A novel approach for regression testing of web applications

Автор: Munish Khanna, Naresh Chauhan, Dilip Sharma, AbhishekToofani

Журнал: International Journal of Intelligent Systems and Applications @ijisa

Статья в выпуске: 2 vol.10, 2018 года.

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Software testing is one of the most arduous and challenging phase which is to be implemented with the intention of finding faults with the execution of minimum number of test cases to increase the overall quality of the product at the time of delivery or during maintenance phase. With the ever increasing demand of web applications and to meet never ending customer expectations, updations are to incorporate which will be validated through testing process. The structure of the web applications (dynamic website) can be modeled using weighted directed graph which consists of numerous paths starting from homepage (index page) of the website. For thorough testing of the website each and every path of the graph should be tested but due to various constraints like time, money and human resources it becomes very much impractical. This scenario ultimately gives rise to the motivation for the development of technique which reduces the number of paths to be tested so that tester community can test only these numbers of path instead of all possible paths so that satisfactory number of faults can be exposed. In this proposed approach assignment of weights on the edges of the directed graph takes place on the basis of the organization of the website, changes in the structure of the website at page level, experience of the coder and the behaviour of the users who have visited the website earlier. The most fault prone paths are identified using random, greedy, Ant Colony Optimization (ACO) and Artificial Bee Colony Optimization (ABCO) algorithms. Two small size websites and one company’s website, and their two versions, were considered for experimentation. Results obtained through ACO and ABCO are promising in nature. This approach will support testing process to be completed in time and delivery of the updated version within given hard deadlines.

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Artificial Bee Colony Algorithm, Ant Colony Algorithm, User Session based web testing, Web Application Testing, Test case Reduction and Regression Testing

Короткий адрес: https://sciup.org/15016462

IDR: 15016462   |   DOI: 10.5815/ijisa.2018.02.06

Список литературы A novel approach for regression testing of web applications

  • Sharma, Girdhar, Taneja, Basia,Vadla and Srivastava , “Software Coverage :A Testing Approach Using Ant Colony Optimization”, Springer-Verlag Heidelberg2011
  • Srivastava,Baby and Raghurama, “An approach of Optimal Path Generation using Ant Colony optimization” TENCON-2009
  • Srivastava and Baby ,“Automated Software Testing using Metaheuristic Technique Based on An Ant Colony Optimization”, International Symposium on Electronic system design 2010.
  • Srivastava,Jose,Barade,Ghosh , “Optimized Test Sequence generation from Usage models using Ant Colony Optimization”, International Journal of Software Engineering and Application 2010
  • Bharti Suri and ShwetaSinghal , “Analyzing Test Case Selection and Prioritization using ACO”, ACM SIGSOFT November 2011.
  • YogeshSingh,Arvinder Kaur and Bharti Suri , “Test Case prioritization using Ant Colony optimization”, ACM SIGSOFT July 2010.
  • Praveen Ranjan Srivastava “Structured Testing Using Ant Colony optimization”,IITM December 2010 Allahabad.
  • Bharti Suri, ShwetaSinghal, “Development and validation of an improved test selection and prioritization algorithm based on aco”,International Journal of Relability,Quality and Safety Engineering Vol 1 No.6 World Scientific Publishing Company 2014.
  • Shunkun Yang, Tianlong Man, and JiaqiXu, “Improved Ant Algorithms for Software Testing Cases Generation,”The Scientific World Journal, vol. 2014, Article ID 392309, 9 pages, 2014. doi:10.1155/2014/392309
  • Derviskaraboga,Beyzagoremli, celalOzturk and NurhanKaraboga “A Comprehensive Survey :Artificial Bee Colony(ABC) and applications” ,Springer March 2012.
  • DervisKaraboga and Beyzagoremli “A Combinatorial Artificial Bee Colony Algorithm for travelling salesman Problem“, INISTA IEEE2011.
  • Lam,Raju,Kiran,Swaraj and Srivastava, “Automated Generations of Independent paths and test suite optimization using artificial bee colony”, ICCTSD2011 Elsevier.
  • Chong,Low,Sivakumar,Lay “A Bee Colony optimization for job shop scheduling” , IEEE2006.
  • A Bee Colony Optimization Algorithm for code coverage test suite prioritization IJEST April 2011.
  • Srikanth,Kulkarni,Naveen,Singh and Srivastava “Test Case optimization using Artificial Bee Colony Algorithm” , ACC 2011 Part III CCIS 192 Springer
  • A hybrid Model of Particle Swarm optimization and Artificial Bee Colony Algorithm for Test Case Optimization,Elsevier.
  • Mala,Mohan and kamalapriya, “Automated Software Test optimization framework-and artificial bee colony optimization-based approach” ,IET software 2010 Volume 4 Issue 5 pp 334-348
  • Dahiya,Chhabra and Kumar “Application of Artificial Bee Colony Algorithm to software Testing” , 21st Australian Software Engineering Conference 2010 IEEE
  • Konsaard and Ramingwong ,”Using Artificial Bee Colony for code coverage based Test Suite Prioritization”, 2015 IEEE.
  • Elbaum, Karre and Rothermel “Improving web application testing with user session data”, Proceedings of the 25th International Conference on Software Engineering. IEEE Computer Society, 2003,pp. 49–59.
  • Sampath, Sprenkle, Gibson, Pollock, and Greenwald “Applying concept analysis to user-session-based testing of web applications”, Software Engineering, IEEE Transactions on, vol. 33, no. 10,pp. 643–658, 2007.
  • Sampath and Bryce “Improving the effectiveness of test suite reduction for user-session-based testing of web applications”, Information and Software Technology 54 (2012) 724–738 Elsevier
  • Peng and Lu “User-session-based automatic test case generation using GA” International Journal of the Physical Science July 2011.
  • Qian “User Session-Based Test Case Generation and Optimization Using Genetic Algorithm”, Journal of Software Engineering and Applications 2010
  • Elbaum S, Rothermal G Karre S and Fisher M “Leveraging User-Session Data to support Web application Testing” IEEE Transaction 2005
  • Liu Y, Wang K, Wei W, Zhang B and Zhong H “User session based test cases optimization method based on Agglutinate Hierarchical Clustering” IEEE Conference 2011
  • Maung Mon H and Win ThiK “Entropy based Test cases reduction algorithm for user session based testing”, Advances in Intelligent systems and computing Springer Switzerland 2016.
  • Li J and Xing D ,“User session data based web applications test with cluster analysis”, CSIE 2011 Springer-Verlag Berlin Heidelberg 2011
  • SprenkleS,Sampath S and Souter A “An empirical Comparison of test suite reduction techniques for user session based testing of web applications”
  • Offutt, J. and Wu Y. “Modeling presentation layers of web applications for testing”, Software System Model Springer, pp.257-280 2010.
  • Maung and Win “An Efficient Test Cases Reduction Approach in User Session Based Testing”, International Journal of Information and Education Technology 2015.
  • Sudhir Kumar Mohapatra, SrinivasPrasad, “Finding Representative Test Case for Test Case Reduction in Regression Testing”, IJISA, vol.7, no.11, pp.60-65, 2015. DOI: 10.5815/ijisa.2015.11.08
  • ManikaTyagi, SonaMalhotra, “An Approach for TestCase Prioritization Based on Three Factors”, IJITCS, vol.7, no.4, pp.79-86, 2015. DOI: 10.5815/ijitcs.2015.04.09
  • Abhinandan H. Patil, NeenaGoveas, Krishnan, Rangarajan, “Regression Test Suite Prioritization using Residual Test Coverage Algorithm and Statistical Techniques”, International Journal of Education and Management Engineering(IJEME), Vol.6, No.5, pp.32-39, 2016.DOI: 10.5815/ijeme.2016.05.04
  • Neha Chaudhary, O.P. Sangwan, RichaArora, “Event-Coverage and Weight based Method for Test Suite Prioritization”, IJITCS, vol.6, no.12, pp.61-66, 2014. DOI: 10.5815/ijitcs.2014.12.08
  • Izzat Alsmadi, SaschaAlda, “Test Cases Reduction and Selection Optimization in Testing Web Services”, IJIEEB, vol.4, no.5, pp.1-8, 2012.
  • Samia Jafrin, Dip Nandi, Sharfuddin Mahmood, “Test Case Prioritization based on Fault Dependency”, I.J. Modern Education and Computer Science, 2016, 4, 33-45 Published Online April 2016 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijmecs.2016.04.05.
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