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Verification and validation skills test - Aerospace
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Test duration:
20
min
Notes
No. of questions:
10
Tie
Level of experience:

Verification and validation Test - Aerospace

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About

Verification and validation skills test - Aerospace

Verification and validation are independent procedures used to check that a product, service, or system meets requirements and specifications and fulfills its intended purpose. The verification process includes checking the design, code, and program, whereas the Validation process includes testing and validation of the actual product. In aerospace, on-site laboratories are equipped with test rigs, ranging from tensile/compressive loading equipment to dynamic impact resistance. To complement this, they have a wide range of defect monitoring and assessment equipment to enable the rapid development of product designs.   



Verification and validation online tests have a unique set of questions. You can also create or ask us to create a customized test that includes questions specific to your job requirements. 

  

The verification and Validation skills test (Aerospace) helps to screen the candidates who possess traits as follows:  

  • Good knowledge of Aerospace V & V tools while inspecting equipment 
  • Good experience in Aerospace testing systems and testing concepts  
  • Familiarity with some standards like DO 178B, DO 332 standards, etc 

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Test Summary

Test Duration
20
No. of Questions
10
Level of Expertise
Useful for hiring
  • Senior Engineer – Verification & Validation
  • Technical Assistance – Defence & Aerospace
  • Test Automation Engineer
Topics Covered
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Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.

Question types :

Multiple Option

Topic:

Difficulty:

Hard


Q 1. You have been asked to train « Naive Bayes model for spam detection dataset

Using Python command, what wil you add in the given code at XXXX to deciore, it and train your modal for the given dataset?

import numpy os np

X= nporroyll 3. 2b[1 21 [2.21.[3,21)
Y= nporray(fi.a,a.1))

XXXX

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

Question types :

Multiple Option

Topic:

Machine teaming

Difficulty:

Hard


Q 1. Q2 Lets assume that you have 6 Pandas DataFrome(af) in the below tole.

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074

When the following commend is executed, what hoppens to the DatoFrome?

df= defiinat()
Y= nporray(fi.a,a.1))

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
it gives an error becouse of the third row which has on empty string.
None of these

Question types :

Multiple Option

Topic:

Aerospace - DO 178B

Difficulty:

Hard

Question:

The architectural model is derived from which of these sources?
A) Information about the application domain for the software to be built.
B) Specific requirements model elements such as data flow diagrams or analysis classes, their relationships, and collaborations for the problem at hand.
C) The availability of architectural styles and patterns.


Options

  • Both A and B
  • Both B and C
  • Both A and C
  • All of the options
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