Brian Lambert PhD Cis 2110 Structured Problem Solving

W Brian Lambert Phd Cis 2110 Structured Problem Solving

W Brian Lambert, PhD CIS 2110 – Structured Problem Solving

Problem Statement:

Bob runs a food truck business with four trucks. Every day, each truck leaves the warehouse and travels to different parts of town, selling food at multiple construction sites. He collects metrics daily including the number of sites visited, gas cost, and revenue. Each morning, Bob wants to generate a report of the previous day's metrics. He inputs these metrics into a program: the date (entered once), followed by each truck's data (Truck ID, number of sites visited, gas expense, and revenue). After each data entry, the program displays the value entered for verification and computes the profit for that truck (revenue minus gas expense). When all trucks have been entered, Bob inputs "End" as the Truck ID to terminate data entry. The program then displays a summary including total trucks, total gas expense, total revenue, total profit, average profit per truck, highest profit, and the Truck ID of the truck with the highest profit. If multiple trucks share the highest profit, only the first entered truck's details are reported.

Paper For Above instruction

IO Design

Input Design

• Report date (string)
• Truck ID (string), with sentinel value "End" to terminate input
• Number of sites visited (integer)
• Gas expense for the day (float)
• Revenue for the day (float)

Output Design

• Display entered data immediately after each input for verification
• Display profit for each truck after data entry
• Upon receiving "End", display a summary with total trucks, total gas expense, total revenue, total profit, average profit, highest profit, and truck ID with highest profit

Full Paper

Introduction

Effective management of business operations requires detailed data collection, analysis, and reporting. In the context of Bob's food truck business, developing a computer program to facilitate data entry and generate comprehensive reports ensures accuracy, efficiency, and informed decision-making. This paper outlines the systematic approach to designing such a program, focusing on input/output specifications, walk-throughs, and logic flow.

Problem Analysis

The core task involves capturing daily metrics for multiple trucks and summarizing these metrics with calculated values. The process includes sequential data input with immediate feedback, conditional termination, and aggregate calculations. Recognizing these tasks informs the structuring of the program’s flow, variables, and output formats.

Input/Output Design

The program begins by prompting for the report date, a single input. Subsequently, each truck's data is entered in a specified sequence: Truck ID, number of sites, gas expense, and revenue. After each input, the program displays the entered value to facilitate verification. This immediate confirmation reduces data entry errors. For each truck, after completing all entries, the profit—computed as revenue minus gas expense—is displayed.

Once all truck entries are made, the user inputs "End" as the Truck ID, signaling the program to conclude data collection. The program then aggregates the data, calculating totals and averages, identifies the highest profit and corresponding truck, and displays the summarized report.

Walk-through Development

A human-level walk-through involves step-by-step event tracking, focusing on user actions and immediate outputs. The key events include entering the report date, each truck's data, verifying inputs, displaying individual profits, and finally receiving the sentinel value "End".

The program-level walk-through extends this by detailing variable management—initializing totals, tracking the highest profit, and updating these with each input. It guides the logic flow from input validation, data processing, updating aggregates, conditionally updating high-profit data, and ultimately producing the output report.

Logic and Implementation Details

The processes underpinning the program involve looping constructs to manage multiple truck entries, conditional statements to check for the sentinel, and arithmetic calculations for profit, totals, and averages. Adequate error checking and user prompts ensure robustness and user-friendliness.

The program must efficiently update accumulative variables; for example, incrementing total truck count and summing gas expenses, revenues, and profits. It’s essential to track the first occurrence of the highest profit, ignoring subsequent trucks with the same profit, by updating only if the current profit exceeds the previous maximum.

Conclusion

Designing an efficient program for Bob’s daily report involves defining clear input/output parameters, developing a logical flowchart or pseudocode based on problem requirements, and creating thorough walk-throughs. Such structured planning ensures smooth implementation and accurate reporting, aiding Bob’s daily operations management.

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