Software Engineering: Application of Enhanced Testing Methods to Equations

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1 Volume-6, Issue-4, July-August 2016 International Journal of Engineering and Management Research Page Number: Software Engineering: Application of Enhanced Testing Methods to Equations Shirdi Wazeed Baba 1, K Nikhil Reddy 2 1 Bachelor of Technology (Computer Science) Final Year at Indian Institute of Information Technology Design and Manufacturing, Jabalpur, INDIA 2 Bachelor of Technology (Information Technology) Final Year at Manipal Institute of Technology, Manipal, INDIA ABSTRACT Software testing plays an important role in the Software Development Life Cycle. Model-based testing has gained a lot of prominence in recent times with organizations looking for automation of test case design and execution in lieu of a manual testing process. Modelbased testing techniques help generate numerous test artifacts such as test cases, test sequences, executable test scripts and requirement traceability matrix. In modelbased software engineering, models can broadly be classified into two categories: 1. Static models and 2. Dynamic models Static models represent the structural aspects of the system (e.g., class diagrams). On the other hand, dynamic models capture the behavioral aspects of the system (e.g., activity diagrams).this paper encompasses different black-box testing techniques like robustness, equivalence class testing,boundary value analysis etc.these techniques are implemented on cubic equation problem and evaluated test cases using these different techniques. Keywords--- Black-Box testing, testing, test cases, software engineering. I. INTRODUCTION Testing is the process of evaluating a system or its component(s) with the intent to find that whether it satisfies the specified requirements or not. This activity results in the actual, expected and difference between their results. In simple words testing is executing a system in order to identify any gaps, errors or missing requirements in contrary to the actual desire or requirements. According to ANSI/IEEE 1059 standard, Testing can be defined as A process of analyzing a software item to detect the differences between existing and required conditions (that is defects/errors/bugs) and to evaluate the features of the software item. Overview II. SOFTWARE TESTING Software testing is the process of evaluation a software item to detect differences between given input and expected output. Also to assess the feature of A software item. Testing assesses the quality of the product. Software testing is a process that should be done during the development process. In other words software testing is a verification and validation process. Black box Testing Black box testing is a testing technique that ignores the internal mechanism of the system and focuses on the output generated against any input and execution of the system. It is also called functional testing. White box Testing White box testing is a testing technique that takes into account the internal mechanism of a system. It is also called structural testing and glass box testing. Black box testing is often used for validation and white box testing is often used for verification. Black Box vs White Box Testing The basic difference between black-box and white-box testing is the areas of focus which they choose. We can simply say that black-box testing is focused on results. Where if an action is performed and the desired result is obtained then the process that has actually been used is irrelevant. White-box testing, on the other hand focuses on the internal working of an application and it is considered to be complete only when all the components are tested for proper functioning. Experiment: We evaluate number of test cases using different techniques for a cubic equation. Boundary Value Analysis The boundary points are not tested properly for many inputs which in turn leads to errors as most of the errors generally occur at boundaries of the input domain. Boundary Value Analysis (BVA) leads to selection of test cases that exercise boundary values. We have a cubic equation and we should evaluate the outputs that are generated based on the inputs given. Experience shows that test cases that are close to boundary 95 Copyright Vandana Publications. All Rights Reserved.

2 conditions have higher chances of detecting an error. Here boundary condition means an input value may be on the boundary or just above the boundary. Here we have input variables with in a limit of The boundary values are 0, 1, 50, 99, 100. In this total number of test cases would be (4n+1). For a cubic equation the n would be 4, so total number of test cases would be 4n+1= 4 4+1= 17 where n=4 Robustness Testing Robustness is defined as the degree to which a system operates correctly in the presence of exceptional inputs or stressful environmental conditions. We can say it as an extension of BVA. Here we see that what happens when the extreme values are exceeded with a valve slightly greater than maximum and the value slightly less than minimum. There would be total number of test cases are (6n+1). Here we have input variables with in a limit of The input variables are -1, 0, 1, 50, 99, 100, 101.For a cubic equation the n value 4, so total number of test cases would be 6n+1= 6 4+1= 25 where n=4 Equivalence Class Testing Equivalence class is a testing technique in which input data is divided into various partitions called as equivalence classes.test cases are designed for equivalence data class. The equivalence partitions are frequently derived from the requirements specification for input data that influence the processing of the test object. Time taken for testing a software can be reduced by using appropriate test cases. It is preferably used first level of software testing. From each partition only one condition is tested as in a given partition all the conditions are considered as same. i.e if any one condition fails in a class it is assumed that all the conditions will behave in a same way i.e they fail. In this paper we have a problem of Cubic Equation for which we have generated test cases using equivalence class testing technique. Here we have two domains: Input & output domain. n=4 (p,q,r,s) Input domain: Input 1 : p : p=0 Input2 : p: p<0 Input 3 : p:1<p<100 Input 4 : p: p>100 Input 5 : q: q<0 Input 6 : q:1<q<100 Input 7 : q:q>100 Input 8 : r: r<0 Input 9 : r:1<r<100 Input 10 : r: r>100 Input 11 : s: s<0 Input 12 : s:1<s<100 Input 13 : s: s>100 Output Domain: Output 1 : <p,q,r,s> : in case p=0 the equation is not cubic Output 2 : <p,q,r,s> : are real roots if h >0 96 Copyright Vandana Publications. All Rights Reserved.

3 Output 3 : <p,q,r,s> : are equal roots if h= 0 Output 4 : <p,q,r,s> : are imaginary roots if h<0 Result tables In this section we have summarized the results in the following tables. Here general cubic equation has the form px 3 +qx 2 +rx+s the coefficients p,q,r,s the following cases need to be considered: If h> 0, then the equation has three distinct real roots. If h = 0, then the equation has a multiple root and all its roots are real. If h< 0, then the equation has imaginary roots. Table 1. Bounded Value Analysis Result Test Case p q r s Output Not Cubic equation Table 1. Bounded Value Analysis Result (Contd ) Imaginary roots Imaginary roots Imaginary roots Imaginary roots `50 0 Imaginary roots Equal roots Note: Total no of test cases= 4n+1 where n =4 Table 2. Robustness Test cases Result Test p q r s Output Input invalid Not Cubic equation 97 Copyright Vandana Publications. All Rights Reserved.

4 Input invalid Input invalid Imaginary roots Imaginary roots input Input invalid Imaginary roots Imaginary roots Input invalid Input invalid Imaginary roots Imaginary roots Table 2. Robustness Test cases Result (Contd ) Invalid input 98 Copyright Vandana Publications. All Rights Reserved.

5 Note: Total no of test cases= 6n+1 where n =4 Table 3. Equivalence class Testing Results p q r s Expected o/p Not cubic Equation Imaginary root Real root Real root Real root Real root Real root Imaginary root Imaginary root Imaginary root Real root Real root Imaginary root Imaginary root Imaginary root Imaginary root Imaginary root Real root Real root Real root 99 Copyright Vandana Publications. All Rights Reserved.

6 III. RESULTS OF EXPERIMENTS Type of Testing Test Case Performance Boundary value 17 Good Robustness Testing 25 Fair Worst Testing 625 Worst IV. CONCLUSION Testing is an important technique for the improvement and measurement of a software system s quality. To make the problem statement clear it is always better to use black box testing method to test the program as you write it instead of fixing it later. This paper has investigated the problem of cubic equation in order to detect domain faults. We have shown a purely geometric basis for test generation. In this we investigate various possible inputs and generate the desired outputs with the help of various black box testing methodologies. CODE #include<stdio.h> #include<math.h> int main() char say; double E; int j=0,a=1,b=1; double n = 12; double p,q,r,s; double gx,gpx,m,x; printf("enter the value of p, q, r and s: "); scanf("%lf %lf %lf %lf",&p,&q,&r,&s); if(p>0) printf("enter your initial guess value of x ): "); scanf("%lf",&m); printf("enter the value of convergence limit: "); scanf("%lf",&e); while(say!='q') x= m; gx = p*x*x*x +q*x*x +r*x +s; j=0; while(j<n) j=j+1; gx = p*x*x*x +q*x*x +r*x +s; 100 Copyright Vandana Publications. All Rights Reserved.

7 gpx = 3*p*x*x +2*q*x +r; x= x - (gx/gpx); printf("after iteration %d, root = %f\n", b++, x); printf("to continue enter c to quit enter q :"); scanf("%c", & say); if(say=='c') printf("please put the values p, q, r and s (separated by space): "); scanf("%lf %lf %lf %lf",&p,&q,&r,&s); V. FUTURE ASPECTS The future approach would be in implementing code to calculate roots of any cubic equation based on the inputs given to it and then use white box testing to test the code. REFERENCES [1] A Code-Based Input Partitioning Method for Equivalence Class Testing Lwin Khin Shar; Hee Beng Kuan Tan; Hui Lui Software Engineering (WCSE), 2010 Second World Congress on Year: 2010, Volume: 2 Pages: , DOI: /WCSE IEEE Conference Publications [2] Reusing black box test paths for white box testing of websites Rajiv Chopra; Sushila Madan Advance Computing Conference (IACC), 2013 IEEE 3rd International Year: 2013 Pages: , DOI: /IAdCC IEEE Conference Publications [3] Test Data Generation from UML State Machine Diagrams using Gas Chartchai Doungsa-ard; Keshav Dahal; Alamgir Hossain; Taratip Suwannasart International Conference on Software Engineering Advances (ICSEA 2007) Year: 2007 Pages: 47-47, DOI: /ICSEA Cited by: Papers (7) IEEE Conference Publications [4] How to solve a cubic equation. Part 1. The shape of the discriminant J. F. Blinn IEEE Computer Graphics and Applications Year: 2006, Volume: 26, Issue: 3 Pages: 84-93, DOI: /MCG Cited by: Papers (2) IEEE Journals & Magazines [5] Mining Frequent Patterns from Software Defect Repositories for Black-Box Testing Ning Li; Zhanhuai Li; Lijun Zhang Intelligent Systems and Applications (ISA), nd International Workshop on Year: 2010 Pages: 1-4, DOI: /IWISA Cited by: Papers (1) IEEE Conference Publication [6] Ostrand, T.J., and Balcer, M. J. The Category- Partition Method for Specifying and Generating Functional Tests. Communications of ACM, 31, 3(June 1988), [7] Poston, R.M. Automating Specification-based Software Testing, IEEE, [8] Perry, W. Effective Methods for Software Testing, Wiley, [9] Clarke, L. A., Hassell, J., and Richardson, D. J A close look at domain testing. IEEE Transactions on Software Engineering 8, 4, Copyright Vandana Publications. All Rights Reserved.