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Previous issue date: 2013-08-02 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / One of the concerns in test Applications Database (ADB) is to keep the operating and
computational costs low. In the context of the ADB, one way to collaborate with this
assumption is ensuring that the Test Databases (TDB) are small, but effective in revealing
defects of SQL statements. Such bases can be constructed or obtained by the reduction of
Production Databases (PDB). In the reductions case, there are combinatorial aspects
involved that require the use of a specific technique for their implementation. In this
context, in response to a deficiency identified in the literature, this work aims to build and
provide a benchmark to enable performance evaluation, using SQL Mutation Analysis,
any search technique that intends to conduct databases reductions. Therefore, to exercise
the search techniques, the benchmark was built with two scenarios where each one
is composed of a PDB and a set of SQL statements. In addition, as a reference for
search techniques, it also contains performance of data database randomly reduced. As
a secondary objective of this work, from the experiments conducted in the construction
of the benchmark, analyses were made with the results obtained to answer important
questions about what factors are involved in the complexity of SQL statements in the
context of Test Mutation. A key finding in this regard was on the restrictiveness of SQL
commands, and this is the factor that most influences the complexity of statements. / Uma das preocupações no teste de Aplicações de Bancos de Dados (ABD) é manter
o custo operacional e computacional baixo. No contexto das ABD, uma das maneiras
de colaborar com essa premissa é garantir que as bases de dados de teste (BDT) sejam
pequenas, porém, eficazes na revelação de defeitos de instruções SQL. Tais bases podem
ser construídas ou obtidas pela redução de grandes bases de dados de produção (BDP). No
caso da redução, estão envolvidos aspectos combinatórios que exigem o uso de alguma
técnica para a sua realização. Neste contexto, em resposta a uma carência identificada na
literatura, o presente trabalho tem como objetivo construir e disponibilizar um benchmark
para possibilitar a avaliação de desempenho, utilizando a Análise de Mutantes SQL, de
qualquer técnica de busca que se proponha a realizar reduções de bases de dados. Sendo
assim, para exercitar as técnicas de busca, o benchmark foi construído com dois cenários,
onde cada um é composto por uma BDP e um conjunto de instruções SQL. Além disso,
como uma referência para as técnicas de busca, ele é composto também por resultados de
desempenho de bases de dados reduzidas aleatoriamente. Como objetivo secundário deste
trabalho, a partir dos experimentos conduzidos na construção do benchmark, foram feitas
análises dos resultados obtidos para responder importantes questões sobre quais fatores
estão envolvidos na complexidade de instruções SQL no contexto da Análise de Mutantes.
Uma das principais conclusões neste sentido foi sobre a restritividade dos comandos SQL,
sendo este o fator que mais influencia na complexidade das instruções.
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.bc.ufg.br:tde/3033 |
| Date | 02 August 2013 |
| Creators | Queiroz, Leonardo Teixeira |
| Contributors | Rodrigues, Cássio Leonardo, Camilo Júnior, Celso Gonçalves |
| Publisher | Universidade Federal de Goiás, Programa de Pós-graduação em Ciência da Computação (INF), UFG, Brasil, Instituto de Informática - INF (RG) |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | Portuguese |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Format | application/pdf |
| Source | reponame:Biblioteca Digital de Teses e Dissertações da UFG, instname:Universidade Federal de Goiás, instacron:UFG |
| Rights | http://creativecommons.org/licenses/by-nc-nd/4.0/, info:eu-repo/semantics/openAccess |
| Relation | -3303550325223384799, 600, 600, 600, 600, -7712266734633644768, 8770386617567581936, -961409807440757778, [1] AGRAWAL, H.; DEMILLO, R.; HATHAWAY, R.; HSU, W.; HSU, W.; KRAUSER, E.; MARTIN, R. J.; MATHUR, A.; SPAFFORD, E. Design of mutant operators for the c programming language. Technical report, Technical Report SERC-TR-41-P, Software Engineering Research Center, Purdue University, 1989. [2] AMMANN, P.; OFFUTT, J. Introduction to software testing. Cambridge University Press, 2008. [3] BARBOSA, E. F.; VINCENZI, A. M.; MALDONADO, J. C. Uma contribuição para a determinação de um conjunto essencial de operadores de mutação no teste de programas c. Simpósio Brasileiro de Engenharia de Software–SBES, 98:33–34, 1998. [4] BERRY, M.; CYBENKO, G.; LARSON, J. Scientific benchmark characterizations. Parallel Computing, 17(10):1173–1194, 1991. [5] BORAL, H.; DEWITT, D. J. A methodology for database system performance evaluation, volume 14. ACM, 1984. [6] BOWSER, J. H. Reference manual for ada mutant operators. Georiga Institute of Technology, Atlanta, Georgia, Technique Report GITSERC-88/02, 1988. [7] BRASS, S.; GOLDBERG, C. Semantic errors in sql queries: A quite complete list. Journal of Systems and Software, 79(5):630–644, 2006. [8] BUDD, T. A.; DEMILLO, R. A.; LIPTON, R. J.; SAYWARD, F. G. The design of a prototype mutation system for program testing. In: Proceedings of National Computer Conference, p. 623–627, 1978. [9] BUDD, T. A. Mutation analysis of program test data [ph. d. thesis]. 1980. [10] CABEÇA, A. G.; JINO, M.; LEITAO-JUNIOR, P. S. Análise de mutantes em aplicações sql de banco de dados. VII Simpósio Brasileiro de Qualidade de Software, 2008. [11] CHAN, W. K.; CHEUNG, S.; TSE, T. H. Fault-based testing of database application programs with conceptual data model. Quality Software, International Conference on, 0:187–196, 2005. [12] CHAYS, D.; DENG, Y.; FRANKL, P. G.; DAN, S.; VOKOLOS, F. I.; WEYUKER, E. J. An agenda for testing relational database applications. Software Testing, verification and reliability, 14(1):17–44, 2004. [13] CIFERRI, R. R. Um benchmark voltado a análise de desempenho de sistemas de informações geográficas. 1995. [14] COUNCIL, T. P. P. Tpc benchmark b. Standard Specification, Waterside Associates, Fremont, CA, 1990. [15] DELAMARO, M.; MALDONADO, J. C. Interface mutation: Assessing testing quality at interprocedural level. In: Computer Science Society, 1999. Proceedings. SCCC’99. XIX International Conference of the Chilean, p. 78–86. IEEE, 1999. [16] DEMILLI, R.; OFFUTT, A. Constraint-based automatic test data generation. Software Engineering, IEEE Transactions on, 17(9):900–910, 1991. [17] DEMILLO, R. A. Mutation analysis as a tool for software quality assurance. In: COMPSAC80, p. 390–393, Chicago, IL, October 1980. [18] DEMILLO, R.; LIPTON, R.; SAYWARD, F. Hints on test data selection: Help for the practicing programmer. Computer, 11(4):34 –41, april 1978. [19] DEREZINSKA, A. An experimental case study to applying mutation analysis for sql queries. In: Computer Science and Information Technology, 2009. IMCSIT’09. International Multiconference on, p. 559–566. IEEE, 2009. [20] DEWITT, D. J. Benchmarking database systems: Past effords and future diretions. Database Engineering Bulletin, 8(1):2–9, 1985. [21] GRAY, J. Benchmark handbook: for database and transaction processing systems. Morgan Kaufmann Publishers Inc., 1992. [22] GRUN, B. J.; SCHULER, D.; ZELLER, A. The impact of equivalent mutants. In: Software Testing, Verification and Validation Workshops, 2009. ICSTW’09. International Conference on, p. 192–199. IEEE, 2009. [23] GUPTA, B. P.; VIRA, D.; SUDARSHAN, S. X-data: Generating test data for killing sql mutants. In: Data Engineering (ICDE), 2010 IEEE 26th International Conference on, p. 876–879. IEEE, 2010. [24] HARMAN, M.; JIA, Y.; LANGDON, W. B. A manifesto for higher order mutation testing. In: Software Testing, Verification, and Validation Workshops (ICSTW), 2010 Third International Conference on, p. 80–89. IEEE, 2010. [25] HARMAN, M.; MCMINN, P.; DE SOUZA, J. T.; YOO, S. Search based software engineering: Techniques, taxonomy, tutorial. In: Empirical Software Engineering and Verification, p. 1–59. Springer, 2012. [26] HU, J.; LI, N.; OFFUTT, J. An analysis of oo mutation operators. In: Software Testing, Verification and Validation Workshops (ICSTW), 2011 IEEE Fourth International Conference on, p. 334–341. IEEE, 2011. [27] JIA, Y.; HARMAN, M. An analysis and survey of the development of mutation testing. Software Engineering, IEEE Transactions on, 37(5):649 –678, sept.-oct. 2011. [28] JOSLIN, E. O.; CHAIRMAN-HITTI, R. Evaluation and performance of computers: application benchmarks: the key to meaningful computer evaluations. In: Proceedings of the 1965 20th national conference, p. 27–37. ACM, 1965. [29] KIM, S.-W.; CLARK, J. A.; MCDERMID, J. A. Investigating the effectiveness of object-oriented testing strategies using the mutation method. Software Testing, Verification and Reliability, 11(4):207–225, 2001. [30] LUCAS JR, H. Performance evaluation and monitoring. ACM Computing Surveys (CSUR), 3(3):79–91, 1971. [31] MA, Y.-S.; OFFUTT, J.; KWON, Y. R. Mujava: an automated class mutation system. Software Testing, Verification and Reliability, 15(2):97–133, 2005. [32] MALDONADO, J. C.; BARBOSA, E. F.; VINCENZI, A. M. R.; DELAMARO, M. E.; SOUZA, S.; JINO, M. Introdução ao teste de software. São Carlos, 2004. [33] MANTERE, T.; ALANDER, J. T. Evolutionary software engineering, a review. Applied Soft Computing, 5(3):315–331, 2005. [34] MONÇÃO, A. C. B. L.; QUEIROZ, L. T.; CAMILO JUNIOR, C. G.; RODRIGUES, C. L.; LEITÃO JÚNIOR, P.; VINCENZI, A. M. Applying genetic algorithms to data selection for sql mutation analysis. Genetic and Evolutionary Computation Conference, 2013. [35] OFFUTT, A. J.; CRAFT, W. M. Using compiler optimization techniques to detect equivalent mutants. Software Testing, Verification and Reliability, 4(3):131–154, 1994. [36] OFFUTT, A. J.; HAYES, J. H. A semantic model of program faults. SIGSOFT Softw. Eng. Notes, 21(3):195–200, May 1996. [37] PAN, K.; WU, X.; XIE, T. Guided test generation for database applications via synthesized database interactions. Technical report, Technical report, UNC Charlotte, 2012, http://coitweb. uncc. edu/˜ xwu/DBGen. [38] PAN, K.; WU, X.; XIE, T. Automatic test generation for mutation testing on database applications. 2013. [39] PÖNIGHAUS, R. ’favourite’sql-statements—an empirical analysis of sql-usage in commercial applications. In: Information Systems and Data Management, p. 75–91. Springer, 1995. [40] PRESSMAN, R. S.; INCE, D. Software engineering: a practitioner’s approach, volume 5. McGraw-hill New York, 1992. [41] RAMEZ, E.; N., S. B. Fundamentals of Database Systems. Pearson, 6a edition, 2005. [42] SHAH, S.; SUDARSHAN, S.; KAJBAJE, S.; PATIDAR, S.; GUPTA, B.; VIRA, D. Generating test data for killing sql mutants: A constraint-based approach. In: Data Engineering (ICDE), 2011 IEEE 27th International Conference on, p. 1175 –1186, april 2011. [43] SHAHRIAR, H.; ZULKERNINE, M. Music: Mutation-based sql injection vulnerability checking. In: Quality Software, 2008. QSIC’08. The Eighth International Conference on, p. 77–86. IEEE, 2008. [44] SUÁREZ-CABAL, M.; DE LA RIVA, C.; TUYA, J. Populating test databases for testing sql queries. Latin America Transactions, IEEE (Revista IEEE America Latina), 8(2):164–171, 2010. [45] TURBYFILL, C.; ORJI, C.; BITTON, D. As3ap: An ansi sql standard scaleable and portable benchmark for relational database systems. The Benchmark Handbook for Database and Transaction Processing Systems, p. 317–358, 1993. [46] TUYA, J.; SUÁREZ-CABAL, M. J.; DE LA RIVA, C. A practical guide to sql white-box testing. ACM SIGPLAN Notices, 41(4):36–41, 2006. [47] TUYA, J.; SUÁREZ-CABAL, M. J.; DE LA RIVA, C. Query-aware shrinking test databases. In: Proceedings of the Second International Workshop on Testing Database Systems, p. 6. ACM, 2009. [48] TUYA, J.; SUAREZ-CABAL, M. J.; DE LA RIVA, C. Sqlmutation: A tool to generate mutants of sql database queries. In: Mutation Analysis, 2006. Second Workshop on, p. 1–1. IEEE, 2006. [49] TUYA, J.; SUAREZ-CABAL, M. J.; DE LA RIVA, C. Sqlmutation: A tool to generate mutants of sql database queries. Mutation Analysis, Workshop on, 0:1, 2006. [50] TUYA, J.; SUÁREZ-CABAL, M. J.; DE LA RIVA, C. Mutating database queries. Information and Software Technology, 49(4):398 – 417, 2007. [51] ZHOU, C.; FRANKL, P. Jdama: Java database application mutation analyser. Software Testing, Verification and Reliability, 21(3):241–263, 2011. |
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