and

shortened time-to-market windows for business

opportunities. Thus, IT systems designed for

operation in an inherently stable environment are

becoming a misfit (Truex et al., 1999). Moreover,

we discovered that no two applications, even for the

same business intent such as straight-through-

processing of trade orders, back-office automation of

a bank, automation of insurance policies

administration, etc., are identical. Though there

exists a significant overlap across functional

requirements for a given business intent, the

variations are manifold too.

Software Product Line Engineering (SPLE)

attempts to address these needs by shifting the focus

of application development from ground-up coding

to assembly of pre-defined components (Kang et al.,

1990). The idea is to identify what changes where

and when in system functionality – the what leads to

the variations, the where leads to the variation

points, and the when leads to internally consistent set

of what-to-where bindings. However, IT systems

tend to vary along multiple dimensions -

functionality, business process, extra-functional

characteristics, and implementation platform to

name only a few (Kulkarni and Reddy, 2003).

Therefore, the notion of ‘what changes where and

when’ needs to be addressed along every dimension

and then across them all at the application level. In

theory, all it means is to define Meta Object Facility

describable metamodels for each dimension but, as

of now, there is no evidence of this issue being

addressed at industry scale. In fact, modeling of/for

extra-functional characteristics is pretty much in

infancy and variability management as well as

composition concerns are yet to be properly

addressed for business processes though some work

is reported (Kulkarni and Barat, 2010) (Barat and

Kulkarni, 2011). Though feature model has become

a popular notation for describing variability (Kang et

al., 1990), there is no handle on tracing features to

application specification and/or implementation

MODELSWARD2013-InternationalConferenceonModel-DrivenEngineeringandSoftwareDevelopment

artefacts. Ideally, feature should be a first class

concept in realizing product lines so that all software

development life cycle (SDLC) phases can be

feature-centric (and hence time- and effort-optimal)

and it should be possible to compose application

specification/implementation from feature

specification hierarchically ad infinitum (Sunkle,

2011). Enterprise IT systems constitute an ill-

defined or hard-to-be-fully-defined space. As a

result, complete-knowledge-hypothesis, the

cornerstone for SPLE, does not hold. Therefore,

there is a need to support product-line-by-evolution

as opposed to product-line-by-design (Kulkarni,

2010); (Kulkarni et al., 2012).

4 THE FUTURE

4.1 Modelling Language Engineering

Platform

From our past experience in delivering enterprise

systems we have found that no two enterprises are

exactly alike; it was not possible to meet their

functional demands - even for identical business

intent such as an order processing system for a

financial services organization, policy administration

system for an insurance organization, retail banking

system for a bank, etc., - with one software system.

In traditional code-centric approaches, it would

mean introducing suitable changes in a copy of the

implementation. In a model-driven approach, it

means introducing changes in the various models,

metamodels and the model-based code generators.

Thus, the problem of evolutionary maintenance of

application code gets transformed into evolutionary

maintenance of models, modeling languages and

model-processing infrastructure, and hence the need

for a modeling language engineering platform. For

want of space, we direct readers to (Kulkarni et al.,

2012) for details of the platform.

Much of the core technology to implement such

a platform is already available. For instance, Eclipse

can provide the backbone plug-in architecture for the

platform. Eclipse's eCore is a good starting point for

the reflexive meta metamodel. Text-based (meta)

model editors can be realized with little

modification, if at all, to the various model editors

available. OMG QVT (QVT, 2011) and OMG

MOFM2T (MOFM2T, 2008) should suffice as

specification languages for model-to-model and

model-to-text transformation respectively. Both have

many implementations available - licensed as well as

freeware variety. In OCL (OCL, 2012), there exists a

sophisticated declarative mechanism to specify

model constraints. However, it is possible to imagine

a situation where a new constraint specification

language seems appropriate. Therefore, the platform

should have the capability to define another

constraint specification and execution mechanism.

The proposed modelling language engineering

platform will provide the minimal tooling

infrastructure for improving productivity of current

MDE practitioners. Also, its existence is likely to

make MDE enthusiasts to 'take the plunge' so to say.

The high level of standardization should help

develop MDE community for and around the

proposed platform. We believe development (and

continuous maintenance) of the proposed platform is

best supported through open source community

model.

4.2 Towards Formal and Precise

Enterprise Architectural Modelling

Economic and geo-political uncertainties are putting

increasingly greater stress on frugality and agility of

enterprises. Large size and increasing connectedness

of enterprises is fast leading them to a system of

systems which is characterized by high dynamics

and absence of a know-all-oracle. Multiple change

drivers are resulting in increasingly dynamic

operational environment for enterprise IT systems,

for instance, along Business dimensions the change

drivers are dynamic supply chains, mergers and

acquisitions, globalization pressures etc., along

Regulatory compliance dimension the change

drivers are Sarbanes Oxley, HiPAA, Carbon

footprint etc., and along Technology dimension the

change drivers are Cloud, smartphones, Internet of

things etc. At the same time, windows of

opportunity for introducing a new

service/product/offering and/or for adapting to a

change are continuously shrinking. Furthermore,

business-critical nature of IT systems means the cost

of incorrect decision is becoming prohibitively high

and there is very little room for later course-

correction. Therefore it is important that we look

beyond the traditional model-based generative/SPLE

based techniques that we have been using in the past

and put more emphasis on understanding of the

target organizational environment including its

business, IT systems, and stakeholder perspectives.

In other words, model the whole enterprise. Formal

and precise enterprise architecture modelling is an

important step towards realizing this goal.

To translate business vision and strategy into

effective enterprise change by creating and

ModellingandEnterprises-ThePast,thePresentandtheFuture

communicating the models centered on business and

IT, a set of techniques are used, referred to as

Enterprise Architecture (EA) techniques (IEEE

1471, 2000). Irrespective of the architectural

methodology followed by an EA technique, there

exist a few shortcomings in current EA techniques.

Architectural artefacts in current EA techniques are

only documents used as reference material by

enterprise architects to communicate with various

stakeholders for achieving goal such as Business-IT

alignment. These models are not machine-

manipulable. An enterprise architect is supposed to

use these artefacts and his knowledge and

experience in achieving enterprise-specific goals.

None of the available EA techniques provides a

mechanism to evaluate the technique itself as it is

applied to an enterprise. Some EA frameworks

provide an assessment framework, but its use is

again dependent on the knowledge and experience of

the enterprise architect. This means that there is

really no guarantee that these techniques will lead to

correct EA.

These and other observations make clear that

applying these EA techniques to an enterprise is a

highly person dependent activity with complete

reliance on the enterprise architect’s knowledge and

experience. Furthermore, validation of goals, such as

business-IT alignment, is carried out in a blue-print

way in current EA techniques (Wagter et al., 2012).

It means that if the enterprise architect feels, based

on his knowledge and experience, that an enterprise

has been architected according to principles laid out

by these EA techniques; then goals such as business-

IT alignment have been accomplished by definition.

An enterprise may also strive for other goals such as

adaptability or cost optimality, for which no

mechanism is provided by current EA techniques to

prove that a property is satisfied across the

enterprise.

Also, the as-is state of an enterprise captured in

current EA techniques is not machine-manipulable.

The various means of architectural description rely

on the expertise of the enterprise architect to provide

a path to the desired to-be state of the enterprise

(Rolland et al., 1999). Essentially, the problem with

regards to enterprise modeling boils down to - what

help can be provided so that relatively less

experienced person will be able to function at the

level of an experienced and knowledgeable

enterprise architect in applying EA techniques to

enterprises?

4.3 Enterprise Adaptation

With enterprises having to become increasingly

dynamic, their supporting IT systems are becoming

increasingly complex. Ever-shortening window of

opportunity means supporting IT systems need to

adapt quickly. Business-critical nature of IT systems

means there is no room for an error in what should

the adaptation be and how should it be effected.

Software engineering community has been focusing

on mechanisms to support the latter, but, as of now,

the former is still the preserve of gurus. Given the

size and complexity of typical enterprises, even

experts find it difficult to determine which

adaptation would be the best response, as per the

chosen criterion, for a given set of changes.

Therefore, we strongly believe that modeling

community should focus on providing help so as to

make this problem more scientific and hence

tractable.

Ideally, the more automatically a system can

adapt, the better, but, given the nature of enterprise

IT systems, it seems hard, at least as of now, to

imagine all adaptations being automatic. Adaptation

under human supervision seems a more pragmatic

solution. Investigations on the role of software

engineering for self-adaptive systems (Cheng et al.,

2009); (Lemos et al., 2011) have emerged in the

recent past. These investigations reveal two broad

lines of attack: one applying control-theoretic ideas

of model reference / mode identification adaptive

control (Brun et al., 2009) and the other applying

adaptation techniques from biology (Brun, 2008).

Both have key dependence on the ability to sense

changes in the environment. To summarize, some of

the key questions that should be investigated to

model enterprise adaptation are: What are the

dimensions of adaptation with respect to functional

or non-functional requirements? What are the

adaptation architectures for business applications,

business processes and the context (e.g.,

Goal/Decision/Component based) (Sykes et al.,

2008)? How to design MAPE-K (Jacob, 2004)

feedback loop for Business, IT and Infrastructure

planes? How to determine the ideal adaptive

controller (i.e., control theoretic, biological or

hybrid) that is best suited for a typical business

need? Can the required Sensors interface be fully

realized using underlying middleware and operating

system level sensors augmented with

instrumentation of IT systems?

MODELSWARD2013-InternationalConferenceonModel-DrivenEngineeringandSoftwareDevelopment

4.4 Open Issues and Possible Solution

Approaches

With regards to enterprise modelling, a key open

issue is to come up with a set of models for the

enterprise that are amenable to rigorous analysis and

simulation. Assuming, a Graph (or network)

adequately models the structural aspect of the

enterprise, the behavioural aspect can be modelled

using an event paradigm wherein nodes, as producer

and/or consumers of events, participate in publisher-

subscriber protocol. Exchange of information within

the nodes can be modelled as side-effects on a

‘global’ context and a variety of data can be

obtained through instrumentation of enterprise

system model. This leads to several interesting

questions: Can first-cut model be automatically

derived from this data? Can the desired analysis be

expressed as a set of properties, structural or

behavioural or both, of the graph? Can impact of

graph perturbations on a given property be

computed? Can the list of graph perturbations

necessary to bring a property within acceptable

value range be identified / computed?

Several results for networks with known

topology seem useful: A property for the whole

network can be computed / optimized (Nagurney,

2011); effect of perturbations such as deletion of a

node and/or link on global properties can be

computed (Nagurney, 2012); analysis support for

‘network of networks’ is claimed (Nagurney, 2012).

However, this work needs to be built further along

multiple dimensions leading to a set of questions:

How to obtain the network topology in a largely

automated manner? Can techniques pertaining to

random graph model (Erdős and Rényi, 1959);

(Barabási and Albert, 1999) suffice in arriving at

first-cut topology that can be further refined by

subject matter experts? Do agent-based ideas (Maes,

1990) help in devising an action plan so as to bring

the network back to the desired range of a given

global property after perturbation? How to simulate

‘what-if’ and ‘if-what’ business scenarios? Can

belief propagation (Kim et al., 1983) help? How to

translate inferences from analysis and simulation

into an action plan for the enterprise IT systems?

With regards to Enterprise Adaptation,

introducing MAPE-K architecture (Jacob, 2004)

across the IT systems plane seems to be a good

starting point. Presuming suitable sensors are in

place, it boils down to coming up with a way to

specify adaptation rules and mechanisms to effect

application adaptation. Event-Condition-Action

paradigm seems adequate for specifying adaptation

rules, but a key challenge is - how to ensure

adaptations are semantically correct i.e. intent-

preserving. Moreover, adaptation mechanism should

have component nature so that it is possible to

decompose application into components and

connectors both of which can be adapted

independently or in concert. Making the abstraction

first-class will help adaptation at any desired level of

granularity. There exists reasonable handle on

structural aspects of component and connector, but,

more work is required for addressing the behavioral

aspects. Plug-n-play architecture to enable open

extensibility is another topic of investigation. As

software processes are also software, application

adaptation techniques are applicable to business

processes as well (Osterweil, 1987). Therefore, the

ability to support adaptations at application as well

as business process levels seems critical for

developing dynamic business platforms (SOA,

2008).

5 CONCLUSIONS

In the past, we have embarked upon a model-driven

approach and the necessary tooling infrastructure for

development of database-centric business

applications. Our MDE endeavour has led to several

benefits such as higher productivity, uniformly high

code quality (i.e., best practices without developer

dependence) and easy retargeting to multiple

technology platforms. At present with increased

globalization and variable business dynamics, SPLE

helped us to create custom solutions for enterprises

using the notion of ‘variability’ – i.e., what changes

where and when in system functionality. However,

with highly uncertain and demanding economic

conditions in the future, enterprises would be

encouraged to investigate the concept behind

modelling an enterprise with a goal to analyse,

predict, simulate and adapt an enterprise on demand.

This paper summarized the role of modelling with

respect to enterprises looking back at our

experiences in the past to the immediate challenges

and needs of the future.

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