Abstract
There are many cases where the development and testing of data-intensive applications need to be supported without the prior existence of data. Our work presents a dynamic test data generation framework for testing such applications. This capability is important, when the data is confidential and cannot be given to the test person for security reasons or when the application is in its development phase and real data does not yet exist. The proposed solution dynamically intercepts queries made by the application under test and creates appropriate data based on user requirements. This approach does not require access to the source code of the application under test, which could also be confidential. Data generation can be controlled to achieve desired data and query result patterns, including realistic data or data with higher test quality. The paper concludes with experiments that demonstrate the coverage and performance aspects of the solution.
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References
http://www.ibm.com/software/data/optim/core/data-privacy-solution/
IBM DB2 Test Data generator, http://www.ibm.com/software/data/optim/protect-data-privacy/
Emmi, M., Majumdar, R., Sen, K.: Dynamic Test Input Generation for Database Applications. In: Proceedings of the 2007 International Symposium on Software Testing and Analysis (ISSTA 2007), pp. 151–162. ACM, New York (2007)
Sen, K., Marinov, D., Agha, G.: CUTE: a Concolic Unit Testing Engine for C. In: Proceedings of the 10th European Software Engineering Conference Held Jointly with 13th ACM SIGSOFT International Symposium on Foundations of Software Engineering (ESEC/FSE-13). ACM, New York (2005)
Sen, K.: DART: Directed Automated Random Testing. In: Namjoshi, K., Zeller, A., Ziv, A. (eds.) HVC 2009. LNCS, vol. 6405, p. 4. Springer, Heidelberg (2011)
Păsăreanu, C., Mehlitz, P., Bushnell, D., Gundy-Burlet, K., Lowry, M., Person, S., Pape, M.: Combining Unit-Level Symbolic Execution and System-Level Concrete Execution for Testing Nasa Software. In: Proceedings of the 2008 International Symposium on Software Testing and Analysis (ISSTA 2008), ACM, New York (2008)
Veanes, M., Grigorenko, P., Halleux, P., Tillmann, N.: Symbolic Query Exploration. In: Breitman, K., Cavalcanti, A. (eds.) ICFEM 2009. LNCS, vol. 5885, pp. 49–68. Springer, Heidelberg (2009)
Taneja, K., Zhang, Y., Xie, T.: MODA: Automated Test Generation for Database Applications via Mock Objects. In: Proceedings of the IEEE/ACM International Conference on Automated Software Engineering (ASE 2010), pp. 289–292. ACM, New York (2010)
Binnig, C., Kossmann, D., Lo, E., Özsu, T.: QAGen: Generating Query-Aware Test Databases. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data (SIGMOD 2007), pp. 341–352. ACM, New York (2007)
Khalek, S., Elkarablieh, B., Laleye, Y., Khurshid, S.: Query-Aware Test Generation Using a Relational Constraint Solver. In: Proceedings of the 2008 23rd IEEE/ACM International Conference on Automated Software Engineering (ASE 2008), pp. 238–247. IEEE Computer Society, Washington, DC (2008)
Bruno, N., Chaudhuri, S., Thomas, D.: Generating Queries with Cardinality Constraints for DBMS Testing. IEEE Trans. on Knowl. and Data Eng. 18(12), 1721–1725
Tuya, J., Suárez-Cabal, M., De la Riva, C.: Full Predicate Coverage for Testing SQL Database Queries. Software. Test. Verif. Reliab. 20(3), 237–288 (2010)
De la Riva, C., Suárez-Cabal, M., Tuya, J.: Constraint-Based Test Database Generation for SQL Queries. In: Proceedings of the 5th Workshop on Automation of Software Test (AST 2010). ACM, New York (2010)
Jackson, D.: Alloy: A Lightweight Object Modeling Notation. ACM Trans. Softw. Eng. Methodol. 11(2), 256–290 (2002)
Grandison, T., Liu, K., Domany, T.: End-to-End Data De-identification (EDDI): Capitalizing on an Emerging Market. In: IBM Academy of Technology Security and Privacy Symposium, Yorktown, New York (2007)
Apt, K.: Principles of Constraint Programming. Cambridge University Press, New York (2003)
Rossi, F., Van Beek, P., Walsh, T. (eds.): Handbook of Constraint Programming. Elsevier (2006)
Naveh, Y., Rimon, M., Jaeger, I., Katz, Y., Vinov, M., Marcus, E., Shurek, G.: Constraint-Based Random Stimuli Generation for Hardware Verification. AI Magazine 28(3) (2006)
http://www.ibm.com/software/integration/optimization/cplex-optimization-studio/
MySQL open source database, http://www.mysql.com/
Marick, B.: The Craft of Software Testing, Subsystem Testing Including Object-Based and Object-Oriented Testing. Prentice-Hall (1985)
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Adir, A., Levy, R., Salman, T. (2012). Dynamic Test Data Generation for Data Intensive Applications. In: Eder, K., Lourenço, J., Shehory, O. (eds) Hardware and Software: Verification and Testing. HVC 2011. Lecture Notes in Computer Science, vol 7261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34188-5_19
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DOI: https://doi.org/10.1007/978-3-642-34188-5_19
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