This foundational chapter establishes the theoretical and practical groundwork for
understanding data structures and algorithms, two fundamental pillars of computer science
that form the backbone of efficient computational problem-solving. The chapter begins with a
comprehensive exploration of algorithmic principles, examining their essential attributes of
correctness, finiteness, and efficiency while introducing classical design paradigms including
divide and conquer, greedy approaches, and dynamic programming. We then transition to the
systematic study of data structures, focusing particularly on static linear structures with
emphasis on arrays and their various manifestations. The treatment includes detailed analysis
of searching and sorting algorithms, culminating in an examination of hashing techniques that
bridge the gap between simple linear structures and more sophisticated access methods.
Through rigorous mathematical analysis and practical examples, this chapter provides readers
with both theoretical understanding and practical skills necessary for advanced study in
computational algorithms and data organization.