Unique Presentation Identifier:

26

Program Type

Honors

Faculty Advisor

Dr. Robin Ghosh

Document Type

Poster

Location

Face-to-face

Start Date

9-4-2026 1:00 PM

End Date

9-4-2026 3:00 PM

Abstract

This project examined how consistent practice with data structures and algorithms (DSA) can improve problem solving skills and preparation for software engineering technical interviews. The goal was to strengthen foundational algorithmic knowledge while developing a structured practice routine that could continue beyond the semester. From week 3 through week 12, four LeetCode style problems were completed each week, focusing on core interview topics including string manipulation, arrays, linked lists, hash tables, sets, and dynamic programming. Each problem required implementing a solution, identifying edge cases, and evaluating time and space complexity to determine the most efficient approach. Through this process, common algorithmic patterns and problem solving strategies were analyzed across multiple data structure categories. Practice with strings and arrays improved indexing and optimization techniques, while linked list problems strengthened understanding of pointer manipulation. Hash tables and sets reinforced efficient lookup strategies, and dynamic programming introduced recursive and subproblem based thinking. Overall, the project demonstrated that structured, repeated exposure to algorithmic challenges improves both conceptual understanding and coding efficiency, while establishing a long term framework for continued technical interview preparation.

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Apr 9th, 1:00 PM Apr 9th, 3:00 PM

Data Structures & Algorithms Prep Hub: A Technical Interview Preparation Tracker

Face-to-face

This project examined how consistent practice with data structures and algorithms (DSA) can improve problem solving skills and preparation for software engineering technical interviews. The goal was to strengthen foundational algorithmic knowledge while developing a structured practice routine that could continue beyond the semester. From week 3 through week 12, four LeetCode style problems were completed each week, focusing on core interview topics including string manipulation, arrays, linked lists, hash tables, sets, and dynamic programming. Each problem required implementing a solution, identifying edge cases, and evaluating time and space complexity to determine the most efficient approach. Through this process, common algorithmic patterns and problem solving strategies were analyzed across multiple data structure categories. Practice with strings and arrays improved indexing and optimization techniques, while linked list problems strengthened understanding of pointer manipulation. Hash tables and sets reinforced efficient lookup strategies, and dynamic programming introduced recursive and subproblem based thinking. Overall, the project demonstrated that structured, repeated exposure to algorithmic challenges improves both conceptual understanding and coding efficiency, while establishing a long term framework for continued technical interview preparation.