Random Number Generation In A Programming
Bayani Gaba-gaba
A computer is the most predictable machine ever built. Give it the same input twice and it gives you the same answer twice, which is exactly what you want from a payroll system and exactly what you do not want from a game of snakes and ladders. Somewhere in that game a die has to be thrown, and the machine has to produce a number it did not know it was going to produce.
This lesson covers the one objective the specification sets here: be able to use random number generation. It also covers the boundary the specification draws, because knowing what is not asked for saves revision time. You will learn how to generate a number in a given range and count how many values that range holds, how to make a choice with equal chance, how to keep generating until you get a value you can use, and why a program that behaves differently every time is harder to test than one that does not.
Manufura
- Be able to use random number generation.
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- How many different values can RANDOM(3, 9) produce, if both bounds are included? A. 6 B. 7 C. 9 D. 12 Answer: B
- An array holds 20 elements. Which call generates a valid index? A. RANDOM(0, 19) B. RANDOM(0, 20) C. RANDOM(1, 20) D. RANDOM(1, 21) Answer: A
- Which structure is used to keep generating a random number until an acceptable value appears? A. A definite loop B. A nested selection C. An indefinite loop D. A subroutine call Answer: C
- A program chooses one of two players at random and must give each an equal chance. Which call is correct? A. RANDOM(0, 1) B. RANDOM(0, 2) C. RANDOM(1, 10) D. RANDOM(2, 2) Answer: A
- According to the specification, which of these is NOT required? A. Using random number generation within a program B. Choosing an appropriate range for a task C. Understanding how pseudo-random numbers are generated D. Storing a randomly generated value in a variable Answer: C
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