A General Approach to Problem Solving in Computer Science

Description

This lecture presents a repeatable problem solving cycle for computer science grounded in operations research. It covers framing, data understanding, modeling, decomposition, core algorithmic paradigms, heuristics, validation, complexity, experimentation, communication, adaptation, and visual retention strategies, with a mini scheduling case. Emphasis is placed on visual thinking, measurable goals, and iterative improvement.