Model-Based Tester Extension
To be eligible for the Model-Based Tester Foundation Extension certification exam, one must have earned ISTQB CTFL Certification. To improve the test process’s efficacy, professionals adopt model-based testing (MBT) to help create automated test designs and allow for easier test suite maintenance. Building models aim to describe the requirements for test generation and eliminate any defects at this stage. Software testers can choose this certification as their entry to the CTFL-MBT testing path.
Model-Based Testing Overview
When testing is performed in an app or software, there are multiple distinct ways that a developer can compare the process. Generating efficient test facts can help make the model more robust and provide better results for a team.
A comprehensive outline of model-based testing includes:
- Tell a model that works for your software.
- Determine which kinds of input will be added to this model.
- Determine what you require based on each test.
- Execute the different tests.
- Compare the test results with your expected outcome to decide what steps to follow next based on these model tests.
You will have to choose a modeling language. A lot of many developers choose the unified modeling language, also recognized as UML. This is a general-purpose modeling language that provides for visual models to be created.
Model-based testing is an innovative test method to increase the effectiveness and efficiency of the test process. A model-based tester on a project does models to drive test analysis and design. It keeps the interest of the models for other testing activities such as test implementation and reporting. This CTFL-MBT course is ideal for testers experienced with the development of web-based, PC, and client-server applications, entry-level testers with interest in model-based testing, and modeling software engineers.
Model-Based Testing is a software testing technique where the software’s runtime behavior under test is checked against a model’s predictions. A model is a description of a system’s behavior. Behavior can be expressed in input sequences, actions, conditions, output, and data flow from input to work. It should be practically proper and can be reusable; shareable must have a detailed description of the system under test.
The Challenges of Model-Based Testing
The move towards models holds great promise, but it also introduces new challenges that must be addressed before you can get the full benefits of CTFL-MBT. The work starts by training the software developers and testers on model-based testing. The learning out is steep. While software developers are easy with coding paradigms, they still need testing knowledge, and they still need to understand how to develop testable applications. Testers will need to learn a new concept of modeling over traditional testing methods.
Before diving into CTFL-MBT head-first, invest in the infrastructure. Modeling is hard. Take the time to study architecture. The tool must be scalable, and it should manage multiple models and provide reliable test coverage. It will need more important upfront time for the original implementation of the tool. It will offset the long-term goal of reduction of test resources and increased test coverage. Fine-tuning the CTFL-MBT tool parallel with creating models could be challenging and can result in refactoring the tool.
The adoption of CTFL-MBT starts by implementing modeling into the development workflow. It might be a test since it requires a shift in mindset and culture regarding developing and testing applications. It is crucial to modify the front-end application code to improve the testability, fixing bugs while creating models for the system under test.
Harder, Better, Faster, Stronger
Of course, there are challenges with Model-Based Testing in that it requires a lot of upfront work to save time and costs, later down the line, across multiple projects and portfolios. It also needs significant upskilling with a steep learning curve, and you need developers who understand the testing and vice versa. It is also challenging to build a model that all those affected across the SDLC understand.
That said, the advantages to end-users far outweigh the original challenges. By reinforcing the concept that QA should be built in from discovery onwards, it enables the earliest bug detection in design and spec, meaning fewer bugs in development and live. The increased automation frees up testers to do other mission-critical work and means that better software gets into the end-users hands faster. It also simplifies Model-Based testing and makes it more accurate and, all of these factors make testing a more enjoyable career choice!
ISTQB Cert 