Research Article AUTOMATED EXCEPTION HANDLING IN SOFTWARE TESTING Dr. Anjaneyulu G.S.G.N*

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1 ISSN: X CODEN: IJPTFI Available Online through Research Article AUTOMATED EXCEPTION HANDLING IN SOFTWARE TESTING Dr. Anjaneyulu G.S.G.N* 1 Professor, School of Advanced Sciences, VIT University, Vellore, India. 2,3,4 B.Tech, School of Computing Sciences and Engineering, VIT University, Vellore, India. anjaneyulu.gsgn@vit.ac.in Received on Accepted on Abstract: Exception Handling is a method of developing a system to detect and deal with exceptional conditions. Exceptional Handling improves the robustness of the system. But exceptional handling increases the cost in testing phase. Earlier research on basis path generation ignored the effects of exception handling on control flow. This paper gives a method to generate basis path set based on Exception Control Flow Graph. Followed by the method this paper provides a simple sample code to show how efficiently our proposed method works. Keywords: Exception handling, Robustness, Software Testing. I. Introduction Software Testing is a very effective way to cut down the maintenance and afterwards software cost development. And if this procedure can be done automatically then it would be a very faster and efficient way to test a particular program. It is been observed that in large projects, huge amount of time in the development section is devoted in testing phase. Therefore automation is very necessary. Testing through automation is a process of writing computer programs that can generate test cases manually. Automated testing save time, money and increase test coverage. Generally, software testing tools lack in reliability, portability, scalability and applicability. Though automated software testing can be done via the following methods as Random, Goal oriented, intelligent approach and path oriented. Random testing is quick and simple but not effective. Goal oriented approach do not require path selection step but there is difficulty in selecting IJPT July-2015 Vol. 7 Issue No Page 8011

2 goal and adequate data. Intelligent approach might face the problems of high computation. The reason behind popularity of path oriented testing is its strongest path coverage method. Main problem behind path oriented test data generation is infeasible path and complexity of data types. Path oriented testing can be implemented by symbolic execution, actual value, and combined method. Conventional method of test data generation using symbolic execution collect the path predicate and then solve it with a help of a constraint solver. There are many issues of symbolic execution. Some of them are unsolvable constraint are arising, solving for infinte loops and size of symbolic expression etc. In current research, the testing of program with exception handling constructs is always separated into ormal testing and exception testing. So we need to test one program twice separately which increases the overall cost in testing phase. Considering such problems, this paper proposes a method to detect normal defect and exception defect to generate the basis path only once. II. Solution Proposing While testing a code with exception handling procedure, Exception Control Flow Graph is used to represent the structure of the code. Exception Control Flow Graph is a directed graph (which is in particular direction), which can be expressed as ECFG (Exception Control: Flow Graph ) =<X,E,Start,End>, where X is a set of nodes, E is a set of edges, Start is the unique entry or starting node and End is the unique exit node or the finish node. Each node represents a program statement or an exception exit. Each edge (x, y) represents the flow of control from statement x to statement y. A BPS is a collection of mutually independent paths through which all the paths can be constructed by linear computation. The number of the BPS equals to the number of Cyclomatic complexity (CC), which is defined to be e - n + 2, where e and n are the number of edges and nodes in the program flow graph, respectively. In case of exception Occurrence in a particular program is, what a code does is it stops it current execution and saves its state and transfers the control too the exception handler. Then it s the job of the exception handler to handle that exception and then again return back the control to the original program. In this paper the algorithm that we proposed involves three steps which are: Firstly, construct an uncompleted CFG in which there should not be any outgoing edge matching to the statement of throw, secondly, determine the type of exception in the IJPT July-2015 Vol. 7 Issue No Page 8012

3 statements that may be thrown, finally, add the outgoing edges of the statement of throw and the necessary exception nodes. II. Algorithm Input: G(P)//CFG or ECFG Output:BPS //basis path will be the output. Explanation: In the initial phase it will first reduce the graph to a simple graph (that is a graph without loops and parallel edges. (in lines 1-5). In lines 1-5 it is checking whether the input graph has a loop or not, if it has then it will make a list of all those edges which does not form a circuit( don t form a loop) and store it in an array denoted as EL and if the graph doesn t have any loops then follow the else condition and store that graph in G. Pseudo Code: Begin 1. if G has a loop then 2. EL= { e e G G-e doesn t include loop} 3. G =G-EL 4. else G =G 5. endif 6.NodeList= {x x G }// Node list is a list that makes a collection of all the nodes that are present in a graph(without loops). 7 Path = {path path is got from G by DFS}// Path is a collection of all those suitable path that are formed as a result of Depth First Search. It is because depth first search searches till the leaf node and thus a path can be selected and can be stored in a Path (array we defined) 8 while(path!=φ) // If there exists some path in in Path(array) 9. for each path in Path do // for all the paths execute this loop 10. if (path NodeList)!=φ then //the nodes and the Path(array of paths) have nodes in common then 11. for each node in Path NodeList do 12. List= List {<node,path>} // List will make a collection of all the suitable paths that could be taken in account while creating the test cases(which path needs to be followed during a program execution) and will include the nodes and path in it 13. NodeList = NodeList - {node}// delete the node from the Node List 14. endfor 15. Path= Path-path // delete the path from the path array 16. BPS= BPS {path} //Basis Path search takes into account that path 17. endif 18. endfor 19. if List!=φ then 20. for each <node, path> in List do // for each node in List array do the following steps 21. for each node s successor do // search if left out for certain paths IJPT July-2015 Vol. 7 Issue No Page 8013

4 22. get new path p //get those paths Dr. Anjaneyulu G.S.G.N* et al. International Journal Of Pharmacy & Technology 23. Path= Path {p} // update the Path array if got 24. endfor 25. List= List-<node, path> // deleting the path from the List 26 endfor 27 endif 28. for each edge in EdgeList do 29. get sp1 from Entry to edge s target node // get source node from the Entry point 30. get sp2 from edge s source node to Exit // get source node from starting edge 31. Path= Path {sp1+sp2} // add those two source pointer to the found path 32. endfor 33. endwhile 34. return BPS(P) End Sample Considered: in order to check the effectiveness our algorithm, we consider the case study in form of a simple java program. 1. import java.util.scanner; 2 3 public class testcase { 4 public static void main(string[] args) { 5 int opt, x, y, temp, r, maximum, minimum; 6 boolean next = true; 7 Scanner sc = new Scanner(System.in); 8 System.out.println("please input two integers:"); 9 x = sc.nextint(); 10 y = sc.nextint(); 11 if (x > y) { 12 maximum = x; 13 minimum = y; 14 } else { 15 maximum = y; 16 minimum = x; 17 } 18 System.out.println("options: \n1 get maximum and minimum;"\n2 get greatest common divisor;\nother exit"); 19 opt = sc.nextint(); 20 try { 21 switch (opt) { 22 case 1: 23 System.out.println("maximum of the two numbers is " + maximum); 24 System.out.println("minimum of the two numbers is +minimum); 25 break; IJPT July-2015 Vol. 7 Issue No Page 8014

5 26 case 2: 27 int a1,a2; 28 a1 = maximum; 29 a2 = minimum; 30 if (a1 == a2) 31 throw new MyException(); 32 int a3 = a1 % a2; 33 while (a3!= 0) { 34 a1 = a2; 35 a2 = a3; 36 a3 = a1 % a2; 37 } Dr. Anjaneyulu G.S.G.N* et al. International Journal Of Pharmacy & Technology 38 System.out.println(" the greatest common divisor is " + a2); 39 break; 40 default: 41 break; 42 } 43 } catch (ArithmeticException e) { 44 system out.printin( Error! the number can t be zero!!!"); 45 } catch (MyException e) { 46 System.out.println("Two numbers are equal! \n The greatest common divisor is " + max); 47 } finally { 48 System.out.println("Analysis end!"); 49 } 50 System.out.println("Program end!"); 51 } The control flow graph of the above sample program is as follows in accordance with the proposed algorithm. Fig.1 gives the CFG when normal procedure is followed no exemption is encountered, where as in Fig.2 gives the CFG when certain exceptional cases arise in a particular program. IJPT July-2015 Vol. 7 Issue No Page 8015

6 Figure.1 On the basis of the CFG drawn, the basis path can be generated and can be stated in the following way in a tabular form. As it can be seen from Table 1, compared with the Basis path set of control flow graph, we can find that there increases two paths in ECFG, VI and VII. This is because we consider the effect of exception-handling in ECFG on the control flow. What s more, the basis paths in ECFG include all the codes in the program, which implements complete converges of the codes. IV. Related Work There are two methods to generate basis path set: 1. The Baseline method proposed by McCabe, without algorithm of generating BPS, 2. Depth Finding Strategy proposed by Poole, which is implemented by recursion. In the case of control flow graph, memory overflow is easy to take place. As a result, it is not quite good for automated testing. The method proposed in this paper combines the advantages of the above two methods. Initially, determining the baseline path by Depth Finding Search(DFS), secondly, obtain the BPS by flipping branch nodes. Hence, it becomes quite easy to handle the control flow graph and thus the generation of basis path set automatically. IJPT July-2015 Vol. 7 Issue No Page 8016

7 V. Conclusion: Exception handling increases the cost of software testing and thus increases the overhead also involved in it, while improving the robustness of the software. This paper mainly proposes a method to generate the basis path taking in account the exception handling as well. But still all the paths that are found are not all feasible, hence our work will be to reduce the number of feasible paths and thus reducing the time involved in software testing. VI. References Shahid Mahmood,"A Systematic Review of Automated Test Data Generation Techniques", School of Engineering, Blekinge Institute of Technology Box 520 SE Ronneby, Sweden, October A Method to Determine a Basis Set of Paths to Perform Program Testing Joseph Poole. 4. GRAPH THEORY APPLICATIONS IN DEVELOPING SOFTWARE TEST STRATEGIES FOR NETWORKING SYSTEMS, Vladimir V. Riabov* Associate Professor, Department of Mathematics and Computer Science, River College. 5. xplanation-based generalization of infeasible path Mickaël Delahaye CEA LIST, Software Safety Laboratory Point courier if-sur- Yvette,France,mickael.delahaye@cea.fr Bernard Botella,CEA LIST Software Safety Laboratory Point courrier Gif-sur-Yvette, France,bernard.botella@cea.fr, Arnaud Gotlieb INRIA Rennes,Project Celtique,35042 Rennes Cedex,France,arnaud.gotlieb@inria.fr 6. Weakness in Code with Cyclomatic Path Analysis, Thomas J.McCabe Sr., McCabe Tecnologies, Thomas J.McCabe Jr., McCabe Software, Lance Fiondella, University of Connecticut. 7. Software Testing Methods and Techniques, Jovanović, Irena 8. Corresponding Author: Dr. Anjaneyulu G.S.G.N *, anjaneyulu.gsgn@vit.ac.in IJPT July-2015 Vol. 7 Issue No Page 8017