2009 Third IEEE International Conference on Secure Software Integration and Reliability Improvement
SSIRI 2009 Fast Abstract
Improvement of QoS in Process Centric Software Development Using ANP
A.SRIVIDYA1 K.KRISHNA MOHAN2,A.K.VERMA3
Department of Civil Engineering 2Reliability Engineering Group,
3
Department of Electrical Engineering,
Indian Institute of Technology Bombay, Mumbai – 400076, INDIA
[email protected], [email protected], [email protected],
1
under study; the second are the many sub-networks of
influences among the elements and clusters of the
problem, one for each control criterion. In the ANP, ratio
scale priority vectors derived from pair wise comparison
matrices are not synthesized linearly as in AHP.
Abstract - To find out the critical phase in the software
environment that may be responsible for more defects
than other phases involves the selection of a suitable
decision making method for realizing the goal. Among
Analytical Hierarchy Process (AHP), Fuzzy AHP and
Analytical Network Process (ANP), the latter is regarded
as a viable alternative, which yields a holistic framework
in the selection of the most critical phases in the presence
of interdependencies. A practical case study concerning
the software development for a financial application
which involves the utilization of a tool driven approach
like Rational Unified Process (RUP) is made use of to
demonstrate the effectiveness of ANP.
III. APPLICATION OF ANP TO THE CASE STUDY
A detailed experimental metric analysis of the
prototype has been performed on three different modules
(EFT, REP and SD modules) over three cycles/builds
with RUP implementation. The results obtained from the
PoC for the EFT module from RUP implementation are
first considered. They show the number of defects as
being significantly reduced in incremental cycles, based
on the data collected from a defect consolidation log. In
this paper, defects by severity type for various stages in
the software production process is considered to find out
the critical phase in the software environment that may
cause more defects than others. The phases of software
are: requirements, design, coding, unit testing, integration
system testing. These are mapped with low, medium and
high type of defects to identify the crucial phase in the
design. The criterion considered has a link to the
alternatives to indicate the flow of influence from the
criterion to the alternatives. Once the feedback network
model is set up, pair wise comparisons have been made.
They indicate the relative amount of influence that flows
from one element to each of the other elements. For each
and every pair wise comparison matrix, eigen values and
eigen vectors are found. The relative values of eigen
vectors are calculated to obtain the weighted vectors
(adding all the eigen vector values to get the sum and
dividing each eigen vector with the sum giving the
required weight vector). Pair wise comparison matrix of
the three types of severity of defects w.r.t the various
phases is done. Also done are pair wise comparisons of
the phases of SDLC w.r.t low, medium and high severity
of defects. The consequent super matrix shown in Table 1
is constructed by using the vector weights for the
alternatives with respect to each criterion, and the vector
weights of the criteria with respect to each alternative.
The results of feedback network model are then assessed.
Key words: Analytical Network Process, Rational Unified Process,
Quality of service, Software Development.
I. INTRODUCTION
This paper explains the best procedure to identify the
critical phases’ estimation during the building of the
Proof-of-Concept of a financial services application at the
prototype level. When initiated with the Fuzzy AHP
based procedural steps, and the results compared with the
experimental proof, no fair correlation was found. This
was because of the existing interdependencies among
different phases in the said software development. Hence,
in the course of search for viable alternatives, Analytical
Network Process (ANP) [1,2] was resorted to. This paper
reports the investigations carried out for RUP [3]
(Rational Unified Process) based software development to
arrive at the crucial estimation of critical phases
encountered.
II. ABOUT ANALYTIC NETWORK PROCESS
The Analytic Network Process (ANP) is the most
comprehensive framework for decision making that
includes qualitative factors. ANP models have two parts:
the first is a control hierarchy or network of objectives
and criteria that control the interactions in the system
978-0-7695-3758-0/09 $25.00 © 2009 IEEE
DOI 10.1109/SSIRI.2009.59
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Table 1. Super matrix
Super Matrix
Low
Medium
High
Requirements
Design
Coding
Low
Medium
High
Requirements
Design
Coding
Unit Testing
IST
0
0
0
0.0237
0.0563
0.1796
0.5412
0.1951
0
0
0
0.0378
0.0714
0.0.306
0.4507
0.1655
0
0
0
0.0226
0.2468
0.0835
0.5633
0.0835
0.5814
0.2318
0.1840
0
0
0
0
0
0.2000
0.6000
0.2000
0
0
0
0
0
0.3300
0.6110
0.0550
0
0
0
0
0
The final priorities for both the objectives and alternatives
are obtained by multiplying this matrix by itself numerous
times until the columns stabilize and become identical in
Unit
Testing
0.4667
0.2666
0.2666
0
0
0
0
0
IST
0.2231
0.3499
0.4268
0
0
0
0
0
each block. The limiting power of the super matrix is
reached at the 39th stage as shown in Table 2.
Table 2. Limiting Power of the super matrix
Super Matrix
Low
Medium
High
Requirements
Design
Coding
Low
Medium
High
Requirements
Design
Coding
Unit Testing
IST
0
0
0
0.0274
0
0
0
0.0275
0
0
0
0.0275
0.3561
0.3647
0.2265
0
0.3576
0.3662
0.2274
0
0.1040
0.1912
0.4784
0.1459
0.1044
0.1919
0.4800
0.1464
0.1045
0.1920
0.4804
0.1465
0
0
0
0
0
0
0
0
From the above matrix, it can be seen that the Unit
Testing row has the highest limiting priority. Hence, we
can conclude that unit Testing is the critical phase of all
the criteria in the software processes application.
0.3560
0.3645
0.2264
0
Unit
Testing
0.3573
0.3658
0.2272
0
IST
0.3576
0.3662
0.2274
0
0
0
0
0
0
0
0
0
0
0
0
0
most effective alternative, using which critical phases
could be identified with a fair degree of confidence.
REFERENCE:
[1] Murat, B. and Meral S. “The Analytic Hierarchy and Analytic Network
Processes”, Journal of Mathematics and Statistics, Volume 32 (2003), pp.
65-73.
[2] Saaty, T. L. Decision Making with Feedback: The Analytical Network
Process (RWS Publications, Pittsburgh, PA, 1996).
[3] Rational Unified Process: http://www.ibm.com
IV. CONCLUSIONS
ANP offers a reliable decision making power. It can be
relied upon to identify the critical parameters affecting the
QoS in a process centric software development
application. For the case study considered, Unit Testing
phase has the highest limiting priority, thus pointing
towards its criticality. Due measures could be taken up to
boost the efficiency of this phase. Identification of critical
phases during the prototype construction goes a long way
in providing pointers to the requisite resources to be
employed for those phases in the actual implementation.
Though Fuzzy Analytical Hierarchy Process is deemed to
be capable of providing the desired result, it fails to
address the case of existing interdependencies among
different phases in the software development. ANP is the
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