Para generar automáticamente casos de prueba a partir de un modelo de un sistema.
- Metodologías: Ingeniería, Diseño de producto, Gestión de proyectos
Pruebas basadas en modelos

Pruebas basadas en modelos
- Metodología ágil, Mejora continua, Ingeniería de sistemas basada en modelos (MBSE), Seguro de calidad, Control de calidad, Gestión de calidad, Sistema de gestión de la calidad (SGC), Pruebas de software, Métodos de ensayo
Objetivo:
Cómo se utiliza:
- Técnica de prueba de software en la que los casos de prueba se derivan de un modelo que describe el comportamiento esperado del sistema sometido a prueba.
Ventajas
- Puede reducir el tiempo y el esfuerzo necesarios para crear casos de prueba; Puede mejorar la calidad de los casos de prueba.
Contras
- La calidad de los casos de prueba depende de la calidad del modelo; Puede ser complejo crear y mantener el modelo.
Categorías:
- Ingeniería, Calidad
Ideal para:
- Generación automática de casos de prueba para un sistema de software complejo, como una máquina de estados o un sistema de control.
Model-Based Testing (MBT) is particularly effective in industries where systems are highly regulated or require adherence to specific standards, such as aerospace, automotive, telecommunications, and healthcare. In these sectors, products often involve intricate requirements and behaviors that can be accurately represented through models, such as state machines, which illustrate various states and transitions of a system. During the design and verification phases of a project, teams can employ MBT early on, facilitating a shift-left approach in software development, where testing occurs concurrently with design and coding. Participants typically include software developers, quality assurance engineers, and systems architects, who collaborate to ensure that the model accurately reflects the intended behavior of the software. The automatic generation of test cases from these models not only diminishes the manual effort involved in test design but also yields a higher degree of test coverage, as it allows for the exploration of every potential pathway within the system. This methodology also enhances traceability, as each test case can be directly linked back to the requirements outlined in the model. Common tools that support MBT include IBM Rational Test Workbench, Spec Explorer, and Conformiq, each offering unique capabilities to further optimize the testing process. By implementing model-based approaches in their testing strategies, organizations can reduce time to deployment and increase confidence in software reliability, ultimately resulting in fewer defects and enhanced user satisfaction.
Pasos clave de esta metodología
- Define the system under test and its requirements through model specifications.
- Create a formal model representing the expected behavior, such as state machines, flow charts, or petri nets.
- Ensure the model accurately captures the functional and non-functional requirements.
- Derive test cases automatically from the formal model using model-based testing tools.
- Execute the generated test cases against the system under test.
- Evaluate test results based on model expectations and identify discrepancies.
- Refine the model and test cases based on feedback and observed outcomes.
- Iterate the process as necessary to ensure comprehensive coverage and validation of the system.
Consejos profesionales
- Utilize model diversity; leverage different modeling languages and notations, like UML or statecharts, to capture system behaviors comprehensively.
- Implement mutation testing on generated test cases to assess their effectiveness and identify gaps in the model that may lead to undetected faults.
- Incorporate feedback loops early in development from stakeholders to iteratively refine the model and ensure alignment with system requirements.
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