Evolving the Quality of a Model Based Test Suite

Abstract

Abstract-Redundant test cases in newly generated test suites often remain undetected until execution and waste scarce project resources. In model-based testing, the testing process starts early on in the developmental phases and enables early fault detection. The redundancy in the test suites generated from models can be detected earlier as well and removed prior to its execution. The article presents a novel model-based test suite optimization technique involving UML Activity Diagrams by formulating the test suite optimization problem as an Equality Knapsack Problem. The aim here is the development of a test suite optimization framework that could optimize the model-based test suites by removing the redundant test cases. An evolution-based algorithm is incorporated into the framework and is compared with the performances of two other algorithms. An empirical study is conducted with four synthetic and industrial scale Activity Diagram models and results are presented.

Systematic mapping study on MBT: tools and models

“…Few studies were classified as Experimental Study, Proof of Concepts and Theoretical, representing, respectively, 9.2% (8), 3.45% (3) and 4.6% (4). From the perspective of MBT activities, the most researched MBT activity of the primary studies is the Test Case Generation activity, which represents 65.52% (57), inasmuch other activities represent 34.48% (30), distributed by Test Modelling 16.09% (14), Model Transformation 5.75% (5) and Other 12.74% (11) (Test Case Instantiation [36], Test Data Generation [24, 83], Test Execution [65], Test Oracle [51, 74], Test Validation [57, 80, 107] and Test Data Transformation [34, 104]). Most of the studies describe techniques and methods for generating test cases and only a few describe details on how to create test modelling and to apply model transformation.…”

“…11 Iss. 4 [36], Test Data Generation [24,83], Test Execution [65], Test Oracle [51,74], Test Validation [57,80,107] and Test Data Transformation [34,104]). Most of the studies describe techniques and methods for generating test cases and only a few describe details on how to create test modelling and to apply model transformation.…”

An enhanced test case selection approach for model-based testing

“…For example, transition coverage in a state machine can be determined if traceability has been preserved between a test case and its source state machine. Most coveragebased techniques are re-expressed into optimization problems where the goal is to select the best combination (or permutation in case of prioritization [11]) of test cases to achieve full coverage [17][18][19][20]. For example, in [11] a Greedy search selects, at every step, the test case that covers the most uncovered statements whereas in [12,19] a GA is used to find the maximum coverage.…”

An Application of Software Fault Injection for Assessment of Quality of Test Sets for Business Processes Orchestrating Web-Services

“…Quality of generated test sets is an important issue, as only tests of high quality (high ability to detect faults) can help to provide dependable products (Wagner and Gericke, 2008) (Farooq and Lam, 2009). Several studies have proved validity of the mutation testing as a powerful technique for testing programs and for evaluation of the quality of test sets (Farooq andLam, 2009) (Estero-Botaro, Palomo-Lozano andMedina-Bulo, 2008). A quality of the test set is determined by a ratio of mutants detected by the tests over all non-equivalent mutants (a mutation score).…”