This can be done, e.g., by increasing a variable every time the control flow gets closer to the place where the original variable is set to the desired value. With this technique, they were able to improve evolutionary test generation considerably. Tcases [38] is a combinatorial testing tool to test system functions and generate input testing data. An XML document defining the SUT as a set of functions is required as input as well as the data space for variables of the functions. The test generation is guided by a predefined data coverage level, through which the number of generated test cases can be controlled. The test cases are in stored XML and can be transformed to JUnit test cases via an integrated convector.
The number of enumerated branches is the number of
distinct available cases for each composition of logical operators
(standard or derived, but not overloaded). Two branches are enumerated for each boolean basic
condition, and one per case basic condition. In order to ensure complete Condition coverage criteria for the above example, A, B and C should be evaluated at least once against “true” and “false”. However, this set of tests does not satisfy branch coverage since neither case will meet the if condition.
- For instance, Malik et al. [41] state that test models can only be used for testing.
- Condition/decision coverage requires that both decision and condition coverage be satisfied.
- The generated test cases can be applied to numeric simulation and circuit simulation domains.
- One possibility is to cover the customer requirements, which directly correlates with several agile principles.
- This allows testing parts of the target software that are rarely or never accessed under normal conditions, and helps reassure that the most important conditions (function points) have been tested.
Especially the automation of the test design task, which is the most costly and time-consuming part in testing, leads to more efficiency. Test automation is the key for assuring working software, frequent delivery, sustainable development, and a constant pace. In [FTC+19] it is considered another important scenario for mMTC communication, that is over-the-air firmware update. Given the presence of many devices per cell, a simple unicast update of the firmware generates a considerable amount of traffic which should be processed properly in order to avoid network saturation.
Decision or branch coverage is a measure of branches that have been evaluated to both true and false in testing. When branches contain multiple conditions, branch coverage can be 100% without instantiating all conditions to true/false. The EC-PDTCH/U peak physical layer data rate matches the EC-PDTCH/D 489.6 kbps across the 20 ms TTI. For devices only supporting GMSK modulation on the transmitter side, the highest modulation and coding scheme is MCS-4, which contains a RLC/MAC header of 4 octets and a single RLC block of 44 octets.
The evaluation assumptions used when deriving these performance figures are the same as presented in Section 4.2.1. Before an application is purchased or accepted, and especially when a system fails, one of the first questions that will be asked is “How well was it tested? ” A variety of measures have been developed to answer this question, based on the extent and manner in which components of the system have been exercised. Code coverage is one component to the answer for this question, so it is natural to consider how CT relates to code coverage.
Multiple Condition Coverage Testing
Tables 4.4 and 4.5 summarizes the findings of this and the previous section in terms of MAC-layer data rates supported at 164 dB MCL and the peak physical layer data rates experienced under error-free conditions. In addition, it presents the MAC-layer data rates simulated at coupling losses of 154 and 144 dB. For the 33 dBm device MCS-1 is providing the best performance at 164 and 154 dB coupling loss. At 144 dB coupling loss MCS-3 is the best choice in the uplink even when 8PSK is supported, while MCS-4 provides the highest data rate for the downlink.
In this case, selecting a weaker coverage criterion is a practicable solution. If even the application of weak coverage criteria results in too large test suites, other selection techniques like proposed in [29] can be used. MoMuT is a set of model-based test case generation tools that work with the UML state machine, timed automata, requirement interfaces, and action systems [35]. A fault localization mechanism is included in MoMuT for debugging purposes when a test case fails.
This modification forces the evaluation of the
second member of these operators. You can use this coverage
type after modified conditions have been reached to ensure that all
Model-Based Testing for Internet of Things Systems
the contained basic conditions have been evaluated. With this
coverage type, you can be sure that only the considered basic
condition value changes between both condition vectors.
In practice a large number of mutants are created automatically, each containing one fault. Condition coverage testing is a type of white-box testing that tests all the conditional expressions in a program for all possible outcomes https://www.globalcloudteam.com/ of the conditions. Finally, not only test cases for manual, but also test scripts for automatic execution are generated in MBT. The automatic execution is done by test automation tools with their own syntax and semantic.
Thus, due to the small packet sizes involved, increasing the granularity helps to decrease the waiting time of UEs which improves both the success rate and the 95th transfer delay percentile. In [MPLC16] it is studied the possibility to enable mMTC applications by sharing the UHF spectrum with DTT. The proposed scenario considers a DVB-T2 network offering fixed rooftop reception as a primary service and NB-IoT network as a secondary service allocated to DTT white spaces. The results indicate that it is not feasible to allocate the NB-IoT carrier within the DVB-T2 channel, because of low power (between -38 and -36 dBm) that could transmit the small cell without interfering with the DVB-T2 channel.
Line coverage reports on the execution footprint of testing in terms of which lines of code were executed to complete the test. Edge coverage reports which branches or code decision points were executed to complete the test. The meaning of this depends on what form(s) of coverage have been used, as 67% branch coverage is more comprehensive than 67% statement coverage. Structural testing approaches are often referred to as white box or glass box. They are also sometimes referred to as Adequacy Criteria which reflects the perception of test data in terms of structural coverage criteria. For example, for a given program, if a set of test data exercises all statements then the set is described as being statement testing, or statement coverage, adequate.
Additionally, what impact does the input model have on the relationship between covering array strength and coverage? We briefly review some of the more widely used measures and then consider results relating t-way testing to these measures. This data rate can be compared with the often referred to physical layer data rate of 489.6 kbps that can be reached across the EC-PDTCH/D 20 ms TTI. High data rates on link level can be translated into a high spectral efficiency, which is of importance for the system as a whole in terms of system capacity.
PragmaDev Studio [37] is a commercial tool with complete support for all the MBT steps. This toolset allows users to create the MBT models in SDL and correspondingly generates the test cases in TTCN-3. PragmaDev Studio integrates with the core of DIVERSITY and uses the symbolic execution algorithm for test case generation and the MBT model validation.
Thus, the choice of using either unicast or SC-PTM depends on the number of UE to be served and their coverage class. A testing strategy that is based on the way that data contained within variables is manipulated within a program. In contrast to other structural testing strategies which use control flow information to determine test criteria, data flow testing looks at the way that variables are used. Variables are categorised as being defined (assigned some value) or used (referenced in some way). The essence of data flow testing is to exercise all possible pairs of definition and usage (i.e. ways in which variables can be given values which can be subsequently referenced).
For the individual device the support of a flexible range of data rates in combination with a proper link adaptation equates to improved latency and battery life when radio conditions improve. In the downlink, a device is dynamically scheduled on its assigned resources and a base station will in best case transmit eight MCS-9 blocks on the eight assigned time slots during four consecutive TDMA frames. Each MCS-9 block contains an RLC/MAC header of 5 bytes and two RLC blocks, each of 74 bytes.