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MutShrink: um método de redução de banco de dados de teste baseado em mutação

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Bibliographic Details
Main Author: Toledo, Ludmila Irineu
Publication Date: 2017
Format: Master thesis
Language: por
Source: Repositório Institucional da UFG
Download full: http://repositorio.bc.ufg.br/tede/handle/tede/7737
Summary: Regression testing for database applications can be a computationally costly task as it often deals with databases with large volumes of data and complex SQL statements (for example, nested queries, set comparisons, use of functions and operators). In this context, some works only select a subset of the database for testing purposes, that is, select data to create a test database and thus improve test efficiency. But usually, the selection of test data is also a complex optimization problem. Thus, this work proposes a method of selecting test data for regression testing on SQL statements based on mutation analysis, called MutShrink. The goal is to minimize the cost of testing by reducing the size of the database while maintaining the same effectiveness as the original database. MutShrink consists of using the result of the generated mutants to evaluate the database and select tuples using filters in these results, selecting reduced sets of test data. Experiments were performed using a benchmark with complex SQLs and database with large data volume. We compared our proposal with the QAShrink tool and the results revealed that MutShrink overcame the QAShrink tool in 92.85 % of cases when evaluated by the Mutation Score metric and 57.14 % of cases when evaluated by the metric Full Predicate Coverage.

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