Combining Model-Based Testing and Failure Modes and Effects Analysis for Test Case Prioritization: A Software Testing Approach

Abstract

Due to The complexity of modern software projects and the increasing size of software systems, it becomes difficult to manually perform tests with limited resources. Also, manual testing cannot assure that the software is tested using all possible combinations of inputs. Therefore, automate software testing activities have become primordial in the Software Development Life Cycle (SDLC). Model-based testing is a prominent validation technique in software testing that uses models of the system under test to automatically generate test cases; this generation leads to a large number of test cases; which cannot exhaustively be executed, due to time and cost constraints. Moreover, the test-cases execution order has an influence on the rate at which faults can be detected. Therefore, it is essential to prioritize test cases in order to execute the most important with limited time and cost. On the other hand, The Failure Mode and Effects Analysis (FMEA) considered as one of the formal techniques to do risk based testing. It offers a structured methodology to identifying the system failure modes, analyzing their effects and setting up controls to risk reducing and improve the quality of systems or products. By applying such a technique to Model-based testing projects, we can benefit from FMEA analysis and the automating in same project. Through this paper, we introduced a new model based testing approach for prioritizing and ranking test cases according to the requirements and failure modes. In the suggested approach we used the Failure Mode and Effect Analysis methodology in model based testing way to automatically generate a set of pair {test case, priority number} to prioritize test cases. It differs from existing approaches in that it generates two types of test cases; requirement-based test cases and failure mode-based test cases. For the purpose of experimental evaluation and analysis, we will compare the suggested approach with some well-known prioritization methods and we will present a case study to illustrate the potential application of the proposed approach in a future work.

Classification of Heart Disease Using Cluster Based DT Learning

“…A call tree uses a treelike model of determinations and their possible results, together with happening results, asset costs and utility (Meriem and Abdelaziz, 2019). It is a system to demonstrate algorithmic approach to decide that exclusively contains restrictive administration articulations.…”

Estrategia integrada de pruebas de software consciente de la situación y basada en escenarios

“…En otros trabajos que presentan enfoques o estrategias de pruebas de software (Bhattacharjee et al, 2007;Chen & Jones, 2007;de Souza Doreste & Travassos, 2020;Lei et al, 2007;Meriem & Abdelaziz, 2019;Pei et al, 2017), también se puede observar que solo especifican el 2 do y/o el 3 er pilar de una estrategia integrada, sin considerar un soporte terminológico/semántico como un glosario, taxonomía u ontología. En otras palabras, estos trabajos solo documentan procesos/actividades/pasos a seguir y/o algoritmos/métodos/herramientas.…”