Verification and Validation Sample Clauses

Verification and Validation. Verification is done for both models. Verification is to test whether the model does what we expect it does. The verification is divided into two parts: the extreme value tests and compares the output of the simulations with exact calculations. In Appendix H the verification of the Min-max model is given. In Appendix I, the verification of the Lead-time model is provided. For the extreme value test, extreme values are assigned to the input parameters; respec- tively to the turn-around stock, the number of servers, the minimum level or threshold, the lead-times or total requirements and the repair times. For example the turn-around stock is set equal to 0 and 100 while the values of the other input parameters remain unchanged. For every case one run is simulated and it is checked whether the output of the simulations was as expected. The results clearly show that the model works as expected. For the com- parison with the exact calculation for one parameter setting, different KPIs are calculated using formulas. For this parameter setting 20 simulations are run. The values of the exact calculation are compared with the values of the 20 simulation runs using a statistical t-test. In the appendices the methods are explained in more detail. During the validation we tested whether the outcome of the model correspond to the outcome in the real situation. To test whether this is the case the Min-max As-Is situation is simulated. As this situation is most similar to the current situation at NedTrain. The average fill rate obtained from the simulation is equal to 0.84 (independent from the uti- lization rate), See Appendix L and Table L.1. The fill rate of the model should be equal to the network service rate at NedTrain, because they measure the same. The network service rate of the 99 parts used in this simulation, in the year 2011 is equal to 0.9681. The differences between the fill rate of the simulation and the network service rate is quite large. As discussed in the subsection 3.3.3 the assumption of independent lead-times might be responsible for this large difference. But due to lack of the right data it was not possible to determine whether the lead-times are dependent from their priority. Therefore this large difference is taken for granted.

Verification and Validation. ‌ When dealing with complex autonomic systems one needs to face the problem of the development and of the validation of the models used for planning and for execution control. Indeed, while it is important for a large class of autonomic systems to integrate sensing and acting functionalities, controlled by deliberation mechanism (e.g. planning and execution control), the actual integration very often follows simple rules of thumb, which do not rely on any clear verification and validation approach. Nevertheless, the autonomy requirement of these systems keeps rising, and they need a more flexible approach to handle the used resources. These systems are deployed for increasingly complex tasks; and it becomes more and more important to prove that they are safe, dependable, and correct. This is particularly true for rovers used in expensive and distant missions, such as Mars rovers, that need to avoid equipment damage and minimize resource usage, but also for robots that have to interact regularly and in close contact with humans or other robots. Consequently, we think that it is becoming very common to require software integrators and developers to provide guarantees and formal proofs as certification. Formal verification is an attractive alternative to traditional methods of testing and simulation that can be used to provide correctness guarantees. By formal verification we mean not just the traditional notion of program verification, where the correctness of code is at question. We more broadly mean design verification, where an abstract model of a system is checked for desired behavioural properties. Finding a bug in a design is more cost-effective than finding the manifestation of the design flow in the code. The ASCENS approach relies on the integration of two state-of-the-art technologies for verification and validation, namely D-Finder [BBNS09, BGL+11] and SBIP [BBD+12]. They are both based on BIP, a formal framework for building heterogeneous and complex component-based systems [BBS06]. Notably, thanks to the formal operational semantics of the SCEL language outlined in the previous section, BIP models can be obtained from static SCEL descriptions (i.e. involving only bounded creation/deletion of components and processes) by exploring a set of transformations rules.

Verification and Validation. The Collateral Account Bank shall not be obliged to make any payment or otherwise to act on any Instruction notified to it under this Agreement if it is unable: (a) to verify any signature pursuant to any request or Instruction against the specimen signature provided for the relevant Authorised Representative hereunder; and (b) to validate the authenticity of the request by telephoning a Call-back Contact who has not executed the relevant request or Instruction as an Authorised Representative of the Issuer.

Verification and Validation. In COPE deliverable D4.4. it was proposed that the COPE technology should be evaluated from two distinguishable aspects of human factors evaluation i.

Verification and Validation. ‌ There is no general approach that can be applied for model verifications and in particular validation because what is appropriate depends fundamentally on the purpose of the model [9, 11]. The ePolicy model will be assessed against three broad types of tests: Utility: Does the model meet the requirements of the project? Face [10] or conceptual [8, 12] validity: Are the model design and results consistent with theory and are they plausible? • Verification [5]: Is the design appropriately translated into model code? A verification test against historical data, which is sometimes also suggested for ABM, is impractical, as the setting (Conto Energia) in which the simulated entities act has changed a lot in recent years. This results in changes of the conditions for the simulator as well as changes in the adoption settings for the photovoltaic consideration. To give one example, in the previous energy account, households could install photovoltaic on the ground (i.e. on far larger areas then roofs). This is not possible under the current energy account any more, which is why in the simulator only roof sizes are included. This change however significantly changes the monetary considerations associated with photovoltaic and thus is likely impact the simulation results. That is why for the ePolich social simulator only the current (fifth) energy account was considered. For this energy account no sufficient number of past data is available to test the simulator on.

Verification and Validation. Verify the authenticity of rabies vaccination certificates submitted by pet owners as a prerequisite to dog license issuance.

Verification and Validation. Such changes shall be verified, or where appropriate validated according to ISO 13485 7.5 (Validation of Processes for Production and Service Provision), before implementation and these activities shall be documented. Such changes shall be approved by appropriate personnel and in accordance with the document change procedures set forth in ISO 13485 7.3 (Control of Design and Development Changes).

Verification and Validation. Verifying or validating the corrective and preventive action to ensure that such action is effective and does not adversely affect the finished device;

Verification and Validation