Derivation of European satellite equipment test specifications from vibro-acoustic test data

1989 ◽  
Vol 19 (10) ◽  
pp. 797-803 ◽  
Author(s):  
A. Girard ◽  
J.F. Imbert ◽  
D. Moreau
1989 ◽  
Vol 17 (1) ◽  
pp. 15-51 ◽  
Author(s):  
M. G. Pottinger ◽  
A. M. Fairlie

Abstract Tire force and moment data are fundamental inputs to vehicle handling simulations. Tire asymetries and tire and test variability must be considered in force and moment testing. This article provides a discussion of asymmetries in tire force and moment behavior and of variation in their data. The asymmetry discussion is thoroughly general. The variability discussion is philosophically general, but the data are specific to the test specifications and tests used. Variability data are presented for the range from −14 to +14 degrees slip angle. The data and concepts concerning tire asymmetries and test data variability presented are especially important now because work to produce up-to-date force and moment testing standards is beginning under the auspices of the Society of Automotive Engineers (SAE).


2020 ◽  
Vol 34 (2) ◽  
Author(s):  
Jonathan Thaler ◽  
Peer-Olaf Siebers

Abstract The importance of Agent-Based Simulation (ABS) as scientific method to generate data for scientific models in general and for informed policy decisions in particular has been widely recognised. However, the important technique of code testing of implementations like unit testing has not generated much research interested so far. As a possible solution, in previous work we have explored the conceptual use of property-based testing. In this code testing method, model specifications and invariants are expressed directly in code and tested through automated and randomised test data generation. This paper expands on our previous work and explores how to use property-based testing on a technical level to encode and test specifications of ABS. As use case the simple agent-based SIR model is used, where it is shown how to test agent behaviour, transition probabilities and model invariants. The outcome are specifications expressed directly in code, which relate whole classes of random input to expected classes of output. During test execution, random test data is generated automatically, potentially covering the equivalent of thousands of unit tests, run within seconds on modern hardware. This makes property-based testing in the context of ABS strictly more powerful than unit testing, as it is a much more natural fit due to its stochastic nature.


2016 ◽  
Vol 32 (3) ◽  
pp. 204-214 ◽  
Author(s):  
Emilie Lacot ◽  
Mohammad H. Afzali ◽  
Stéphane Vautier

Abstract. Test validation based on usual statistical analyses is paradoxical, as, from a falsificationist perspective, they do not test that test data are ordinal measurements, and, from the ethical perspective, they do not justify the use of test scores. This paper (i) proposes some basic definitions, where measurement is a special case of scientific explanation; starting from the examples of memory accuracy and suicidality as scored by two widely used clinical tests/questionnaires. Moreover, it shows (ii) how to elicit the logic of the observable test events underlying the test scores, and (iii) how the measurability of the target theoretical quantities – memory accuracy and suicidality – can and should be tested at the respondent scale as opposed to the scale of aggregates of respondents. (iv) Criterion-related validity is revisited to stress that invoking the explanative power of test data should draw attention on counterexamples instead of statistical summarization. (v) Finally, it is argued that the justification of the use of test scores in specific settings should be part of the test validation task, because, as tests specialists, psychologists are responsible for proposing their tests for social uses.


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