Algorithmic Problem Solving

Problem solving that begins with the question, not the shortcut

Algorithmic Problem Solving takes a refreshingly disciplined approach to computer science: instead of treating algorithms as abstract recipes, it shows how to think your way toward them. Roland Backhouse structures the book around examples and carefully developed reasoning, so readers see not only what works, but why it works.

The emphasis is firmly on mathematical method in service of programming and algorithm design. That makes the book especially useful for readers who want to strengthen the habits behind good technical problem solving: modeling a problem clearly, choosing the right abstraction, and turning ideas into precise steps that can be executed reliably.

What the book covers

• core ideas in algorithmic problem solving
• logic, propositions, and calculational reasoning
• induction and proof-oriented thinking
• sets, functions, and relations
• graphs, paths, and combinatorial structures
• exercises and solutions that support active study

A teaching text with a strong mathematical spine

The book was developed from a first-year module at the University of Nottingham, and that classroom origin shows in its pacing. It is designed to be worked through, not merely skimmed. Examples lead the reader forward, while the second part of the book develops the mathematics that underpins the method.

That balance makes the text especially appealing for computer science and software engineering students, as well as instructors looking for a structured way to introduce rigorous problem-solving habits. It also rewards self-directed readers who enjoy careful reasoning and technical clarity.

Why it stands out

Rather than presenting algorithm design as a bag of tricks, Algorithmic Problem Solving treats it as a way of thinking. The result is a book that is methodical, demanding, and genuinely instructive — a strong fit for readers who want depth, not just examples.