Regression Test Cases Minimization for Object Oriented

International Journal of Software Engineering and Its Applications Vol.8, No.6 (2014), pp.253-264

http://dx.doi.org/10.14257/ijseia.2014.8.6.20

ISSN:1738-9984 IJSEIA Copyright ⓒ 2014 SERSC

Regression Test Cases Minimization for Object Oriented

Programming using New Optimal Page Replacement Algorithm

Swapan Kumar Mondal1 and Dr. Hitesh Tahbildar

2

1Research Scholar, Department of CSE

University of Science and Technology, Meghalaya,

Ri-Bhoi, Meghalaya-793101, India, 2H.O.D, Assam Engineering Institute, Guwahati. India

[email protected], [email protected]

Abstract

Regression testing remains one of the most laborious and costly software testing activities

in software maintenance. Its laboriousness and costing increases with increasing number of

test suits: need to changed re-testing strategy. The strategy should identify and eliminate

redundant test cases in order to minimize the test cases from test suites. The aim of regression

testing is to reduce the retesting effort and achieve the adequate testing coverage. An

important research problem, in this context, is the new developed algorithm is needed to

reduce the retesting effort, cost and time without disturbance of thoroughness. The traditional

optimal page replacement algorithm is used for managing the virtual memory. Our approach

has been showing that the novel optimal page replacement algorithm reducing the redundant

test cases during retesting of modified object oriented program. Our testing approach is on

unit level. The logic based transitive relationship model achieves the adequate testing

coverage to the modified object oriented program. Hybridization of clock page replacement-

counting based algorithm is used for making the logic based transition relationship model. An

Illustrative example has been presented to establish the effectiveness of our methodology

coupled with logic based transitive relationship model.

Key Words: Clock page replacement algorithm, Counting based algorithm, Logic based

transition relationship, optimal page replacement algorithm

1. Introduction

Software maintenance is related to the modification in software development lifecycle. The

modification is done after delivered to the customer. The modified program need to improves

the performance and adopt the new environments. Therefore, validated software need to re-

test again (e g. Revalidation) is called regression testing. The aim of regression testing is to

ensure that there will be no new errors to be introduced in the previously validated software

[17, 26]. As well as the regression testing need to satisfy the new user requirements quickly

and reliably. Each modification of software evolved huge number of test cases and making

interface with new environments. As a result, re validation of modified software becomes

high expensive, time consuming and laborious work. Almost half of the software maintenance

cost is accountable for regression testing [19]. So minimization of the re-testing effort is a

major challenging activity in software development life cycle. Regression testing is carried

out at various level of software development life cycle phase such as unit level, re-integration

level, system level. Regression test suites minimization for object oriented programming is a

very complicated task than procedural programming. Little bit of modification in OOP may

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International Journal of Software Engineering and Its Applications Vol.8, No.6 (2014)

254 Copyright ⓒ 2014 SERSC

affect to the different programming elements among the classes. Because object oriented

programming shows the dynamic behavior, inheritance, polymorphism etc. Puzzling behavior

of objects oriented programming improves the quality of software development but lead to

complexity of depend relationship among programming elements. Different approaches

published in the literature [6, 7, 10, 26 and 28] relating to regression test minimization. Three

different regression testing techniques are generally considered. First is Test case

minimization technique [3, 4, 5, 13, 23and 30] by which the redundant test cases are removed.

The reduced Test suites need to have the fault detection capabilities. Second is a test suites

prioritization [23, 27 and 30]. Third is test suites selection [8, 10, 15, 20, 21, and 23].

In this paper we have approached the Regression test cases minimization in Object

Oriented programming based on novel optimal page replacement algorithm. The reference

strings in optimal page replacement algorithm are represented here as test cases. All the test

cases (validated test cases and test cases from modified program) are arranged and finally

divided as per page frame number. The optimal page replacement algorithm acts on the

divided parts of test cases and generates the page fault number through optimization

technique. The page fault number indicates the number of test cases in the test suites after

elimination of redundant test cases. Hybridization of clock page replacement-counting based

algorithm and generic testing requirements model among classes is used to making the logic-

based transitive relationship model. A. Frank - P. Weisberg has explained clock page

replacement and counting based algorithm for virtual memory management. Combination of

two page replacement algorithm represents here as the transitive relationship among test

cases. Stuart Anderson, 2011 proposed logic based model for abstract representation of the

system. We have modified it to the logic based transitive relationship model to detect the

affected classes. New proposed model is help to achieve the adequate testing coverage to the

modified program. Illustrative example has been given to establish the effectiveness of our

proposed algorithm in our paper.

2. Related Works

Researchers have proposed different regression testing technique for object oriented

programming in the literature. They proposed firewall based technique [9, 6, and 29], design

model based technique [1, 25 and 30], and program model based technique [2, 7 and 10]. Shin

Yoo et al., [23] explained that test cases minimization problem is a NP complete problem.

Therefore, test suites reduced problem can be converted to Regression test suites

minimization problem in polynomial time [12]. Bharti et al., [3] approaches regression test

reduction technique based on Genetic algorithm and Bee colony Optimization Technique.

This work can cover the maximum faults and reduce re-testing effort during regression

testing. But this approach makes the computational complexity, time and space complexity

for long program. As per increasing program length the probabilistic computation, space and

time complexity is generated from roulette wheel, crossover stages and mutation stages. The

proposed technique is not evaluated for regression test suites reduction in object oriented

programming. Various graph model based test cases minimization technique has been

explained in the literatures e g. M. Harrold et al., [18] has explained class call graph based, G.

Rothermel et al., [8] has explained Inter Procedural program dependence graph based and G.

Rothermel et al., [18] has explained class dependence graph based regression test suites

minimization technique in object oriented programming. Graph model based technique is

imprecise and unsafe because all the entire loop coverage path cannot be represented by graph

model. Every third party’s user needs to have changed the graph model every time because

the dynamic behavior and inheritance may harm different programming elements throughout


Copyright ⓒ 2014SERSC 255

the system. Soft computing [22, 28, 29 and 30,] based regression test suite minimization

technique also approached in the literature. Soft computing based approached used the

random input variables. The random input variables always not produce the accurate result

like hard computing. For long program it faces difficulties. So it becomes costly.

3. Proposed Approach

Class is a basic unit of testing for OOP. Method is a basic unit for testing a class. Any

modified program does affected on a certain programming elements among classes due to

dynamic nature and complex dependency relationship. Our proposed approach in a unit level,

class impacted based regression test suite minimization. Sequence of our proposed approach

is given below:

3.1. A Library Contains with the Collections of Validated Test Cases from Existing

Software. The test cases are generated by automated test cases generation technique [24].

The interfaces hardware information and user manual is also included in the library. It would

be helpful to third parties for safe re-testing.

3.2. Collects the Test Cases from Unaffected and Affected Classes of Modified Program. Therefore, redundant test cases are formed.

3.3. The Test Cases are Arranged as per Sequence of Classes in a Program Under Test. Insertion sort is used to re-arrange the redundant cases.

3.4. Arranged Test Cases are Divided as per Frame Number of Optimal Page

Replacement Algorithm. Now optimal page-replacement algorithm is used and reduced the

redundant test cases from test suites.

3.5. The Reduced Test Suites Coverage the Modified Program to Achieve the Adequate

Testing. We have used Logic based transitive relationship model for adequate fault coverage.

The logic based transitive relationship model is made on the basis of clock page replacement-

counting based hybridized algorithm. Type of testing relations (Generalization relation: not

symmetric, not reflexive but Transitive [19]) coupled with proposed hybridized algorithm and

it is coverage the modified program. Graphical representation of our proposed approach is

given below:



Validated with automated test cases generation. The Library along with

user manual send to customer. The Library contains with validated

test cases, supported hardware specification.

Change requirements

Collection of redundant test cases (P+ P*) along with Libraries and

user manual. The Library contains with validated test cases of P,

test cases of P*, code changing list and supported hardware

specification P*.

Re -arranged test cases are divided based on frame Number.

Reduced test cases are generated. Page fault number represents test cases

number in test suites.

Figure 1. Graphical Representation of our Proposed Approach

4. Illustration of Proposed Approach

Illustrative example has been presented below to establish the effectiveness of our

proposed methodology.

Step-A Software P: Automated Test cases generation generates the following validated

teat cases.

Software P

Customer

Modified

Software P*

Insertion sort acts on redundant test

cases

Optimal page replacement algorithm

Logic based transitive

relationship model

Clock page replacement- Counting based

hybridized algorithm

Testing relation among classes

Re-validation

New software version released



Validated Test cases: a1, a2, a3, a4

Validated Test cases: b1, b2, b3

Validated Test cases: c1, c2,

Figure 2. Source Program

Step-B Modified software P*

Figure 3. New Class D is Appended

The new class D is affected to the classes A and C due to dynamic behavior of objects,

inheritance of classes and polymorphism etc. The new and redundant test cases are generated

from affected classes. Class B is not affected by new class D. The new class D generates the

test cases are: d1, d2, d3. Therefore, modified Program P* generates the test cases are: {a1,

a2. a3, a4, b1, b2, a1, c1, c2, b3, c1, c2, a3, c3, d1, a4, d2, d3, a5} Step-C Sequential

number is given on each test cases based on the sequence of classes in the program P*.

1 2 3 4 6 7 1 9 10 8 9 10

a1 a2 a3 a4 b1 b2 a1 c1 c2 b3 c1 c2

3 11 12 4 13 14 5

a3 c3 d1 a4 d2 d3 a5

We got the following re-arranged test cases with the help of Insertion sort Algorithm.

{a1, a1, a2, a3, a3, a4, a4, a5, b1, b2, b3, c1, c1, c2, c2, c3, d1, d2, d3 }

Step-D Divide the sorted test cases as per page frame number. We assume the page frame

number is 3. The memory reference strings represented here as test cases. The page fault rate

represents the test cases number in test suite. As per optimal page replacement algorithm, the

page is to be replaced which is not to be used in future for longest period of time. It is

impossible to know the future. Therefore, traditional optimal page replacement algorithm

could not reduce the redundant test cases from test suites. We have used the re-arranged test

cases in optimal page-replacement algorithm. As a result we can get the reduced test suites

after removing the redundant test cases. Implementation of optimal page replacement

algorithm on re-arranged test cases is explained below: Dividing the test cases as per page

frame number:

Class A

Class B

Class C

Class A

Class B

Class C

Class D



Page frame number = 3

{a1, a1, a2, a3, a3, a4, a4, a5, b1, b2, b3, c1, c1, c2, c2,

c3, d1, d2, d3 }

Figure 4. Optimal Page Replacement Algorithm

Page fault rate = 14

The test suite contains with 14 numbers of test cases. After removing the redundant test cases

with the help of optimal page replacement algorithm, we got the following test cases: { a1,

a2, a3, a4, a5, b1, b2, b3, c1, c2, c3, d1, d2, d3 }

Step-E The reduced test cases coupled with logic based transitive relationship model to

evolve the adequate faults from modified program. The logic based transitive relationship

model is made on the basis of testing relations among classes and hybridized clock page

replacement – counting based algorithm. A generic test requirement is necessary for testing

relations among classes. The generic test is based on generalization relation [19].The

generalization relation in object oriented programming is not reflexive, not symmetric but

transitive. We are taking a simple example below for showing the generic test relationship requirements among classes:

Class A { int width, length ,arearect ;

Public: void arearectangle () {

arearect= width * length; }};

Class B: public A { int areasquare, side;

Public: void inputareasquare () {

areasquare= width * width;

cout < < “ enter the side” ;

cin > > side;

}};

Class C: public A, public B {

Private: int voloumecube, diag;

Public: void Diagonal () {

diag= √width+ length;

volumecube= side * side * side ;

cout < < “ volumecube= ” < < volumecube;

cout < < “diagonal = ” < < diag ;}};

main() {

}

a1

a2

a3

a4

a5

b1

b2

b3

c1

c2

c3

d1

d2

d3



Specilization

Class A: arearect

Class B: areasquare

Class C: diag

Generalization relation

Volumecube

Figure 5. Testing Relation among Classes

The hybridized clock page replacement-counting based algorithm represents the transitive

relationship among single test cases or a group of test cases. In a clock page replacement,

every test case is connected in clock wise. Reference bits 1 is used for allocated page frame

with test cases. After replacement or empty page frame is represented with 0. The allocable

page frames in clock page replacement are transitively connected. Most frequently used

(MFU) algorithm is a part of counting based page replacement algorithm. We have used most

frequently used (MFU) algorithm for allocating the set of test cases in a single page frame.

Based on the argument, the classes with smallest count of test cases are brought in the page

frame and used it. A class contains with smallest number of test suites executed first. Then

gradually increase the classes with higher number of test suites. In our object oriented

program example, the class B, C, D contains with 3 numbers of test cases. Class D is the new

class and appended at the end in the modified program P*. Class D contains with three

numbers of test cases. As per argument, test cases of class D would be replaced first and then

class C and so on. Therefore, replacement strategy represents the transitive relationship within

test cases among the classes. Details hybridized clock page replacement-counting based

algorithm is represented below in Figure 6.

As per logic based transitive relationship model (From Figure 6):

Class D (Executed with) (d1, d2, d3), (d1,d2, d3) (c1, c2, c3)

Therefore, Class D is affected to Class C.

Class D (Affected to) (c1, c2. c3)

(c1, c2. c3) (a1. a2, a3, a4. a5)

Therefore, class D is affected to Class A.

So, Class D is affected to Class A, C and to be executed with test cases a1, a2, a3, a4, a5

and c1, c2, c3. Class D is does not affect to Class B. Logic based transitive relationship model

also show the complex dependency relationship of each test cases with other test cases e g., If

a1 a2, a2 b4, b4 c2. Therefore, a1 is related to c2.

The logic based transitive relationship model done adequate coverage along with support

of previous library. So it is a safe testing also for third parties.

width

length

width

side

width

length

side * side * side



Figure 6. Hybridization of Clock Page Replacement-Counting based Algorithm

5. Result and Discussion

5.1. Before Optimization, Redundant Test Cases are Recognized Through Insertion Sort

Algorithm. Numbers of test cases in test suites are understand through page fault number.

According to optimal page replacement algorithm, replacement is done that will not be used

for future. If it is used in future then it generates the redundant test cases. Therefore, it would

resist to forming the same test cases. As a result we get reduced test cases after removing

redundant test cases.

5.2 The Reduced Test Cases Coverage the Modified Program for Adequate Fault

Detection. The affected classes would identify easily by our proposed logic based transitive

relationship model. We are also having been using the user manual, library of test cases, and

supported hardware during re-validation. It would become helpful to the third party’s for safe

testing. As per S. Yoo et al., [], the effectiveness of the minimization of this proposed

algorithm is =

Number of test cases in the reduced test suite

1 x 100%

Number of test cases in the original test suite

= (1 14 / 19) x 100%

= 26.316%

5.3. Soft Computing based Regression Test Suite Minimization is a Complex Task. The

complexity increases with increasing program structure. The probabilistic functions .The

computational complexity, time complexity, space complexity (e g., crossover stages,

mutation stages) are raised. Our new page replacement algorithm can reduced the huge

number of redundant test cases from large and complex modified software. There is no



random test cases are using here. Therefore, computational complexity, time and space

complexity can also be removed by our proposed algorithm.

5.4. Several Puzzling Behavior like Inheritance, Polymorphism, Encapsulation, Dynamic

Binding Founds in Object Oriented Programming. This puzzling behavior leads to the

complex relationship among program components and make dependency relationship more

difficult. The complex dependency relationship can be easily traced out from generic test

relationship and hybridized clock page replacement-counting based algorithm. As a result re-

validation is done with less imparted effort. Graphical representation of our proposed

approach showing the benefits:

Figure 7. Graph Showing Benefits From Our Proposed Method

All possible states of solution do not be explored through heuristic search algorithm. Only

the best solution is explored by this algorithm from the design life cycle. Logic based

transitive relationship model represents dependency relationship among programming

components. It explored all the possible states of solution through reference bit in hybridized

model (Figure 6). Therefore, it would increase the efficiency of heuristic based regression test

cases minimization technique [23].

6. Conclusion and Future Work

Traditional optimal page replacement algorithm is used for managing virtual memory. Our

novel optimal page replacement algorithm has been using for regression test suite

minimization in object oriented programming. The large number of redundant test cases can

be identifying by insertion sort prior to reduction. Reduced number of test cases in test suites

is represented by the number of page faults. One of the examples has been shown in this

paper to establish the effectiveness of our proposed approach. This novel optimal page

replacement algorithm identifies and reduced the huge number of redundant test cases from

large program. This approach leads to effort and time minimization. The reduced test cases do

the coverage of modified program. Thus adequate testing is done with the coupling of Logic

based transitive relationship model. The logic based transitive relationship model is made on

the basis of generic test requirements among classes and hybridized clock page replacement-

counting based algorithm. The complex dependency relationship among programming

elements can be traced out by our proposed model. As a result our logic based transitive



relationship model do the adequate testing coverage with optimal time. This lead also safe

testing because every re-validation is done along with third parties library and user manual.

Our issue of future research including automation technique on regression testing for large

and complex objects oriented software.

References

[1] A. Nadeem Ali, Z. Iqbal and M. Usman, “Regression testing based on UML design models”, Proceedings of

the 13th Pacific Rim International Symposium on Dependable Computing, (2007), pp. 85-88.

[2] A. Orso, N. Shi and M. Harrold, “Scaling regression testing to large software systems”, Proceedings of the

12th ACM SIGSOFT Twelfth International Symposium on Foundations of Software Engineering, (2004)

November, pp. 241-251.

[3] B. Suri, I. Mangal and V. Srivastava, “Regression Test Suite Reduction using an Hybrid Technique Based on

BCO And Genetic Algorithm”, Special Issue of International Journal of Computer Science & Informatics

(IJCSI), ISSN (PRINT) : 2231–5292, vol. 2, no. 1-2, pp. 165-172.

[4] T. Y. Chen and M. F. Lau, “Dividing strategies for the optimization of a test suite”, Information Processing

Letters, vol. 60, no. 3, (1996), pp. 135-141.

[5] D. Kichigin, “Test Suite Reduction for Regression Testing of Simple Interactions between Two Software

Modules”.

[6] D. Kung, J. Gao, P. Hsia, F. Wen, Y. Toyoshima and C. Chen, “On regression testing of object oriented

programs”, Journal of Systems and Software, vol. 32, no. 1, (1996) January, pp. 21-40.

[7] G. Rothermel and M. Harrold, “Selecting regression tests for object-oriented software”, International

Conference on Software Maintenance, (1994) March, pp. 14-25.

[8] G. Rothermel and M. Harrold, “Selecting tests and identifying test coverage requirements for modified

software”, Proceedings of the International Symposium on Software Testing and Analysis, (1994) August, pp.

169-184.

[9] G. Rothermel, M. Harrold, J. Ostrin and C. Hong, “An empirical study of the effects of minimization on the

fault detection capabilities of test suites”, Proceeding of the international conference on software

maintenance, (1998) November, pp. 34-43.

[10] G. Rothermel, M. Harrold and J. Dedhia, “Regression test selection for C++ software”, Software Testing,

Verification and Reliability, vol. 10, no. 2, (2000) June, pp. 77109.

[11] M. J. Harrold, R. Gupta and M. L. Soffa, “A methodology for controlling the size of a test suite”, ACM

Transactions on Software Engineering and Methodology, vol. 2, no. 3, (1993), pp. 270–285.

[12] M. Garhi Ignou, New delhi-110 068, April. 2009. Design and analysis of algorithm (MCS-031, Design

Techniques-. I, II). P.25. 49 Maa Printers, New Delhi.

[13] J. Lin, C. Huang and C. Lin, “Test suite reduction analysis with enhanced tie-breaking techniques”, 4th IEEE

International Conference on Management of Innovation and Technology, 2008. ICMIT 2008, (2008)

September, pp. 1228-1233.

[14] K. Abdullah and L. White, “A firewall approach for the regression testing of object-oriented software”,

Proceedings of 10th Annual Software Quality Week, (1997) May, pp. 27.

[15] L. Briand, Y. Labiche and S. He, “Automating regression test selection based on UML designs”, Information

and Software Technology, vol. 51, no. 1, (2009) January, pp. 16-30.

[16] L. Briand, “An Introduction to Regression Testing”, Ph.D., IEEE Fellow, © Lionel Briand, (2011).

[17] M. J. Harrold, R. Gupta and M. L. Soa, “A methodology for controlling the size of a test suite”, ACM

Transactions on Software Engineering and Methodology, vol. 2, no. 3, (1993), pp. 270-285.

[18] G. Rothermel and M. Harrold, “Selecting tests and identifying test coverage requirements for modified

software”, Proceedings of the International Symposium on Software Testing and Analysis, (1994) August, pp.

169–184.

[19] www.phindia.com/rajibmall/chapters/LECTURE16.ppt .

[20] P. Hsia, X. Li, D. Kung, C. Hsu, L. Li, Y. Toyoshima and C. Chen, “A technique for the selective

revalidation of object-oriented software”, Journal of Software Maintenance: Research and Practice, vol. 9, no.

4, (1997), pp. 217-233.

[21] Q. Farooq, M. Iqbal, Z. Malik and A. Nadeem, “An approach for selective state machine based regression

testing”, Proceedings of the 3rd international workshop on Advances in model-based testing, AMOST ’07,

ACM, (2007), pp. 44–52.

[22] R. Kommineni, V. Ahlawat and Anjaneyulu Pasala, “ Functional Test Suite Minimization using Genetic

Algorithm”, Infosys Labs Briefings, vol. 11, no. 2, (2013), pp. 59-69.

[23] S. Yoo and M. Harman, “Regression Testing Minimization Selection and prioritization: ASurvey”,

WileyInter Science (www.interscience.wiley.com). DOI: 10.1002/000, Reliab. (2007), pp. 1–7.



[24] S. Kumar Mondal and Dr. H. Tahbildar, “Automated Test Data generation using Fuzzy logic-Genetic

algorithm hybridization system for class testing in object oriented programming”, International Conference

on Computer Network & Information Technology (ICCNIT-2014), ISBN: 978-93-83842-27-8, (2014)

March, pp. 315-324.

[25] T. Cormen, C. Leiserson, R. Rivest and C. Stein, “Introduction to Algorithms”, MIT Press, Cambridge, MA,

(2001).

[26] T. Y. Chen and M. F. Lau, “Dividing strategies for the optimization of a test suite”, Information Processing

Letters, vol. 60, no. 3, (1996), pp. 135-141.

[27] W. Eric Wong, “Reduce Cost of Regression Testing”, Star Laboratory of Advance research on Software

Technology, The University of Texas at Dallas, http://www.utdallas.edu/~ewong.

[28] W. Wong, J. Horgan, S. London and A. Mathur, “A study of effective regression testing in practice”,

Proceeding of the Eighth International symposium on software reliability Engineering, (1997) November, pp.

230-238.

[29] X.-Y. Ma, B.-K. Sheng and C.-Q. Ye, “Test-suite reduction Using Genetic algorithm”, J. Cao, W. Nejdl and

M.Xu (Eds.): APPT2005, LNCS3756, (2005), pp. 253-262.

[30] Z. Li, M. Harman and R. M. Hierons, “Search Algorithms for Regression Test Case Prioritization”, IEEE

Transactions on software engineering, vol. 33, no. 4, (2007) April, pp. 225-237.

Authors

Swapan Kumar Mondal, Research Scholar, Department of CSE,

University of Science and Technology, Meghalay, 9th Mile, Techno-

city, Baridua, Ri-Bhoi, Meghalaya-793101, India, e-mail: swapan

[email protected], Mob No: 8724075808, received his B.SC degree

from Burdwan university in 1989 and MCA from Indira Gandhi

National Open University in 2011.

Presently he is doing Ph.D in University of Science And

Technology, Meghalaya, India, and his current research interest in

automated software Test Data Generation for industrial related

software.

H. Tahbildar Received his B. E. degree in Computer Science andEngineering from Jorhat

Engineering College, Dibrugarh University in 1993and M. Tech degree in Computer and

Information Techno logy from IndianInstitute of Technology, Kharagpur in 2000 and Ph.D

from Guwahati University. His current research interest is Automated Software Test data

generation,Program Analysis. He is working as HOD, Computer EngineeringDepartment,

Assam Engineering Institute,Govt of Assam. Guwahati.



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Regression Test Cases Minimization for Object Oriented