Task $1$: Implementation and Analysis of Search Algorithms with User Input

Objective:

Develop Python programs that implement recursive and non$-$recursive versions of linear and binary search algorithms, allow user input for the list and the item to search, and compare their performances across multiple dimensions.

Concepts Used:

Loops, conditionals, recursion, functions, user input handling, and algorithm efficiency.

Project Structure:

$1.$ User Input Handling:

$$ Implement functions to prompt users to enter a list of numbers and the item they want to search for. Ensure robust input handling to manage non$-$numeric inputs and other potential input errors.

$2.$ Algorithm:

$$ Linear Search:

$$ Non$-$Recursive Function: Implement a standard iterative version of linear search.

$$ Recursive Function: Develop a recursive version of linear search.

$$ Binary Search:

$$ Non$-$Recursive Function: Implement a standard iterative binary search.

$$ Recursive Function: Develop a recursive version of binary search.

$3.$ Implementation:

$$ Linear Search:

$$ Non$-$Recursive Function: Implement a standard iterative version of linear search.

$$ Recursive Function: Develop a recursive version of linear search.

$$ Binary Search:

$$ Non$-$Recursive Function: Implement a standard iterative binary search.

$$ Recursive Function: Develop a recursive version of binary search.

$4.$ Performance Measurement:

$$ Execution Time: Measure the time taken by each function to complete the search.

$$ Number of Instructions: Count the iterations or recursive calls.

$$ Memory Usage: Monitor the memory consumption using the memory profiler module.

$5.$ Analysis and Reporting:

$$ Compare the efficiency of recursive vs$.$ non$-$recursive methods in terms of time, instructions, and memory.

$$ Discuss the practical implications of these results, focusing on the trade$-$offs between different approaches.

$6.$ Report:

$$ Introduction: Discuss the project$$s goals and the importance of the algorithms.

$$ Methodology: Detailed description of user input handling and algorithm implementations.

$$ Results: Present detailed data on the performance of each search method.

$$ Discussion: Insights into the benefits and drawbacks of each method.

$$ Conclusion: Recommendations based on performance and usability.

$$ Appendices: Include all code, error handling routines, and raw performance data.

Deliverables:

$$ Code: Well$-$documented Python code implementing all parts of the project.

$$ Performance Analysis: Detailed metrics on execution time, instruction count, and memory usage.

$$ Project Report: A comprehensive $10-15$ page document articulating all project phases.

$$ Presentation: A PowerPoint or similar presentation that summarizes the project, methodology, key findings, and conclusions. This should be designed for a $10-15$ minute presentation to the class.

Presentation Guidelines:

$$ Slide $1$: Title Slide $-$ Project title, group members, date.

$$ Slide $2$: Introduction $-$ Objectives and importance of the project.

$$ Slide $3-4$: Methodology $-$ How the algorithms were implemented and tested.

$$ Slide $5-6$: Results $-$ Graphs and tables showing performance comparisons.

$$ Slide $7$: Discussion $-$ Analysis of the results and their implications.

$$ Slide $8$: Conclusion $-$ Summarize the findings and offer recommendations.

$$ Slide $9$: Future Work $-$ Suggestions for further exploration or improvements.

$$ Slide $10$: Q&A $-$ Open the floor for questions from the audience and instructors.

The inclusion of a presentation will help students develop their public speaking skills and ability to present technical content succinctly, while the comprehensive report and code deliverables ensure they have a deep engagement with programming concepts and analysis techniques.