Algorithms and Programs: An AI-Assisted Approach

Description

Bridge the gap between algorithm design and real-world code with a practical, AI-assisted approach built for today's developers.

Algorithms power modern systems--from flight control and robotics to recommendation engines and AI applications. Algorithms and Programs: An AI-Assisted Approach shows how to clearly define an algorithm's purpose, design a structured outline, translate it into reliable code, and reason about its efficiency and complexity.

Rather than relying on traditional pseudocode, this book uses precise algorithm outlines that are easier to understand and directly support correct implementation. This approach bridges the gap between design and code, reducing ambiguity and minimizing errors.

Each algorithm is expressed as a sequence of clear, intended outcomes, which naturally define its correctness conditions and support reasoning about invariants and program behavior. This structured method encourages better programming practice, improves reliability, and aligns well with modern AI-assisted development tools.

• Practical approach to algorithms: Moves beyond traditional pseudocode to clear, structured algorithm outlines that directly translate into reliable code.
• Bridges theory and real-world programming: Helps learners and engineers connect algorithm design with implementation, correctness, and performance in everyday software development.
• Makes invariants intuitive and usable: Developed from decades of teaching experience, the book rethinks invariants in a practical, common-sense way that students and practitioners can actually apply.
• Designed for modern AI-assisted development: Aligns with how programming is done today, enabling AI-checkable algorithm structures that support correctness and reduce errors.
• Rooted in teaching and real industry experience: Inspired by long-term discussions with students and professional practice, addressing real gaps between academic concepts and industry needs.
• Strategic AI Thinking: Explore leverage from AI platforms that specify function requirements, outline appropriate algorithms, implement outlines, and inspect them reliably.

Sample Content

Table of Contents

Chapter 1: Specifying Problems, Functions, and Classes

Chapter 2: Expressing Algorithms and their Complexity

Chapter 3: Algorithm Creation and Analysis

Chapter 4: Divide and Conquer

Chapter 5: Sorting

Chapter 6: Dynamic Programming

Chapter 7: Greedy Algorithms

Chapter 8: Minimum Spanning Trees

Chapter 9: Shortest Paths

Updates

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