My Journey Learning Data Structures and Algorithms

This article describes the author's seven‑year learning journey in data structures and algorithms, beginning with a neglected university course and a personal five‑year study plan that included C language fundamentals, data structures, and computer networks.

The author first consulted senior students who recommended classic texts such as Introduction to Algorithms and The Art of Computer Programming , but found them intimidating and turned to Douban reviews to select more approachable books.

The first influential book was Data Structures and Algorithm Analysis – C Language Description , which the author studied intensively, copying code by hand and drawing algorithmic state diagrams. The book illustrated the importance of algorithms by improving the complexity of the maximum sub‑sequence problem from O(N³) to O(N).

During a later internship the author realized that real‑world work often involved stitching together existing APIs rather than applying algorithms, prompting a shift toward deeper algorithmic study.

In graduate school the author attended Professor Han Jun's Algorithm Design and Analysis course, which mirrored the structure of the textbook and introduced concepts such as divide‑and‑conquer, dynamic programming, and backtracking.

Additional reading included Algorithm Introduction , which focuses on creating algorithms, and two implementation‑focused books: Elements of Programming and C Interfaces and Implementation . These helped the author improve practical C coding skills, exemplified by the need to implement a stof function for a Baidu interview.

Project work included a T‑SQL parser built with an LL(k) grammar and an AST walker to generate block‑coverage HTML reports, a high‑performance pinyin index for a mobile app using Int16 and Int64 indexing, and a fast string‑matching dialer that replaced linear search with a trie, achieving a 90‑fold speedup.

The author also experimented with simulated‑annealing‑based pagination for an e‑book reader and studied code‑correctness proofs from The Science of Programming , gaining the ability to formally verify simple code snippets.

Later studies covered classic interview books such as Algorithm Design Manual , the Programming Pearls series, and advanced data‑structure courses (MIT 6.851) that introduced persistent structures, van Emde Boas trees, O(1) LCA/RMQ solutions, and linear‑time suffix‑tree construction.

In the concluding reflection, the author observes a dialectical progression: early belief in the power of algorithms, a mid‑career phase of algorithm skepticism, and a final reaffirmation that solid algorithm knowledge is essential for becoming an excellent developer rather than merely a code monkey.