There are too many permutations and combinations are involved in designing a testing workflow of an application, testing countless business flow becomes a challenge.
It also increases the chance of missing a step or two in the entire process; hence businesses bank on innovative testing approaches like model-based testing.
What Is Model-Based Testing?
The model-based testing approach helps you generate test cases automatically using application models. No doubt it’s a modern software testing approach that uses secondary, lightweight implementation of a software build – also called a model.
The model uses real-world functions and exhibits the expected behavior of the system under the test. A model consists of business logic in the form of a few lines of code.
Besides the model, another program called driver sends the same information to the software under test (SUT) and the model.
Then it compares the input results to ensure they are the same. Different results are considered a failure and get examined later.
Model-based testing requires the model’s application component to be simulated, driven by the driver program, and compared by the results. This is the criteria for an element to test with MBT.
To perform model-based testing, you need a higher order of thinking, as traditional or linear testing approaches don’t work. Also, the MBT test writer needs to be technically strong.
Testers who write MBT tend to be either strong enough technically to be production programmers or to partner in some way with production programmers to get the test creates.
Model-based testing helps you find memory leaks and potential conflicts that can crash the software. However, unlike MBT, automated tests can submit random input and run for an extended time without qualifying for model-based tests.
Instead, batch applications that take a single piece of information (like a file) and produce a single output (like populating a database) are the easiest to get started with MBT.
Understand Model-Based Testing With an Example:
Suppose a user is at the login page of a web application. There are three possibilities that a user can explore:
- First Stage: Instant login by entering user id and password.
- Second Stage: The user might go forward with forgot password option.
- Third Stage: Reset password by following the instructions
Once the user decides which option to pursue, it can come back from the second and third states to the first. These steps can be drawn as a flow or sequence using the state transition diagram, and it can become the simplest model for a login scenario.
Like this, multiple models could be drawn for the entire application with several permutations and combinations of the user and data flows and can be interconnected.
As the state transition diagrams are ready, the automated validation tools are validated different permutations and combinations of the functions and data flows. These tools generate test cases from the state transition diagrams automatically.
Why Model-Based Testing Is Required?
Model-based testing helps you identify that whether test cases are performing actions in the same sequence or not?
It’s a widely popular testing technique; hence it is integrated with the other testing approaches. Various tools are developed to support this type of technique these days.
Once a tester implements this technique in the overall testing approach, it monitors the software behavior against the model’s prediction during the runtime.
Usually, the behavior of a system depends upon the actions, sequence, conditions, and input/output flow of a process. This system model different behavior like data flow, control flow, state transition machines, decision tables, and dependency graphs.
Popular Model-Based Testing Tools:
- fMBT: This tool is developed by Intel to create test cases from models written in Python language automatically. Besides generating test cases automatically, it executes tests to enhance the overall test coverage.
- Graphwalker: This tool also creates test cases automatically, but it’s an open-source model-based testing tool. It simplifies the creation of test cases by using graphs and generates a path that is used to design test cases.
- TOSCA: This is a renowned tool to perform model-based testing. By using this tool, the tester can create test cases by modeling the application.
Advantages of Model-Based Testing:
- Already this testing approach leverages automation, but there is always an opportunity available to take it to the next level.
- Using MBT, you can also implement other testing methods and can turn them into comprehensive testing. Besides this, If you change something using different testing approaches, you can correct those changes with model-based testing.
- This testing technique can include finite state machines, unified model diagrams, and statecharts.
Disadvantages of Model-Based Testing:
- The testing purpose system always needs formal specifications while changes are made according to different combinations.
- The concept needs higher skills to master it completely, hence for users, the learning curve could be overwhelming and could lead to failure.
- To make model-based testing part of your testing approaches, you will need to train testers, and the current testing approaches will need to be improvised.
Conclusion:
Generally, testers make test cases for applications and perform the test accordingly. However, model-based testing uses a different approach.
Instead of testing the entire application using the test cases, it helps testers create data flow of various functionalities of the applications and enables them to test the predictions made by the data flow against the actual result during the runtime.
It’s an advanced testing concept, and that’s why testers have higher technical skills to master it completely.
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FAQ
Q1.What are Benefits of Model-Based Testing?
MBT offers several benefits that contribute to enhanced software QA:
a. Improved Test Coverage.
b. Early Bug Detection.
c. Efficient Test Automation.
d. Requirements Traceability.
Q2. What are Real-World Applications of Model-Based Testing?
MBT finds applications across various industries and domains. Some notable applications include:
a. Automotive Software Testing.
b. Financial Systems Testing.
c. Medical Device Testing.
d. Internet of Things (IoT) Testing.