Modbat [34] is an open-source tool based on extended finite-state machines specialized for testing the APIs of software. A Scala-based domain-specific language is used to create the models with features for probabilistic and nondeterministic transitions, component models with inheritance, and exceptions. Test cases are generated as sequences of method calls to the API that can be directly executed against the SUT. HTG uses a hybrid automaton model or SPICE netlists [28] as input and generates test cases in C++. A data coverage measure based on star discrepancy [29] is used to guide the test generation and ensure the test cases are relatively equally distributed over the possible data space. The generated test cases can be applied to numeric simulation and circuit simulation domains.
The maximum supported EC-GSM-IoT RLC window size of 16 limits the number of RLC blocks that at any given time can be outstanding with a pending acknowledgment status. The base station uses the RRBP field in the RLC header of the EC-PDTCH/D block to poll the device for a Packet Downlink Ack/Nack (PDAN) report. https://www.globalcloudteam.com/ The device responds earliest 40 ms after the end of the EC-PDTCH/D transmission time interval (TTI) as illustrated in Fig. A forced condition is a multiple condition in which
Condition Coverage Testing
any occurrence of the or else operator is replaced with the or
operator, and the and then operator is replaced with the and
- Condition coverage testing is a type of white-box testing that tests all the conditional expressions in a program for all possible outcomes of the conditions.
- Here, we discuss based on some literature references about the differences of system models and test models.
- A testing strategy that is based on the way that data contained within variables is manipulated within a program.
- This would seem to indicate that Multiple Condition Coverage, as the name suggests, only applies to conditionals with multiple statements.
- In [NLZ18] various scheduling designs are compared with the aim of maximizing the transmission reliability.
operator.
3 MBT Tools
The later are created during requirements engineering in special tools (for example DOORS10). To support features like traceability, comprehensibility, coverage measurement, etc. this interface has to be given. Further, the modeling task in industrial projects is mostly done in separate modeling tools (as for example Sparx Systems Enterprise Architect11) and not by using the modeling feature of MBT tools. Surveys on quality assurance show that most of the errors in software are introduced during requirements elicitation within the development process [35].
You need to verify that using this
coverage type does not modify the behavior of the software. Condition coverage is also known as Predicate Coverage in which each one of the Boolean expression have been evaluated to both TRUE and FALSE. Each testing project has some kind of test management tools (from simple Microsoft Excel lists up to advanced tools like HP Quality Center). In such tools, test cases are managed and their lifecycle (create, execute, evaluate) is stored. Since MBT is all about generating test cases and their number can be very high, the direct interface to test management tools is strongly needed.
To fulfil condition coverage, Boolean expression X, Y and Z will be evaluated in TRUE and FALSE form, at least once. Condition coverage is correlated to decision coverage as whenever any decision is to be taken, focus will be on number of possible conditions. The image below shows how TestCompass prompts you to run an impact analysis after you change the model. One of the standout features of TestCompass is its change impact analysis capability.
Most of the diagrams have a simple syntax and fairly clear semantics such that customer and developer can easily learn how to express their requirements more precisely, thus enabling the principle close collaboration. The changes in requirements can easily be made on the already created models, thus improving fast adaptation. Models can also support the conversation between team members, where the results of a discussion can be edited into the models immediately. Also the simplicity principle can be supported by models by using the abstraction, modularization, and decomposition features of modeling. Another challenge of the state-of-the-art MBT is the missing support for non-functional testing. As stated by the survey from Dias Neto et al. [18], most of the MBT approaches concentrate on functional testing, coverage criteria, selection algorithms and the like.
Let us understand how change impact analysis works and how it helps you find the right testing direction with TestCompass. Here, we sketch the ideas of two approaches that are focused on improving the test generation process and the test quality, respectively. Finally, we increment the classical usage of the CertifyIt tool for functional and security testing and integrate it into a MBT as a Service (MBTAAS) environment, which delivers immense value for the IoT community. The adaptation of CertifyIt for the IoT domain has already shown its value, as discussed by the authors in [3] and [45]. Compared with FCCH, EC-SCH, and EC-BCCH that have been described in Section 3.2.6, the EC-CCCH/D channel makes use of CCs introduced in Section 3.2.8, to be able to reach users in different coverage conditions effectively.
The low levels of coverage may have been the result of factor and levels chosen for the covering arrays not sufficiently modeling the possible inputs for each program. The relationship between test suite size and covering array strength varied among the programs tested. This is closely related to decision coverage but has better sensitivity to the control flow. Fault injection may be necessary to ensure that all conditions and branches of exception-handling code have adequate coverage during testing. In summary, for improving the software quality MBT techniques can be combined with and integrated into RE techniques.
For an efficient MBT realization in a project, the interface to such tools is needed. Since test automation tools can be changed within the project life cycle, an abstract interface with tool-specific adapters is strongly encouraged. As discussed above, MBT addresses many challenges in agile development processes. We have shortly discussed the possibilities of how to improve the individual tasks in agile processes in general. For a more concrete discussion of this topic, we refer the interested readers to our paper [40] for an implementation of model-based testing for Scrum. This would seem to indicate that Multiple Condition Coverage, as the name suggests, only applies to conditionals with multiple statements.
Each block for each CC is mapped onto predefined frames in the overall frame structure. A technique that focuses on identifying all the possible distinct states within a module. It is often employed when testing individual objects (the localized maintenance of state being one of the central tenets of object-orientation) or other systems that implement state machines. I might be missing something here but, the way you wrote the code in your question, conditions A and B are completely independent of each other. Unlike Condition Coverage a) all possible combinations and b) the decision outcomes are considered. The number of possible combinations can ‘explode’ in light of big numbers of conditions.
In this work the transmission of one MBytes of firmware data is required in presence of normal application traffic. The performance using unicast transmission is compared to the one using Single Cell Point-to-Multipoint (SC-PTM), a feature introduced in Rel-14 of NB-IoT standard to enable multicast communication. The gains in terms of delivery time introduced by SC-PTM are quite obvious w.r.t. unicast. For unicast mode the delivery time varies from the order of hours to 1 day when increasing the ISD from 500 m to 1732 m, while it varies from the order of minutes to 1 hour for the SC-PTM. This indicates that the effective gains of SC-PTM w.r.t. unicast mode are strictly related to the location of UE. Nevertheless, it is worth emphasizing that while the delivery time is affected by the number of UE in the unicast case, the SC-PTM has a performance that does not vary with the number of UE being served.
Recall that MCDC subsumes branch coverage, which in turn subsumes statement coverage, so full MCDC coverage means that statement and branch coverage were 100% as well. A key feature in the application of MCDC is that tests are constructed based on requirements. Achieving structural coverage is viewed as a check that the test set is adequate, i.e., the MCDC source coverage is not the goal in itself, only a metric for evaluating the adequacy of the test set. Software authors can look at test coverage results to devise additional tests and input or configuration sets to increase the coverage over vital functions. Two common forms of test coverage are statement (or line) coverage and branch (or edge) coverage.
We think, however, that the models that describe the tests can also be complex and allowing for an infinite number of behaviors. Here, we discuss based on some literature references about the differences of system models and test models. Until now, there are only a few comparisons of system models and test models. For instance, Malik et al. [41] state that test models can only be used for testing. In contrast, one of our findings in [71] is that test models can also be used for implementation.
The NB-IoT small cell could transmit up to 15 dBm for adjacent channel with a 1 MHz guard band and there is no angular antenna discrimination. If it is considered, the improvement in the EIRP will be equivalent to the antenna discrimination (16 dB). The maximum allowable EIRP that the IoT devices can transmit varies between 9 and 14 dBm for the best case (Smart Parking) with a 2 MHz guard band. For the most restrictive case (Traffic Congestion) it is possible to transmit between 3 and 8 dBm with the same guard band, being this power enough to ensure a right operation. To efficiently perform the tests, VERA also provides a library containing common vulnerability test patterns for modeling. In this section, we present a representative set of academic and industrial MBT tools for test case generation that we investigated for usage in the IoT domain and discuss their characteristics.
To mitigate this problem the Modified Condition/Decision Coverage metric was created. This website is using a security service to protect itself from online attacks. There are several actions that could trigger this block including submitting a certain word or phrase, a SQL command or malformed data.
