SlideShare a Scribd company logo
1 of 3
Download to read offline
IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 9, 2013 | ISSN (online): 2321-0613
All rights reserved by www.ijsrd.com 1851
Abstract—Regression testing has been receiving increasing
attention nowadays. Numerous regression testing strategies
have been proposed. Most of them take into account various
metrics like cost as well as the ability to find faults quickly
thereby saving overall testing time. In this paper, a new
model called the Configuration Navigation Analysis Model
is proposed which tries to consider all stakeholders and
various testing aspects while prioritizing regression test
cases.
Key words: Regression Testing, Analysis, Stakeholder,
Rank, Navigation, Test case Prioritization.
I. INTRODUCTION
Any type of software system tends to evolve as it is adapting
to the dynamic environment, modifiable needs, new
concepts and new technologies. So, it will grow in the
number of components, functions, and interfaces .Existing
functionality may be expanded for uses beyond their
original design. Thus, changes to the software are
unavoidable. According to industry estimates, it has been
that software maintenance consumes nearly 50 to 80% of the
total software cost. A major stage of maintenance is the
retesting of the software. The reduction in cost of
maintenance is possible by adopting efficient regression
testing strategies.
Regression testing is done after the bug fixing work
has been completed. Some test cases from the original suite
of test cases are selected to validate the system functionality.
Thus Regression testing helps in keeping the confidence of
the testing team high and also helps in tracking the bugs
effectively. A number of testing tools exist to help in
software development; but, few of them can be applied
directly to regression testing. Among those which can be
useful for regression testing, most have no more than the
capability to store the previous tests and rerun them after
every modification. They are not capable of any intelligent
test selection and they cannot estimate the required testing
effort.
The Regression testing strategies at unit level
attempt to select a subset of the previous test for execution
and do not repeat all the previous tests. The test cases store
some data so that after specific changes are made to the
system, those test cases can be easily identified. But the
most important aspect is consideration of saving of cost
while retesting some old test cases. This paper proposes a
novel approach named as the Configuration Navigation
Model. In section II, the overview of existing regression test
prioritization strategies is presented. Section III discusses
the proposed model in details and section IV indicates the
Challenges posed for the model and concludes with the plan
for future research in section V.
II. OVERVIEW OF EXISTING REGRESSION TEST
PRIORITIZATION STRATEGIES
Many models are used for prioritizing regression test cases.
They may be based on code coverage of a program segment.
Metrics like weighted average of the percentage of branch
covered (APBC), percentage of decision covered (APDC)
and percentage of statement covered (APSC) help in ranking
the test cases. But the severity of faults is generally not an
effective factor in this type of strategy. The main drawback
is that it does not show encouraging results when time
constraints are bound to it.
Another approach is using the Models to generate
regression test cases like use case diagrams, class diagrams,
state machine diagrams, activity diagrams. As, it is known
that in UML artifacts are interrelated with each other so any
change in one diagram forces changes in the other. For
instance, if in a class diagram we change a specific
operation then the corresponding message in the sequence
diagram also changes. The behavioural models also depend
on each other and due to system modification it becomes
really difficult to carry out an efficient test analysis. This
shortcoming creates a type of hindrance to independability
of test case design.
The Risk based regression testing takes into
account the severity of the fault by assigning an appropriate
cost to the fault and according to probability of occurrence
of the fault a risk exposure factor is calculated as:
(2.1)
Another approach for regression testing of service centric
systems is the Quota Constrained where the concept of
Request Quota is used along with the technique of Inter
Liner Programming (ILP) for test case selection. It uses a
multi stage iterative process of Time Slot Partition, Test
case selection and Prioritization for each time Slot and
Information Refreshing. But this approach is developed only
for Web Services. The drawback of this model is that any
constraints other than request quota are not handled.
The History based Test prioritization strategy takes
into account the historical data of test execution. Here a
historical value based approach with the historical data to
estimate current cost as well as the fault severity. The cost
cognizant, test case prioritization uses the function level
gratuity and the historical information of the cost of the test
cases .The fault severities values help in producing an
effective APFD (Average Percentage of Faults Detected)
metric. The drawback of this approach is that only the effect
of last execution of test cases is used to calculate the
probability of selecting test cases and that too in a binary
fashion. Another drawback is that this approach behaved
differently in a constrained environment and for
unconstrained environment. For lengthy regression testing
process the historical based concept was efficient but it was
Configuration Navigation Analysis Model for Regression Test Case
Prioritization
Manas Kumar Yogi1
1
Department of Computer Science and Engineering
1
Ellenki Engineering College, India
Configuration Navigation Analysis Model for Regression Test Case Prioritization
(IJSRD/Vol. 1/Issue 9/2013/0041)
All rights reserved by www.ijsrd.com 1852
not cost effective for small software systems.
The Genetic Algorithm based test prioritization
criteria uses genetic operators like crossover, mutation,
selection, transformation operators to reorder a regression
test case suit. This approach is effective in case of large
number of test cases interdependent on each other. Research
is going on in this regard. But according to experimental
studies, the Genetic based approach was found to produce
better results than other evolutionary search based
techniques which can be applied for test prioritization.
III. CONNECTION NAVIGATION ANALYSIS MODEL
A. Overview
The proposed technique in this paper is composite in nature.
It considers equal participated of all who are in need of the
services provided by a software system so that the failure
rate of the system is decreased to as much as possible. The
Novel approach proposed in this paper has 3 stages of
analysis each depending on other due to requirement
traceability and other essential factors that cannot be ignored
while regression testing. The model is named as
Configuration Navigation as the software system is tested in
the way it is built considering a conventional linear
sequential model for development. In each navigation stage
we consider various factors which are helpful in enhancing
the effectiveness of regression testing process.
B. Stakeholder Analysis Stage
The various user categories according to their specific
business needs will rank the test cases after receiving a
stable build. The build is delivered to stakeholder after bug
fixing is completed. Each test case is ranked as follows,
TC ID Rank (1-10)
1 …
2 …
3 …
Table. 1: Stakeholder’s Rank Table
The Rank 1 indicates highest test case priority and 10
indicate the lowest priority.
C. Business Analyst Evaluation
The business analyst decides strengthening the ranks of the
test cases obtained after stakeholder analysis. Each user
category is pre-assigned a Weightage depending on
pragmatic issues. The test case rank evaluation is done as
shown below.
TC ID
Rank (1-10) Stakeholder
Weightage
(1-5)
Cumulative
Value
1
2
Table. 2: Business Analyst Evaluation Table
The Cumulative value is computed with the following
equation:
(2.2)
If two test cases have same Cumulative values then the
Analyst performs Cost/Benefit evaluation and then decides
the prioritized order. Stakeholder Weightage values are
given on a scale of 1-5 with 1 indicating the highest
Weightage and 5 for lowest Weightage. The lower
cumulative values are preferred over the higher. Then these
values are passed on to the regression testing team.
D. Regression Testing Team Analysis
The Cumulative value obtained from the earlier stage is used
to prioritize test cases in an order such that overall testing
effort and cost is reduced. It is done by considering various
constraints like time taken to design a test case, complexity
in test case design, amount of testing resources consumed by
a test case and the time taken to fix the bug. .The team then
arrives at a value which gives a clear understanding
regarding the order in which the test cases may be executed
effectively. The technical complexity in test case design is
represented by CXT, The time to design a test case is
denoted by DT, the amount of resources consumed is
symbolized by RCT and finally the time to fix a bug is
denoted by FT. The final Connection Navigation value (CN)
is calculated as follows:
(2.3)
The test cases are then arranged by increasing order of CN
values which gives a prioritized order of regression test
cases.
IV. CHALLENGES IN IMPLEMENTATION
The approach presented in this paper has to be
experimententally validated and for that some challenges
need to be faced in each of the 3 stages mentioned above.
Stage 1: There may be ambiguity in assigning ranks by
individual user within a particular user category. This is due
to the fact that requirement perception of each individual
may not be same. One may assign a lower rank for the same
test case which might have been assigned a higher rank by
another. This dissimilarity may be reduced by application of
additional constraints but still it poses a challenge.
Stage 2: The Business analyst faces challenge while
performing Cost/Benefit analysis which may or may not
equate with those present in the predefined baselines. In
some cases multiple test cases may have same cumulative
values but still a priority must be assigned to the test cases
which are distinct. This shortcoming can be reduced only by
careful analysis of the baseline document against the test
cases.
Stage 3: The greatest challenge lies in this stage. The
technical complexity in designing, a test case directly
proportionate the time for test case design. If the system
under development is entirely new domain for the team then
these Weightage values will be naturally high. Resources
consumed for the test cases depend on the testing model
adopted by the testing team. The time to fix the bugs
depends on whether manual testing is done or automation
tools are applied for the system.
V. CONCLUSION AND FUTURE RESEARCH
The relationship between the various cumulative values and
CN values can be reaffirmed only by experimental
established for large scalable software systems. Highly
Configuration Navigation Analysis Model for Regression Test Case Prioritization
(IJSRD/Vol. 1/Issue 9/2013/0041)
All rights reserved by www.ijsrd.com 1853
reliable software is always desirable but cost must be
reasonable. Hence this paper tries to establish a relationship
between all those who influence the construction of a
software system with regression testing strategies. The
proposed model can be used to downscale the overall testing
budget by effective analysis.
REFERENCES
[1] S. Elbaum, A. Malishevsky, and G. Rothermel,
“Incorporating varying test costs and fault severities
into test case prioritization”, Proceedings of the
International Conference on Software Engineering,
May 2000.
[2] G. Rothermel, R. H. Untch, C. Chu, and M. J.
Harrold, “Prioritizing test cases for regression
testing”, IEEE Transactions on Software Engineering,
Vol.27, No.10, pp. 929-948, Oct.2001.
[3] H. Do, G. Rothermel. “A controlled experiment
assessing test case prioritization techniques via
mutation faults”, Proceedings of the International
Conference on Software Maintenance
(ICSM),pp.411-420, 2005.
[4] S. Yoo, M. Harman, "Regression Testing
Minimization, Selection and Prioritization: A
Survey", Software Testing, Verification and
Reliability, Wiley Interscience, 2010.
[5] W. E. Wong, J. R. Horgan, S. London, and A.
Aggarwal, “A study of effective regression testing in
practice”, Proceedings of the Eighth International
Symposium Software Reliability Engineering, pp.
230-238, Nov. 1997.
[6] R. C. Bryce, A. M. Menon, “Test Suite Prioritization
by Interaction coverage”, Proceedings of the
workshop on domain specific approaches to software
test automation (DOSTA), ACM, pp. 1-7, 2007.
[7] F. Belli, M. Eminov, N. Gokco. “Coverage-Oriented,
Prioritized Testing-A Fuzzy Clustering Approach and
Case Study”. In: Bondavalli. A., Brasileiro, F.
Rajsbaum, S. (eds.) LADC 2007, LNCS, Springer,
Heidelberg, Vol. 4746, pp. 95-110, 2007.
[8] H. Do, S. Mirarab, L. Tahvildari, G. Rothermel, "An
Empirical Study of the effect of time constraints on
the cost benefits of regression testing" Proceedings of
the 16th ACM SIGSOFT International Symposium
on Foundations of software Engineering, pp71-82,
2008.
[9] B. Beizer, Software Testing Techniques, New York:
Van Nostrand Reinhold, 1990.
[10] D. Binkley, ªSemantics Guided Regression Test Cost
Reduction, IEEE Trans. Software Eng., vol. 23, no. 8,
pp. 498-516, Aug. 1997.
[11] T.Y. Chen and M.F. Lau, “Dividing Strategies for the
Optimization of a Test Suite,” Information Processing
Letters, vol. 60, no. 3, pp. 135-141, Mar. 1996.
[12] H. K. N. Leung and L. White, “Insights Into
Regression Testing”, Proc. Conf. Software
Maintenance, pp. 60-69, Oct. 1989.
[13] W. E. Wong, J. R. Horgan, S. London, and A.P.
Mathur, ªEffect of Test Set Minimization on Fault
Detection Effectiveness,º Software Practice and
Experience, vol. 28, no. 4, pp. 347-369, Apr. 1998.
[14] J. Karlsson, K. Rayan , “A Cost value approach for
Prioritizing requirements,” IEEE Software Vol 14,
NO 5, 1997.

More Related Content

What's hot

Determination of Software Release Instant of Three-Tier Client Server Softwar...
Determination of Software Release Instant of Three-Tier Client Server Softwar...Determination of Software Release Instant of Three-Tier Client Server Softwar...
Determination of Software Release Instant of Three-Tier Client Server Softwar...
Waqas Tariq
 
Abstract.doc
Abstract.docAbstract.doc
Abstract.doc
butest
 
Test case prioritization using firefly algorithm for software testing
Test case prioritization using firefly algorithm for software testingTest case prioritization using firefly algorithm for software testing
Test case prioritization using firefly algorithm for software testing
Journal Papers
 
TEST CASE PRIORITIZATION USING FUZZY LOGIC BASED ON REQUIREMENT PRIORITIZING
TEST CASE PRIORITIZATION USING FUZZY LOGIC  BASED ON REQUIREMENT PRIORITIZINGTEST CASE PRIORITIZATION USING FUZZY LOGIC  BASED ON REQUIREMENT PRIORITIZING
TEST CASE PRIORITIZATION USING FUZZY LOGIC BASED ON REQUIREMENT PRIORITIZING
ijcsa
 
Enabling and Supporting the Debugging of Field Failures (Job Talk)
Enabling and Supporting the Debugging of Field Failures (Job Talk)Enabling and Supporting the Debugging of Field Failures (Job Talk)
Enabling and Supporting the Debugging of Field Failures (Job Talk)
James Clause
 

What's hot (13)

Kitamura1992
Kitamura1992Kitamura1992
Kitamura1992
 
Ijcatr04051006
Ijcatr04051006Ijcatr04051006
Ijcatr04051006
 
MIT521 software testing (2012) v2
MIT521   software testing  (2012) v2MIT521   software testing  (2012) v2
MIT521 software testing (2012) v2
 
Determination of Software Release Instant of Three-Tier Client Server Softwar...
Determination of Software Release Instant of Three-Tier Client Server Softwar...Determination of Software Release Instant of Three-Tier Client Server Softwar...
Determination of Software Release Instant of Three-Tier Client Server Softwar...
 
Sta unit 5(abimanyu)
Sta unit 5(abimanyu)Sta unit 5(abimanyu)
Sta unit 5(abimanyu)
 
@#$@#$@#$"""@#$@#$"""
@#$@#$@#$"""@#$@#$"""@#$@#$@#$"""@#$@#$"""
@#$@#$@#$"""@#$@#$"""
 
Abstract.doc
Abstract.docAbstract.doc
Abstract.doc
 
Test case prioritization using firefly algorithm for software testing
Test case prioritization using firefly algorithm for software testingTest case prioritization using firefly algorithm for software testing
Test case prioritization using firefly algorithm for software testing
 
TEST CASE PRIORITIZATION USING FUZZY LOGIC BASED ON REQUIREMENT PRIORITIZING
TEST CASE PRIORITIZATION USING FUZZY LOGIC  BASED ON REQUIREMENT PRIORITIZINGTEST CASE PRIORITIZATION USING FUZZY LOGIC  BASED ON REQUIREMENT PRIORITIZING
TEST CASE PRIORITIZATION USING FUZZY LOGIC BASED ON REQUIREMENT PRIORITIZING
 
Enabling and Supporting the Debugging of Field Failures (Job Talk)
Enabling and Supporting the Debugging of Field Failures (Job Talk)Enabling and Supporting the Debugging of Field Failures (Job Talk)
Enabling and Supporting the Debugging of Field Failures (Job Talk)
 
Chapter 2 - Test Management
Chapter 2 - Test ManagementChapter 2 - Test Management
Chapter 2 - Test Management
 
Audit
AuditAudit
Audit
 
Object Oriented Analysis
Object Oriented AnalysisObject Oriented Analysis
Object Oriented Analysis
 

Viewers also liked

Precauciones con la corriente electrica
Precauciones con la corriente electricaPrecauciones con la corriente electrica
Precauciones con la corriente electrica
danielpauta
 
Consejos para utilización de ubuntu leonardo jiménez
Consejos para utilización de ubuntu leonardo jiménezConsejos para utilización de ubuntu leonardo jiménez
Consejos para utilización de ubuntu leonardo jiménez
leojt2011
 
Resumen de libro de la biblioteca
Resumen de libro de la bibliotecaResumen de libro de la biblioteca
Resumen de libro de la biblioteca
Jorge-villamar
 
Evoluciã“n de la_informã-tica[1]
Evoluciã“n de la_informã-tica[1]Evoluciã“n de la_informã-tica[1]
Evoluciã“n de la_informã-tica[1]
yessiiii
 
Cuestionario
CuestionarioCuestionario
Cuestionario
jacinxxx
 
Nancy Grsic Character Values Knowledge Skills Abilities
Nancy Grsic Character Values Knowledge Skills AbilitiesNancy Grsic Character Values Knowledge Skills Abilities
Nancy Grsic Character Values Knowledge Skills Abilities
nancygrsic
 
15098345 acknowledgement
15098345 acknowledgement15098345 acknowledgement
15098345 acknowledgement
punitpatil007
 

Viewers also liked (20)

Presentación curso emprendedores
Presentación curso emprendedoresPresentación curso emprendedores
Presentación curso emprendedores
 
Mensajes Que Dan Miedo
Mensajes Que Dan MiedoMensajes Que Dan Miedo
Mensajes Que Dan Miedo
 
Precauciones con la corriente electrica
Precauciones con la corriente electricaPrecauciones con la corriente electrica
Precauciones con la corriente electrica
 
Yumion
YumionYumion
Yumion
 
Consejos para utilización de ubuntu leonardo jiménez
Consejos para utilización de ubuntu leonardo jiménezConsejos para utilización de ubuntu leonardo jiménez
Consejos para utilización de ubuntu leonardo jiménez
 
Lizbeth2
Lizbeth2Lizbeth2
Lizbeth2
 
Presentación 1º guerra mundial diver 2015
Presentación 1º guerra mundial diver  2015Presentación 1º guerra mundial diver  2015
Presentación 1º guerra mundial diver 2015
 
Manual de usuario
Manual de usuarioManual de usuario
Manual de usuario
 
Resumen de libro de la biblioteca
Resumen de libro de la bibliotecaResumen de libro de la biblioteca
Resumen de libro de la biblioteca
 
Evoluciã“n de la_informã-tica[1]
Evoluciã“n de la_informã-tica[1]Evoluciã“n de la_informã-tica[1]
Evoluciã“n de la_informã-tica[1]
 
20080901 Fried Rice
20080901 Fried Rice20080901 Fried Rice
20080901 Fried Rice
 
Cuestionario
CuestionarioCuestionario
Cuestionario
 
Glosario
GlosarioGlosario
Glosario
 
Final pr
Final prFinal pr
Final pr
 
Tutorial Unad 1 2012
Tutorial Unad 1 2012Tutorial Unad 1 2012
Tutorial Unad 1 2012
 
Con el tweet de mi colegio
Con el tweet de mi colegioCon el tweet de mi colegio
Con el tweet de mi colegio
 
Tipos de cámaras
Tipos de cámarasTipos de cámaras
Tipos de cámaras
 
Nancy Grsic Character Values Knowledge Skills Abilities
Nancy Grsic Character Values Knowledge Skills AbilitiesNancy Grsic Character Values Knowledge Skills Abilities
Nancy Grsic Character Values Knowledge Skills Abilities
 
15098345 acknowledgement
15098345 acknowledgement15098345 acknowledgement
15098345 acknowledgement
 
Redes inalambricas
Redes inalambricasRedes inalambricas
Redes inalambricas
 

Similar to Configuration Navigation Analysis Model for Regression Test Case Prioritization

International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)
IJERD Editor
 
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TESTTEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
ijfcstjournal
 
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TESTTEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
ijfcstjournal
 
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TESTTEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
ijfcstjournal
 
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TESTTEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
ijfcstjournal
 
A Productive Method for Improving Test Effectiveness
A Productive Method for Improving Test EffectivenessA Productive Method for Improving Test Effectiveness
A Productive Method for Improving Test Effectiveness
Shradha Singh
 
A Comprehensive Approach to Data Warehouse TestingMatteo G.docx
A Comprehensive Approach to Data Warehouse TestingMatteo G.docxA Comprehensive Approach to Data Warehouse TestingMatteo G.docx
A Comprehensive Approach to Data Warehouse TestingMatteo G.docx
ronak56
 
A Comprehensive Approach to Data Warehouse TestingMatteo G.docx
A Comprehensive Approach to Data Warehouse TestingMatteo G.docxA Comprehensive Approach to Data Warehouse TestingMatteo G.docx
A Comprehensive Approach to Data Warehouse TestingMatteo G.docx
makdul
 
A PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR GENERATING PAIRWISE TEST CASES
A PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR GENERATING PAIRWISE TEST CASESA PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR GENERATING PAIRWISE TEST CASES
A PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR GENERATING PAIRWISE TEST CASES
Kula Sekhar Reddy Yerraguntla
 

Similar to Configuration Navigation Analysis Model for Regression Test Case Prioritization (20)

International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)
 
Model based test case prioritization using neural network classification
Model based test case prioritization using neural network classificationModel based test case prioritization using neural network classification
Model based test case prioritization using neural network classification
 
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TESTTEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
 
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TESTTEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
 
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TESTTEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
 
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TESTTEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
 
A NOVEL APPROACH FOR TEST CASEPRIORITIZATION
A NOVEL APPROACH FOR TEST CASEPRIORITIZATIONA NOVEL APPROACH FOR TEST CASEPRIORITIZATION
A NOVEL APPROACH FOR TEST CASEPRIORITIZATION
 
Bd36334337
Bd36334337Bd36334337
Bd36334337
 
Test case-point-analysis (whitepaper)
Test case-point-analysis (whitepaper)Test case-point-analysis (whitepaper)
Test case-point-analysis (whitepaper)
 
Test Case Optimization and Redundancy Reduction Using GA and Neural Networks
Test Case Optimization and Redundancy Reduction Using GA and Neural Networks Test Case Optimization and Redundancy Reduction Using GA and Neural Networks
Test Case Optimization and Redundancy Reduction Using GA and Neural Networks
 
TRANSFORMING SOFTWARE REQUIREMENTS INTO TEST CASES VIA MODEL TRANSFORMATION
TRANSFORMING SOFTWARE REQUIREMENTS INTO TEST CASES VIA MODEL TRANSFORMATIONTRANSFORMING SOFTWARE REQUIREMENTS INTO TEST CASES VIA MODEL TRANSFORMATION
TRANSFORMING SOFTWARE REQUIREMENTS INTO TEST CASES VIA MODEL TRANSFORMATION
 
A Productive Method for Improving Test Effectiveness
A Productive Method for Improving Test EffectivenessA Productive Method for Improving Test Effectiveness
A Productive Method for Improving Test Effectiveness
 
A Complexity Based Regression Test Selection Strategy
A Complexity Based Regression Test Selection StrategyA Complexity Based Regression Test Selection Strategy
A Complexity Based Regression Test Selection Strategy
 
Software Cost Estimation Using Clustering and Ranking Scheme
Software Cost Estimation Using Clustering and Ranking SchemeSoftware Cost Estimation Using Clustering and Ranking Scheme
Software Cost Estimation Using Clustering and Ranking Scheme
 
Software testing effort estimation with cobb douglas function a practical app...
Software testing effort estimation with cobb douglas function a practical app...Software testing effort estimation with cobb douglas function a practical app...
Software testing effort estimation with cobb douglas function a practical app...
 
Software testing effort estimation with cobb douglas function- a practical ap...
Software testing effort estimation with cobb douglas function- a practical ap...Software testing effort estimation with cobb douglas function- a practical ap...
Software testing effort estimation with cobb douglas function- a practical ap...
 
A Comprehensive Approach to Data Warehouse TestingMatteo G.docx
A Comprehensive Approach to Data Warehouse TestingMatteo G.docxA Comprehensive Approach to Data Warehouse TestingMatteo G.docx
A Comprehensive Approach to Data Warehouse TestingMatteo G.docx
 
A Comprehensive Approach to Data Warehouse TestingMatteo G.docx
A Comprehensive Approach to Data Warehouse TestingMatteo G.docxA Comprehensive Approach to Data Warehouse TestingMatteo G.docx
A Comprehensive Approach to Data Warehouse TestingMatteo G.docx
 
A PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR GENERATING PAIRWISE TEST CASES
A PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR GENERATING PAIRWISE TEST CASESA PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR GENERATING PAIRWISE TEST CASES
A PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR GENERATING PAIRWISE TEST CASES
 
FROM THE ART OF SOFTWARE TESTING TO TEST-AS-A-SERVICE IN CLOUD COMPUTING
FROM THE ART OF SOFTWARE TESTING TO TEST-AS-A-SERVICE IN CLOUD COMPUTINGFROM THE ART OF SOFTWARE TESTING TO TEST-AS-A-SERVICE IN CLOUD COMPUTING
FROM THE ART OF SOFTWARE TESTING TO TEST-AS-A-SERVICE IN CLOUD COMPUTING
 

More from ijsrd.com

More from ijsrd.com (20)

IoT Enabled Smart Grid
IoT Enabled Smart GridIoT Enabled Smart Grid
IoT Enabled Smart Grid
 
A Survey Report on : Security & Challenges in Internet of Things
A Survey Report on : Security & Challenges in Internet of ThingsA Survey Report on : Security & Challenges in Internet of Things
A Survey Report on : Security & Challenges in Internet of Things
 
IoT for Everyday Life
IoT for Everyday LifeIoT for Everyday Life
IoT for Everyday Life
 
Study on Issues in Managing and Protecting Data of IOT
Study on Issues in Managing and Protecting Data of IOTStudy on Issues in Managing and Protecting Data of IOT
Study on Issues in Managing and Protecting Data of IOT
 
Interactive Technologies for Improving Quality of Education to Build Collabor...
Interactive Technologies for Improving Quality of Education to Build Collabor...Interactive Technologies for Improving Quality of Education to Build Collabor...
Interactive Technologies for Improving Quality of Education to Build Collabor...
 
Internet of Things - Paradigm Shift of Future Internet Application for Specia...
Internet of Things - Paradigm Shift of Future Internet Application for Specia...Internet of Things - Paradigm Shift of Future Internet Application for Specia...
Internet of Things - Paradigm Shift of Future Internet Application for Specia...
 
A Study of the Adverse Effects of IoT on Student's Life
A Study of the Adverse Effects of IoT on Student's LifeA Study of the Adverse Effects of IoT on Student's Life
A Study of the Adverse Effects of IoT on Student's Life
 
Pedagogy for Effective use of ICT in English Language Learning
Pedagogy for Effective use of ICT in English Language LearningPedagogy for Effective use of ICT in English Language Learning
Pedagogy for Effective use of ICT in English Language Learning
 
Virtual Eye - Smart Traffic Navigation System
Virtual Eye - Smart Traffic Navigation SystemVirtual Eye - Smart Traffic Navigation System
Virtual Eye - Smart Traffic Navigation System
 
Ontological Model of Educational Programs in Computer Science (Bachelor and M...
Ontological Model of Educational Programs in Computer Science (Bachelor and M...Ontological Model of Educational Programs in Computer Science (Bachelor and M...
Ontological Model of Educational Programs in Computer Science (Bachelor and M...
 
Understanding IoT Management for Smart Refrigerator
Understanding IoT Management for Smart RefrigeratorUnderstanding IoT Management for Smart Refrigerator
Understanding IoT Management for Smart Refrigerator
 
DESIGN AND ANALYSIS OF DOUBLE WISHBONE SUSPENSION SYSTEM USING FINITE ELEMENT...
DESIGN AND ANALYSIS OF DOUBLE WISHBONE SUSPENSION SYSTEM USING FINITE ELEMENT...DESIGN AND ANALYSIS OF DOUBLE WISHBONE SUSPENSION SYSTEM USING FINITE ELEMENT...
DESIGN AND ANALYSIS OF DOUBLE WISHBONE SUSPENSION SYSTEM USING FINITE ELEMENT...
 
A Review: Microwave Energy for materials processing
A Review: Microwave Energy for materials processingA Review: Microwave Energy for materials processing
A Review: Microwave Energy for materials processing
 
Web Usage Mining: A Survey on User's Navigation Pattern from Web Logs
Web Usage Mining: A Survey on User's Navigation Pattern from Web LogsWeb Usage Mining: A Survey on User's Navigation Pattern from Web Logs
Web Usage Mining: A Survey on User's Navigation Pattern from Web Logs
 
APPLICATION OF STATCOM to IMPROVED DYNAMIC PERFORMANCE OF POWER SYSTEM
APPLICATION OF STATCOM to IMPROVED DYNAMIC PERFORMANCE OF POWER SYSTEMAPPLICATION OF STATCOM to IMPROVED DYNAMIC PERFORMANCE OF POWER SYSTEM
APPLICATION OF STATCOM to IMPROVED DYNAMIC PERFORMANCE OF POWER SYSTEM
 
Making model of dual axis solar tracking with Maximum Power Point Tracking
Making model of dual axis solar tracking with Maximum Power Point TrackingMaking model of dual axis solar tracking with Maximum Power Point Tracking
Making model of dual axis solar tracking with Maximum Power Point Tracking
 
A REVIEW PAPER ON PERFORMANCE AND EMISSION TEST OF 4 STROKE DIESEL ENGINE USI...
A REVIEW PAPER ON PERFORMANCE AND EMISSION TEST OF 4 STROKE DIESEL ENGINE USI...A REVIEW PAPER ON PERFORMANCE AND EMISSION TEST OF 4 STROKE DIESEL ENGINE USI...
A REVIEW PAPER ON PERFORMANCE AND EMISSION TEST OF 4 STROKE DIESEL ENGINE USI...
 
Study and Review on Various Current Comparators
Study and Review on Various Current ComparatorsStudy and Review on Various Current Comparators
Study and Review on Various Current Comparators
 
Reducing Silicon Real Estate and Switching Activity Using Low Power Test Patt...
Reducing Silicon Real Estate and Switching Activity Using Low Power Test Patt...Reducing Silicon Real Estate and Switching Activity Using Low Power Test Patt...
Reducing Silicon Real Estate and Switching Activity Using Low Power Test Patt...
 
Defending Reactive Jammers in WSN using a Trigger Identification Service.
Defending Reactive Jammers in WSN using a Trigger Identification Service.Defending Reactive Jammers in WSN using a Trigger Identification Service.
Defending Reactive Jammers in WSN using a Trigger Identification Service.
 

Recently uploaded

1_Introduction + EAM Vocabulary + how to navigate in EAM.pdf
1_Introduction + EAM Vocabulary + how to navigate in EAM.pdf1_Introduction + EAM Vocabulary + how to navigate in EAM.pdf
1_Introduction + EAM Vocabulary + how to navigate in EAM.pdf
AldoGarca30
 
DeepFakes presentation : brief idea of DeepFakes
DeepFakes presentation : brief idea of DeepFakesDeepFakes presentation : brief idea of DeepFakes
DeepFakes presentation : brief idea of DeepFakes
MayuraD1
 
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak HamilCara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Kandungan 087776558899
 
Integrated Test Rig For HTFE-25 - Neometrix
Integrated Test Rig For HTFE-25 - NeometrixIntegrated Test Rig For HTFE-25 - Neometrix
Integrated Test Rig For HTFE-25 - Neometrix
Neometrix_Engineering_Pvt_Ltd
 

Recently uploaded (20)

Thermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VThermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - V
 
PE 459 LECTURE 2- natural gas basic concepts and properties
PE 459 LECTURE 2- natural gas basic concepts and propertiesPE 459 LECTURE 2- natural gas basic concepts and properties
PE 459 LECTURE 2- natural gas basic concepts and properties
 
Introduction to Data Visualization,Matplotlib.pdf
Introduction to Data Visualization,Matplotlib.pdfIntroduction to Data Visualization,Matplotlib.pdf
Introduction to Data Visualization,Matplotlib.pdf
 
Employee leave management system project.
Employee leave management system project.Employee leave management system project.
Employee leave management system project.
 
1_Introduction + EAM Vocabulary + how to navigate in EAM.pdf
1_Introduction + EAM Vocabulary + how to navigate in EAM.pdf1_Introduction + EAM Vocabulary + how to navigate in EAM.pdf
1_Introduction + EAM Vocabulary + how to navigate in EAM.pdf
 
Ghuma $ Russian Call Girls Ahmedabad ₹7.5k Pick Up & Drop With Cash Payment 8...
Ghuma $ Russian Call Girls Ahmedabad ₹7.5k Pick Up & Drop With Cash Payment 8...Ghuma $ Russian Call Girls Ahmedabad ₹7.5k Pick Up & Drop With Cash Payment 8...
Ghuma $ Russian Call Girls Ahmedabad ₹7.5k Pick Up & Drop With Cash Payment 8...
 
Computer Graphics Introduction To Curves
Computer Graphics Introduction To CurvesComputer Graphics Introduction To Curves
Computer Graphics Introduction To Curves
 
DeepFakes presentation : brief idea of DeepFakes
DeepFakes presentation : brief idea of DeepFakesDeepFakes presentation : brief idea of DeepFakes
DeepFakes presentation : brief idea of DeepFakes
 
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak HamilCara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
 
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptxHOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
HOA1&2 - Module 3 - PREHISTORCI ARCHITECTURE OF KERALA.pptx
 
fitting shop and tools used in fitting shop .ppt
fitting shop and tools used in fitting shop .pptfitting shop and tools used in fitting shop .ppt
fitting shop and tools used in fitting shop .ppt
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
 
Integrated Test Rig For HTFE-25 - Neometrix
Integrated Test Rig For HTFE-25 - NeometrixIntegrated Test Rig For HTFE-25 - Neometrix
Integrated Test Rig For HTFE-25 - Neometrix
 
Orlando’s Arnold Palmer Hospital Layout Strategy-1.pptx
Orlando’s Arnold Palmer Hospital Layout Strategy-1.pptxOrlando’s Arnold Palmer Hospital Layout Strategy-1.pptx
Orlando’s Arnold Palmer Hospital Layout Strategy-1.pptx
 
Double Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torqueDouble Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torque
 
Max. shear stress theory-Maximum Shear Stress Theory ​ Maximum Distortional ...
Max. shear stress theory-Maximum Shear Stress Theory ​  Maximum Distortional ...Max. shear stress theory-Maximum Shear Stress Theory ​  Maximum Distortional ...
Max. shear stress theory-Maximum Shear Stress Theory ​ Maximum Distortional ...
 
Introduction to Serverless with AWS Lambda
Introduction to Serverless with AWS LambdaIntroduction to Serverless with AWS Lambda
Introduction to Serverless with AWS Lambda
 
Jaipur ❤CALL GIRL 0000000000❤CALL GIRLS IN Jaipur ESCORT SERVICE❤CALL GIRL IN...
Jaipur ❤CALL GIRL 0000000000❤CALL GIRLS IN Jaipur ESCORT SERVICE❤CALL GIRL IN...Jaipur ❤CALL GIRL 0000000000❤CALL GIRLS IN Jaipur ESCORT SERVICE❤CALL GIRL IN...
Jaipur ❤CALL GIRL 0000000000❤CALL GIRLS IN Jaipur ESCORT SERVICE❤CALL GIRL IN...
 
457503602-5-Gas-Well-Testing-and-Analysis-pptx.pptx
457503602-5-Gas-Well-Testing-and-Analysis-pptx.pptx457503602-5-Gas-Well-Testing-and-Analysis-pptx.pptx
457503602-5-Gas-Well-Testing-and-Analysis-pptx.pptx
 
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced LoadsFEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
 

Configuration Navigation Analysis Model for Regression Test Case Prioritization

  • 1. IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 9, 2013 | ISSN (online): 2321-0613 All rights reserved by www.ijsrd.com 1851 Abstract—Regression testing has been receiving increasing attention nowadays. Numerous regression testing strategies have been proposed. Most of them take into account various metrics like cost as well as the ability to find faults quickly thereby saving overall testing time. In this paper, a new model called the Configuration Navigation Analysis Model is proposed which tries to consider all stakeholders and various testing aspects while prioritizing regression test cases. Key words: Regression Testing, Analysis, Stakeholder, Rank, Navigation, Test case Prioritization. I. INTRODUCTION Any type of software system tends to evolve as it is adapting to the dynamic environment, modifiable needs, new concepts and new technologies. So, it will grow in the number of components, functions, and interfaces .Existing functionality may be expanded for uses beyond their original design. Thus, changes to the software are unavoidable. According to industry estimates, it has been that software maintenance consumes nearly 50 to 80% of the total software cost. A major stage of maintenance is the retesting of the software. The reduction in cost of maintenance is possible by adopting efficient regression testing strategies. Regression testing is done after the bug fixing work has been completed. Some test cases from the original suite of test cases are selected to validate the system functionality. Thus Regression testing helps in keeping the confidence of the testing team high and also helps in tracking the bugs effectively. A number of testing tools exist to help in software development; but, few of them can be applied directly to regression testing. Among those which can be useful for regression testing, most have no more than the capability to store the previous tests and rerun them after every modification. They are not capable of any intelligent test selection and they cannot estimate the required testing effort. The Regression testing strategies at unit level attempt to select a subset of the previous test for execution and do not repeat all the previous tests. The test cases store some data so that after specific changes are made to the system, those test cases can be easily identified. But the most important aspect is consideration of saving of cost while retesting some old test cases. This paper proposes a novel approach named as the Configuration Navigation Model. In section II, the overview of existing regression test prioritization strategies is presented. Section III discusses the proposed model in details and section IV indicates the Challenges posed for the model and concludes with the plan for future research in section V. II. OVERVIEW OF EXISTING REGRESSION TEST PRIORITIZATION STRATEGIES Many models are used for prioritizing regression test cases. They may be based on code coverage of a program segment. Metrics like weighted average of the percentage of branch covered (APBC), percentage of decision covered (APDC) and percentage of statement covered (APSC) help in ranking the test cases. But the severity of faults is generally not an effective factor in this type of strategy. The main drawback is that it does not show encouraging results when time constraints are bound to it. Another approach is using the Models to generate regression test cases like use case diagrams, class diagrams, state machine diagrams, activity diagrams. As, it is known that in UML artifacts are interrelated with each other so any change in one diagram forces changes in the other. For instance, if in a class diagram we change a specific operation then the corresponding message in the sequence diagram also changes. The behavioural models also depend on each other and due to system modification it becomes really difficult to carry out an efficient test analysis. This shortcoming creates a type of hindrance to independability of test case design. The Risk based regression testing takes into account the severity of the fault by assigning an appropriate cost to the fault and according to probability of occurrence of the fault a risk exposure factor is calculated as: (2.1) Another approach for regression testing of service centric systems is the Quota Constrained where the concept of Request Quota is used along with the technique of Inter Liner Programming (ILP) for test case selection. It uses a multi stage iterative process of Time Slot Partition, Test case selection and Prioritization for each time Slot and Information Refreshing. But this approach is developed only for Web Services. The drawback of this model is that any constraints other than request quota are not handled. The History based Test prioritization strategy takes into account the historical data of test execution. Here a historical value based approach with the historical data to estimate current cost as well as the fault severity. The cost cognizant, test case prioritization uses the function level gratuity and the historical information of the cost of the test cases .The fault severities values help in producing an effective APFD (Average Percentage of Faults Detected) metric. The drawback of this approach is that only the effect of last execution of test cases is used to calculate the probability of selecting test cases and that too in a binary fashion. Another drawback is that this approach behaved differently in a constrained environment and for unconstrained environment. For lengthy regression testing process the historical based concept was efficient but it was Configuration Navigation Analysis Model for Regression Test Case Prioritization Manas Kumar Yogi1 1 Department of Computer Science and Engineering 1 Ellenki Engineering College, India
  • 2. Configuration Navigation Analysis Model for Regression Test Case Prioritization (IJSRD/Vol. 1/Issue 9/2013/0041) All rights reserved by www.ijsrd.com 1852 not cost effective for small software systems. The Genetic Algorithm based test prioritization criteria uses genetic operators like crossover, mutation, selection, transformation operators to reorder a regression test case suit. This approach is effective in case of large number of test cases interdependent on each other. Research is going on in this regard. But according to experimental studies, the Genetic based approach was found to produce better results than other evolutionary search based techniques which can be applied for test prioritization. III. CONNECTION NAVIGATION ANALYSIS MODEL A. Overview The proposed technique in this paper is composite in nature. It considers equal participated of all who are in need of the services provided by a software system so that the failure rate of the system is decreased to as much as possible. The Novel approach proposed in this paper has 3 stages of analysis each depending on other due to requirement traceability and other essential factors that cannot be ignored while regression testing. The model is named as Configuration Navigation as the software system is tested in the way it is built considering a conventional linear sequential model for development. In each navigation stage we consider various factors which are helpful in enhancing the effectiveness of regression testing process. B. Stakeholder Analysis Stage The various user categories according to their specific business needs will rank the test cases after receiving a stable build. The build is delivered to stakeholder after bug fixing is completed. Each test case is ranked as follows, TC ID Rank (1-10) 1 … 2 … 3 … Table. 1: Stakeholder’s Rank Table The Rank 1 indicates highest test case priority and 10 indicate the lowest priority. C. Business Analyst Evaluation The business analyst decides strengthening the ranks of the test cases obtained after stakeholder analysis. Each user category is pre-assigned a Weightage depending on pragmatic issues. The test case rank evaluation is done as shown below. TC ID Rank (1-10) Stakeholder Weightage (1-5) Cumulative Value 1 2 Table. 2: Business Analyst Evaluation Table The Cumulative value is computed with the following equation: (2.2) If two test cases have same Cumulative values then the Analyst performs Cost/Benefit evaluation and then decides the prioritized order. Stakeholder Weightage values are given on a scale of 1-5 with 1 indicating the highest Weightage and 5 for lowest Weightage. The lower cumulative values are preferred over the higher. Then these values are passed on to the regression testing team. D. Regression Testing Team Analysis The Cumulative value obtained from the earlier stage is used to prioritize test cases in an order such that overall testing effort and cost is reduced. It is done by considering various constraints like time taken to design a test case, complexity in test case design, amount of testing resources consumed by a test case and the time taken to fix the bug. .The team then arrives at a value which gives a clear understanding regarding the order in which the test cases may be executed effectively. The technical complexity in test case design is represented by CXT, The time to design a test case is denoted by DT, the amount of resources consumed is symbolized by RCT and finally the time to fix a bug is denoted by FT. The final Connection Navigation value (CN) is calculated as follows: (2.3) The test cases are then arranged by increasing order of CN values which gives a prioritized order of regression test cases. IV. CHALLENGES IN IMPLEMENTATION The approach presented in this paper has to be experimententally validated and for that some challenges need to be faced in each of the 3 stages mentioned above. Stage 1: There may be ambiguity in assigning ranks by individual user within a particular user category. This is due to the fact that requirement perception of each individual may not be same. One may assign a lower rank for the same test case which might have been assigned a higher rank by another. This dissimilarity may be reduced by application of additional constraints but still it poses a challenge. Stage 2: The Business analyst faces challenge while performing Cost/Benefit analysis which may or may not equate with those present in the predefined baselines. In some cases multiple test cases may have same cumulative values but still a priority must be assigned to the test cases which are distinct. This shortcoming can be reduced only by careful analysis of the baseline document against the test cases. Stage 3: The greatest challenge lies in this stage. The technical complexity in designing, a test case directly proportionate the time for test case design. If the system under development is entirely new domain for the team then these Weightage values will be naturally high. Resources consumed for the test cases depend on the testing model adopted by the testing team. The time to fix the bugs depends on whether manual testing is done or automation tools are applied for the system. V. CONCLUSION AND FUTURE RESEARCH The relationship between the various cumulative values and CN values can be reaffirmed only by experimental established for large scalable software systems. Highly
  • 3. Configuration Navigation Analysis Model for Regression Test Case Prioritization (IJSRD/Vol. 1/Issue 9/2013/0041) All rights reserved by www.ijsrd.com 1853 reliable software is always desirable but cost must be reasonable. Hence this paper tries to establish a relationship between all those who influence the construction of a software system with regression testing strategies. The proposed model can be used to downscale the overall testing budget by effective analysis. REFERENCES [1] S. Elbaum, A. Malishevsky, and G. Rothermel, “Incorporating varying test costs and fault severities into test case prioritization”, Proceedings of the International Conference on Software Engineering, May 2000. [2] G. Rothermel, R. H. Untch, C. Chu, and M. J. Harrold, “Prioritizing test cases for regression testing”, IEEE Transactions on Software Engineering, Vol.27, No.10, pp. 929-948, Oct.2001. [3] H. Do, G. Rothermel. “A controlled experiment assessing test case prioritization techniques via mutation faults”, Proceedings of the International Conference on Software Maintenance (ICSM),pp.411-420, 2005. [4] S. Yoo, M. Harman, "Regression Testing Minimization, Selection and Prioritization: A Survey", Software Testing, Verification and Reliability, Wiley Interscience, 2010. [5] W. E. Wong, J. R. Horgan, S. London, and A. Aggarwal, “A study of effective regression testing in practice”, Proceedings of the Eighth International Symposium Software Reliability Engineering, pp. 230-238, Nov. 1997. [6] R. C. Bryce, A. M. Menon, “Test Suite Prioritization by Interaction coverage”, Proceedings of the workshop on domain specific approaches to software test automation (DOSTA), ACM, pp. 1-7, 2007. [7] F. Belli, M. Eminov, N. Gokco. “Coverage-Oriented, Prioritized Testing-A Fuzzy Clustering Approach and Case Study”. In: Bondavalli. A., Brasileiro, F. Rajsbaum, S. (eds.) LADC 2007, LNCS, Springer, Heidelberg, Vol. 4746, pp. 95-110, 2007. [8] H. Do, S. Mirarab, L. Tahvildari, G. Rothermel, "An Empirical Study of the effect of time constraints on the cost benefits of regression testing" Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software Engineering, pp71-82, 2008. [9] B. Beizer, Software Testing Techniques, New York: Van Nostrand Reinhold, 1990. [10] D. Binkley, ªSemantics Guided Regression Test Cost Reduction, IEEE Trans. Software Eng., vol. 23, no. 8, pp. 498-516, Aug. 1997. [11] T.Y. Chen and M.F. Lau, “Dividing Strategies for the Optimization of a Test Suite,” Information Processing Letters, vol. 60, no. 3, pp. 135-141, Mar. 1996. [12] H. K. N. Leung and L. White, “Insights Into Regression Testing”, Proc. Conf. Software Maintenance, pp. 60-69, Oct. 1989. [13] W. E. Wong, J. R. Horgan, S. London, and A.P. Mathur, ªEffect of Test Set Minimization on Fault Detection Effectiveness,º Software Practice and Experience, vol. 28, no. 4, pp. 347-369, Apr. 1998. [14] J. Karlsson, K. Rayan , “A Cost value approach for Prioritizing requirements,” IEEE Software Vol 14, NO 5, 1997.