Scripting-and-Programming-Foundations Exam Dumps - WGU NDE Questions and Answers

A. X + 2 / 10:

• First, calculate 2 / 10, which is 0.2.
• Then add x (17.0) to 0.2, resulting in 17.2. This does not equal 3.7.

B. (2 + x) / 10.0:

• First, add 2 and x (17.0), which gives 19.0.
• Then divide 19.0 by 10.0, resulting in 3.7.

C. X + 2.0 / 10:

• First, calculate 2.0 / 10, which is 0.2.
• Then add x (17.0) to 0.2, resulting in 17.2. This does not equal 3.7.

D. 2 + x / 10:

• First, divide x (17.0) by 10, which gives 1.7.
• Then add 2 to 1.7, resulting in 3.7.

Therefore, option B is the correct expression.

References:

• Mathway - Math Calculator
• Quizlet - Scripting and Programming Actual FINAL PREP- Foundations

Object-oriented programming (OOP) is characterized by the concept of encapsulating data and operations within objects. This characteristic is fundamental to OOP and distinguishes it from procedural programming, which is structured around functions rather than objects. In OOP, objects are instances of classes, which define the data (attributes) and the operations (methods) that can be performed on that data. This encapsulation of data and methods within objects allows for more modular, reusable, and maintainable code.

References: The characteristics of object-oriented programming languages are well-documented and include encapsulation, abstraction, inheritance, and polymorphism. These principles are foundational to OOP and are supported by languages like C++, Java, and Python12345.

Space complexity refers to the amount of memory space required by an algorithm in relation to the size of the input data. It is a function, often denoted as S(N), that represents the number of fixed-size memory units used by the algorithm for an input of size N. For example, if an algorithm needs to create a new array that is the same size as the input array, its space complexity would be linear, or O(N), where N is the size of the input array. This term is crucial in evaluating the efficiency of an algorithm, especially when working with large data sets or in systems with limited memory resources.

References: The definition and explanation of space complexity can be found in various educational resources and literature on data structures and algorithms, such as computer science textbooks and online educational platforms12.

 In the Waterfall model of software development, the phase where all functions that need to be written to support the inventory system would be outlined is the Design phase. This phase is critical as it translates the requirements gathered during the analysis phase into a blueprint for constructing the system. It involves two subphases: logical design and physical design. The logical design subphase is where possible solutions are brainstormed and theorized, while the physical design subphase is when those theoretical ideas and schemas are turned into concrete specifications12.

References:

• The explanation is based on the standard Waterfall model phases, which include Requirements, Design, Implementation, Verification, and Maintenance. More detailed information on these phases can be found in resources like “Waterfall Methodology: The Ultimate Guide to the Waterfall Model” by ProjectManager1 and other educational platforms2.