USING A DEPTH TREE FRAMEWORK TO EVALUATE

CHANGE IMPACTS OF MODIFICATIONS TO IT

INFRASTRUCTURE

Yang Min

, Zhang Mi

, Han Peng

, Chen Haiguang

, Zhou Xi

, Mao Dilin

, Gao Chuanshan

1,2,3,4,5,6,7

Department of Computer Science and Engineering, Fudan University, Shanghai, P.R.C, 200433

Keywords: Depth Tree Change IT Infrastructure.

Abstract: In a business IT system, change is an engine of progress, as well as a source of doom. End user applications,

operational disciplines, and IT vendors are major sources of continuous change. However, application

software change control is a relatively mature process; many organizations implement IT infrastructure

change manually, relying primarily on the IT staff's knowledge and expertise. Thus, an effective and

efficient way to settle it is urgently needed. In this paper, we take a necessary first step toward the change

management of IT infrastructure. Mainly along with utilizing a depth tree, termed with DTM in the

following, to qualitatively get hold of the sequence of affected parts of IT infrastructure and trace the

detailed propagation paths, it can also be relatively accurate to evaluate the quantitative influence to each

implicative part and provide its benchmark-values corresponding to industrial experiences in business and

techniques for the decision-makers.

1 INTRODUCTION

IT Infrastructure Change Management is primarily

driven by increasing business requirements

especially in recent years (Jean-Pierre Garbani,

2004). However, application software change

control is a relatively mature process; many

organizations implement infrastructure change

manually, relying primarily on the IT staff's

knowledge and expertise.

The industry is focused on how the infrastructure

reacts to that change while each corporation has its

unique system for each own business process. That’s

why ITIL (IT Infrastructure Library) is developed,

which is a framework of an integrated set of

processes that are designed to provide best practice

in the support and delivery of IT services, while

change management framework can be defined as

that integrated set of processes, standards and

supporting tools that facilitate the management of

the application of changes to IT Infrastructure (Mark

Nicolett,Debra Curtis,2002). But it is only the

guidance on the process of change management

rather than the total solution on this problem, even

not a methodology dealing with it.

Meanwhile, companies need a methodology to

analysis the propagation progress of Change Impact

qualitatively and quantitatively. Also, it should be

able to produce the sequence of the affected parts of

IT infrastructure and trace how change ripples

corresponding to the process of change impacting

propagation as well as to calculate the impact more

accurately than that envisioned.

The rest of this paper is organized like this:

section 2 presents the related work and endeavor

both in the academy and the industry; section 3

offers the formulation models of IT Infrastructure

with the help of ADS and algorithms using

dependency analysis to construct the depth tree;

section 4 addresses our conclusion and the future

work.

2 RELATED WORK

According to ITIL (Colin Rudd,2004), a single

centralized Change Management process, for the

efficient and effective handling of changes, is vital

to the successful operation of any IT organization.

Changes must be carefully managed throughout their

entire lifecycle from initiation and recording,

Min Y., Mi Z., Peng H., Haiguang C., Xi Z., Dilin M. and Chuanshan G. (2006).

USING A DEPTH TREE FRAMEWORK TO EVALUATE CHANGE IMPACTS OF MODIFICATIONS TO IT INFRASTRUCTURE.

In Proceedings of the International Conference on e-Business, pages 88-92

DOI: 10.5220/0001427000880092

 SciTePress

through filtering, assessment, categorization,

authorization, scheduling, building, testing,

implementation and eventually their review and

closure. The kernel issue of change management of

IT infrastructure is to assess the impact of a

proposed change in the entire system and to evaluate

the benefits and costs on the initial and consequent

modifications. In industry, there are several leading

companies, such as IBM, HP, Remedy, CA, etc, are

hammering at this issue. The gap between business

requirements and IT services is the big challenge

that it is hard to describe the hand-on consequence

because of the change.

Nevertheless, in academy, as commonly believes,

traditional impact analysis approaches based on

program slicing (M.Weiser,1984) (S.

Horwitz,T.Reps, etc,1993) and program dependence

graphs(R.Al-Zoubi and A.Prakash,1995) (J.Loyall,

etc,1993)(A.Podgurski, etc,1990). And almost all of

these works were studied in the context of

conventional programming language, while fewer

focused on the IT infrastructure especially in recent

years. According to Zhao (Jianjun Zhao,1997), most

of the results presented above are derived from the

study of small commercial systems or even of

systems developed in course assignments instead of

the realistic IT environment. So, the existing

academic methods need further work to apply to real

large-scale system because of the different

characteristics. IT infrastructure contains

complicated mixtures of software and hardware and

anfractuous relationships while these academic

works would rather engage in the hierarchy

relationships between interfaces or classes in a

program/application. (Jun Han,1997) (M.Ajmal,

etc,1999) (Jianjun Zhao,1997) may allow for the

software architecture in the software engineering

environment, and they all made great efforts to

analysis the dependences in software architecture,

which give the hints to evaluate change impact. All

these works focus on the impact relationship

analysis, but do not evaluate the quantitative

influence to each part of software architecture

indeed because the model they used can only

represent the qualitative relationships. Thereby, a

model to describe the implicative parts elaborately is

necessary that the rippling effect spreading abroad in

a quantitative manner among the IT infrastructure

can be evaluated. Meanwhile, the model would help

to leverage the gap between the business

Figure 1: ADS-View of a scrap of the sample IT infrastructure.

USING A DEPTH TREE FRAMEWORK TO EVALUATE CHANGE IMPACTS OF MODIFICATIONS TO IT

INFRASTRUCTURE

requirement and IT service and formalize the

propagation by abstracting the invoking

relationships between different business functional

operations as will be descried in section 3.

3 DTM: ELEMENTARY

METHODOLOGY TO

EVALUATE CHANGE IMPACT

OF IT INFRASTRUCTURE

3.1 Modeling IT Infrastructure in

DTM

3.1.1 General Architecture Description

Standard - ADS

The complicated IT infrastructure is composed of

numerous applications, middlewares, operating

systems, mainframes, servers, LAN devices, etc.

ADS (Ed Kahan,2005) is initiated to take advantage

of the industry experiences gained over the last few

years exploration. The semantic specification aims

to provide the clear and unambiguous definition of

the concepts involved in modeling certain aspects of

the architecture of IT system.

As figure 1 intercepted from (Ed Kahan,2005)

shows, a commonly accepted structure for

metamodeling is the four layer metamodel hierarchy,

on which among UML is based. According to ADS:

Infrastructure: the system being modeled.

M1 layer: this layer contains the concepts that

represent things from the system being modeled. It is

referenced to as a model layer.

M2 layer: this layer contains the meta-concepts.

All models are built from instances of these meat-

concepts. This layer is referenced to as a metamodel

layer.

M3 layer: this layer contains the meta-meta

concepts. All metamodels are built from instances of

these meta-meta concepts. It is referenced to as a

meta-metamodel layer.

With this specification, we can accurately abstract

and model the infrastructure according to the

algorithm through finely defining each functional

sub-system as well as its dependency relationships

and its attributes, just illustrated as figure 2.

3.1.2 The Formulation Model of IT

Infrastructure

In this section, we will formulize the IT

infrastructure with the following rules so that DTM

can build up a formulation model utilizing ADS, and

then DTM can evaluate the change impact easily and

automaticly throughout the model.

Figure 2: M3 Layer of ADS-view of IT Infrastructure.

Definition 1: Base Functional Unit (BFU)

It is a functional operation, which will serve

others through its specific interface, no matter

whether it is a software unit or hardware unit or

admixture of both. And it will be finely defined at

the beginning of forming ADS-description of the

whole IT infrastructure when modeling, with the

suitable granularity according to the business logic,

which depends on the experiences and skills of the

architect. And it will be mapped into the concepts of

M1 layer, as the figure 1 illustrates.

Definition 2: Component

It is a logical entity composed by one or more

functional operations, as figure 3 shows, which

involves: Applications; Subsystem; Mainframe;

Server; Storage; LAN devices; Or Combination

made up of several other components.

Suppose A is a component, then: A={ a

, a

,……, a

}, while a

is a component either.

The Base Functional Unit (BFU) is regarded as

the atomic component, which means not to be

composed by any other components. As defined in

Business Functional Operation:

Customer

Management

Integrated

Services

Product

Services

System

Management

Integrated

Count

Inquiry

Provider/

Copartner

Management

Com_

Com_F

Com_E

Com_

Existing

Subsystem

Increased

Subsystem

Existing

Dependency

Increased

Dependency

Existing

Server

Increased

Server

Com_B

Web Component

Com_C

Com_D

Com_E

Com_FCom_GCom_H

Com_A

Com_B

Com_I

ICE-B 2006 - INTERNATIONAL CONFERENCE ON E-BUSINESS

definition 1, each of the six units would not be

decomposed into a smaller granularity.

In this case, we will call a

is A’s sub-component

while A is a

’s sup-component. A component will be

mapped to the M1 layer. Typically, an order

processing sub-system, including the application

server, os and the hardware server, will be regarded

as a component which may be composed by several

different business operations.

Definition 3: Input and Output of a component

To component A, it will have Input and Output of

a RequestForCapacity, and we describe that as F

(A)

and F

out

(A), which will be formed as a n-vector like

,……,i

}. Each one in this vector represents for

one attribute of a business functional operation.

Figure 3: Component.

Input:

It represents the parameters of each business

operation called by the other components. For

example, a typical input for an order processing sub-

system will be like,

Output:

It represents the parameters of the other

components called by its business operation.

Utilizing input and output, implicative components

can build up relationships. When change occurs, the

numerical values of input and output will be updated

according to the rippling sequence, then after the

propagation ends, based on these parameters of

input, the calculation of the benchmark-value, such

as TPmC (Typically Used for a DB server),

SPECjbb (Typically used for applications reside in

an application server), will be relatively accurate

according to the industry experience. The variation

of the capacity of each affected part can be evaluated.

Also, we suppose the parameters have been defined

by ADS at the M1 layer.

ADS would give the specific RequestForCapacity

for each base functional unit as well as for each

component, which represents for the standard Input

and Output. Besides this, they should agree with

following expressions:

(A)

⊆

∪ F

), F

out

(A)

⊆

∪ F

out

)

When we compose several components, we can

get the Fin and F

out

of the sup-component from F

and F

out

of each sub-component according to the

environment.

Assumption:

Each RequestforCapacity of Input and Output of

the components is finely defined as attributes in

ADS-view. Indeed, it’s business-specific. They are

tightly associated to the specific functions of the

components and also they will be defined by the

architect according to the estimative capacity of

design requirements of the correlated components,

such as a vector (total number of users, type of

business operations, percent of each type, response

time, maximum concurrent users, java operations,

number of standard transaction).

Definition 4: Dependency Relationship R:

A R B represents that component A has a direct

influence to component B which means there are

connections between the input and output of these

two components respectively. That is:

A R B = { (a

) |

∃

(f∈ F

out

) ∧ f∈ F

)), a

∈ A,

∈ B }

If given A, B, C, while

∃

(a,b)

∈

A R B and (b,c)

∈

B R C, then we think that A has a indirect impact

to C. Typically in IT infrastructure, A R B, means

there exists a part of A calling functional services of

some part of B. As an indirect impact, the called

functions of some part of B will need the services of

some part of C while fulfilling A.

3.1.3 The Key Algorithm of DTM

Methodology: Creation of a Depth

Tree

Using the enterprise model, the paper has developed

a methodology named DTM, which takes the

rippling effect of change impact propagation

progress into careful consideration, to analyze the

impact of the change to the whole infrastructure..

Algorithms pseudo-code:

1. Create the Initial Tree T : root

node rt with depth Å0 and its

directly impacting nodes A[1…n] with

each depthÅ1;

2. i Å1

3. CURRENT_NO Å n

4. REPEAT

a) jÅ1

b) WHILE (j<= CURRENT_NO)

i. a

Åone of the component at ith

depth

ii. IF(a

directly impacting nodes

B[1…m])

USING A DEPTH TREE FRAMEWORK TO EVALUATE CHANGE IMPACTS OF MODIFICATIONS TO IT

INFRASTRUCTURE

THEN FOR t Å 1 to m

IF ( B[t]

∉

T )

[Add B[t] to T]

[Set depth of B[t] Å i+1]

ELSE IF !(Check Dependency Loop

from a

to B[t])

[Add B[t] to T]

[Update depth of B[t] Å i+1]

[Update depth of B[t]’s sub

tree]

ELSE

[Exit]

iii. j++

c) i++

d) CURRENT_NOÅthe number of

components at the ith depth

5. UNTIL CURRENT_NO = 0

6. RETURN T

4 CONCLUSIONS AND FUTURE

WORK

All of IT Infrastructure Change Management want to

do is about proactive, efficient and effective use of

all its resources for the requirements when changes

occur. In this paper, we present our method named

DTM to cope with the problem that changes to IT

infrastructure bring down on. And also we

implement it to the typical case of IT infrastructure.

The results show that DTM works. It provides

decision-makers with the sequence of affected

components when change occurs and propagates and

the quantitative evaluation of the impact to each

affected components using functional equations

gained from industrial experiences as well. Based on

the result, we can easily know where the critical

point of the infrastructure is when some specific

change should be put into practice and how much

the whole infrastructure is influenced. Thus, we link

up the business requirements and IT services

ingeniously and leverage the gap between them by

abstracting the invoking relationships between

different business functional operations.

In the future, we will implement DTM to some

realistic industry companies and consummate it with

much more calculation equations suitable for

different systems and platforms including varieties

of hardware. Then we will develop a tool to support

automation change managements, especially offer

decision-makers with change plans according to

business requirements and impacts analysis of

change implementation.

ACKNOWLEDGEMENTS

The Conference Participation is supported by Nokia

Bridging the World Program.

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ICE-B 2006 - INTERNATIONAL CONFERENCE ON E-BUSINESS