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  4. Model-based testing (MBT)

A test case consists of a sequence of function calls to the implementation of the system. Usually test adapters are used to connect the testing tool to the implementation. A test adapter converts the abstract function calls generated by testing tool to concrete function calls with correct format and data.

In this project, we focus on the properties of the test adapters for ModelJUnit programs and we investigate different aspects of effective development of such test adapters. Jump to: navigation , search. Category : StudentProject. Personal tools Log in.

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In this project different aspects of generating test adapters for ModeJunit programs are investigated. Mark Utting and Bruno Legeard. Mahsa Varshosaz , Mohammad Reza Mousavi. The tools used to create the models used in model-based testing are normally very similar to those uses by developers, and could be identical in some cases. Where hybrid notations are used then open source development tools can be reasonably easy to modify, even though in the future it is expected commercial development tool vendors will provide the essential added functionality for testers. The tools for test case generation are particular to the model notation used and the test coverage criteria to be achieved.

These tools are not currently used in traditional software testing or development and they are specific to model-based testing.

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Because of their belief on the input model, they are generally closed to the tools used for model generation. Test execution is performing in the same way for model-based testing as like traditional testing, so the same tools can generally be used. A list of model-based testing tools and the modeling notation they support is shown in below figure.

At present there are no standards that particularly support model-based testing; however there are different standards that can be used from other areas of software engineering. For instance, the most probably candidate for the test model is the new UML 2. The output from the test generation tool is a test suite or a sequence of test cases. If in the future model-based testing tools converse using standard data formats, then users will be able to select between combinations of tools for each of the three main stages rather than being tied to a single tool and supplier, with all the inherent economic and technological limitations that this brings.

The algorithms used for test creation and their equivalent coverage criteria are correlated by the same coverage measurement. There are some test coverage measures defined in BS [8], and even if these were originally defined to support component testing, some of the measures, such as state transition coverage, may be suitable for used in model-based testing.

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They are appears to be lack of in-depth knowledge in this area of the model-based testing approach. Some basic coverage measures are usually understood, but the more complex measures necessary for sensible coverage of large state models appear to be either proprietary, or in any case not well-understood by the testing community. For model based testing to become accepted on a wider scale, the test coverage achieved by the approach that should be both widely understood and accepted. Thus allowing model-based testing to be more likely compared with traditional testing and the best way for this to happen is for these measures to be consistent.

At some point in the near future there will also come a requirement for a consistent model-based testing methodology, to provide a familiar understanding of the approach. Many studies has been shown that model based testing is effective, mainly when used to test small applications, embedded systems, user interfaces and state-rich systems with practically complex data.

Understanding model-based testing

Rosaria and Robinson interfaces, Agrawal studied testing graphical user and Whittaker embedded control software and Avritzer and Larson phone systems. Usually the mainly attractive attribute of model based testing is idea to be the automatic generation of test cases, but that is not all. Model of software may help refining uncertain and badly defined requirements [10].

By eliminating model defects before the coding starts and automating the test case creation the result is considerable cost savings and higher quality code. Other benefits that are more related to testing include e. Comprehensive tests; if the model is an entire abstraction of the software, it is likely to automatically generate test cases which cover each possible transition of the model by using graph algorithms.

Defect discovery; model based test automation discovers defects more successfully than manual methods. The article established this with a case study in which manual method uncovered 33 defects in a system, and model based method all of those and in calculation 56 more. As it was shown in this section the benefits of model based testing are huge if modelling and all the related tasks are done powerfully, but it also has some difficulties and drawbacks.

Almost every research on model based testing agrees on one thing: deployment of model based testing into an organization requires considerable efforts and investments.

Practical Model-Based Testing: A Tools Approach

In [12], the following three reasons for the desirable efforts and investments are offered:. Excessive amount of skills is necessary from the testers.

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They need to be well-known with the model, which means knowledge of dissimilar forms of state machines, formal languages, and automata theory. In accumulation, expertise in tools and scripts is essential when test automation is going to be used. A large initial effort in terms of man-hours is required. The type of the model has to be carefully chosen, different parts of software must be separated so that the modelling is easier because of the smaller areas and the actual model has to be built.

Models themselves have also several drawbacks. The main one of those is the explosion of state-space required. Even a simple application can hold so many states that the maintenance of the model becomes complicated and tedious task. As can be shown from the list, model based approach to software testing is not the perfect solution.

The positive side though is that all the points in the list can be overcome with thorough planning of the deployment of model based testing into an organization. Before anybody goes to using model-based testing, they must be sure that the approach is suitable for their circumstances. The creation of test models is clearly a large up-front cost, but this must be recouped by the lower maintenance costs when the system is prepared. Certainly, if the system is estimated to have low maintenance costs, then the test modelling costs should not be recouped by the potential maintenance savings of model-based testing until much later in the maintenance phase.

Low maintenance costs may be predicted, for example, if the system is planned to have only a short operational life or it is expected that there will be mainly few changes to the system required by the users and its environment. Obviously the application must be appropriate for modelling in a supported notation. As stated in advance, switching applications have been found to be mainly suitable, as they are well-suited to modelling as a state model and there is good tool support for this [11].

The application should also be considered significant enough to warrant the cost of model-based testing. If high quality is not important to the customer then model based testing will be unlikely to be cost effective. The complexity of performing traditional testing of simultaneous applications could also act as a driver towards using model-based testing, where the mix of many test cases and systematic test case generation provides good test coverage of complex models.

Model-based testing (MBT)

Because the tests are generated from a model of the application, It is needed only update the model to generate new tests when the application changes. This makes model-based tests far easier to maintain, review and update than traditional automated tests. Testers who are willing and able to create model-based test programs can create flexible, useful tests for the cost of a general-purpose test language tool. Good software testers cannot avoid models. MBT has emerged as a useful and efficient testing method for realizing adequate test coverage of systems.

Model-based testing has already been used effectively on a number of projects and the number of applications for which model-based testing will be appropriate will carry on to grow. A number of factors will make this growth. Second, more commercial quality tool support will become offered. Model-based testing will not, however, be suitable for all situations.

There will still be projects where no explicit model of necessities is available and testing needs to be finished before the end of next week. There will also be situations where the available testers are not professional software engineers, but simply those re-assigned from other parts of the organization that are currently free. Dalal, A.