Elements of Programming 1st Edition by Alexander Stepanov, Paul Mcjones ISBN 032163537X 9780321635372

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Product details:
ISBN 10: 032163537X
ISBN 13: 9780321635372
Author: Alexander Stepanov, Paul Mcjones
“Ask a mechanical, structural, or electrical engineer how far they would get without a heavy reliance on a firm mathematical foundation, and they will tell you, ‘not far.’ Yet so-called software engineers often practice their art with little or no idea of the mathematical underpinnings of what they are doing. And then we wonder why software is notorious for being delivered late and full of bugs, while other engineers routinely deliver finished bridges, automobiles, electrical appliances, etc., on time and with only minor defects. This book sets out to redress this imbalance. Members of my advanced development team at Adobe who took the course based on the same material all benefited greatly from the time invested. It may appear as a highly technical text intended only for computer scientists, but it should be required reading for all practicing software engineers.”

Elements of Programming 1st Edition Table of contents:

• Introduction

  • Overview of Programming and its Elements
  • Purpose and Scope of the Book
  • The Philosophy of Programming: Efficiency and Elegance
  • The Relationship Between Data Structures and Algorithms
  • Key Concepts and Terminology

• The Foundation of Programming

  • Understanding the Role of Abstractions in Programming
  • Basic Concepts of Algorithms and Data Structures
  • Mathematical Foundations for Programming
  • Introduction to Complexity Theory
  • The Importance of Design and Specification

• Generic Programming: A New Paradigm

  • Introduction to Generic Programming
  • The Core Principles of Generic Programming
  • Generic Algorithms and Data Structures
  • Templates and Type Parameters in C++
  • Benefits of Generic Programming for Software Development

• Data Structures and Their Role in Programming

  • Fundamental Data Structures: Arrays, Lists, Stacks, Queues
  • Advanced Data Structures: Trees, Graphs, Heaps
  • Designing Efficient Data Structures
  • The Relationship Between Data Structures and Algorithms
  • Practical Considerations for Choosing Data Structures

• Algorithms and Their Design Principles

  • General Approach to Algorithm Design
  • Searching and Sorting Algorithms
  • Recursive Algorithms and Their Applications
  • Dynamic Programming and Divide-and-Conquer Strategies
  • Greedy Algorithms and Backtracking

• Efficiency and Complexity Analysis

  • Time and Space Complexity: Big-O Notation
  • Analyzing and Comparing Algorithm Efficiency
  • Trade-Offs Between Time and Space
  • Optimizing Algorithms for Real-World Use Cases
  • Practical Considerations for Algorithm Design

• Functional Programming and Its Integration with Generic Programming

  • Key Principles of Functional Programming
  • The Role of Higher-Order Functions
  • Combining Generic and Functional Programming Techniques
  • Immutable Data Structures in Functional Programming
  • Case Studies of Functional Programming in Practice

• Abstract Data Types and Encapsulation

  • Defining and Using Abstract Data Types (ADTs)
  • Encapsulation and Information Hiding
  • Abstracting Operations on Data
  • The Role of ADTs in Designing Modular Programs
  • Examples of ADTs in Real-World Programming

• Object-Oriented Programming and Generic Programming

  • The Basics of Object-Oriented Programming (OOP)
  • Integrating Object-Oriented Principles with Generic Programming
  • Inheritance, Polymorphism, and Abstraction
  • Design Patterns in Object-Oriented and Generic Programming
  • Case Studies and Examples of OOP in Practice

• Concurrency and Parallelism in Programming

  • Introduction to Concurrency and Parallel Programming
  • Managing Shared Resources and Synchronization
  • Parallel Algorithms and Their Implementation
  • Practical Considerations for Writing Concurrent Code
  • Tools and Techniques for Debugging Concurrent Programs

• Error Handling and Exception Management

  • Strategies for Error Detection and Handling
  • The Role of Exceptions in Modern Programming Languages
  • Designing Robust Systems with Proper Error Management
  • Techniques for Managing Runtime and Logic Errors
  • Best Practices for Exception Handling

• Programming for Performance and Scalability

  • Understanding Performance Bottlenecks
  • Techniques for Profiling and Optimizing Code
  • Scalability Considerations for Large Systems
  • Parallel and Distributed Systems for Performance Improvement
  • Designing Systems for Future Growth and Flexibility

• Testing and Verification

  • The Importance of Testing in Software Development
  • Unit Testing, Integration Testing, and System Testing
  • Tools and Frameworks for Automated Testing
  • Formal Verification Methods for Ensuring Correctness
  • Debugging Techniques and Best Practices

• Software Engineering Principles

  • Introduction to Software Engineering Methodologies
  • The Role of Design Patterns and Architecture
  • Managing Complexity in Large Software Projects
  • Documentation and Specification in Software Design
  • Version Control and Collaborative Development Practices

• The Future of Programming

  • Emerging Trends in Programming Languages and Paradigms
  • The Evolution of Tools for Software Development
  • Challenges and Opportunities in the Software Industry
  • The Growing Importance of Algorithmic Thinking
  • The Role of Programmers in Shaping Future Technologies

• Conclusion

  • Key Takeaways from the Book
  • The Journey from Theory to Practice in Programming

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