Which of the following is NOT a source of bias in an algorithm? Mental models of programmers Explainability Measurement error Misrepresentation in a dataset

Is it at all feasible to offer an overview of the compiler as well as an explanation of the significance of testability?

1. Define the following and give one example for each: a. Compile-time error b. Run-time error c. Logical error d. Linker error

Using existing algorithms as building blocks for new algorithms has all the following benefits EXCEPT:    A.   reduces development time    B.   reduces testing    C.   simplifies debugging    D.   removes procedural abstraction

(A) The first task is to create a scanner for python language. The scanner should have the following features. • Skip over white spaces. • Recognize all keywords and return the correct token. The scanner implemented for c in the slides can be used as a reference. (B) The second task is to implement a parser of your choice. You can choose any top down or bottom up parser.

Has a set of criteria been established for Algorithm Analysis?

Select the correct answer for the question below: Dynamic programming is an algorithm pattern ... 1.Is not applicable to algorithms which use recursion.   2.That is applicable to almost every set of circumstances and can be widely implemented.   3.That is applicable to only a narrow range of circumstances.   4.Offers poor efficiency gains, when applicable.

Consider the role that debugging may play in the development of more trustworthy programs.

In this chapter, computer-generated random numbers were used to simulate statistical distributions. Which of the following statements makes you believe a machine can create a really random number that passes all randomness tests? Should we study random number generators and their methods?

Can someone please answer the following?