Ch 4 teaches systematic problem solving — analysing problems, designing algorithms, representing solutions through flowcharts and pseudocode, and verifying correctness before writing code.
Steps: (1) Understand the problem — identify input, output, constraints. (2) Analyse — break into smaller sub-problems (decomposition). (3) Design algorithm — step-by-step solution. (4) Test — trace through examples (dry run). (5) Code — implement in programming language. Algorithm properties: finite (must terminate), definite (each step clear), input (zero or more), output (at least one), effective (each step doable). Good algorithms are correct, efficient, and readable.
Flowchart symbols: oval (start/stop), parallelogram (input/output), rectangle (process), diamond (decision — Yes/No), arrows (flow direction). Draw for: finding maximum, checking prime, factorial. Pseudocode: structured English close to code — no strict syntax rules. Example: READ n, SET sum = 0, FOR i = 1 TO n: sum = sum + i, PRINT sum. Debugging: syntax errors (wrong code structure), logical errors (wrong algorithm), runtime errors (divide by zero, overflow). Trace through with a table: track variable values at each step.
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An algorithm is a step-by-step procedure to solve a problem — language-independent, abstract, focuses on logic. A program is the implementation of an algorithm in a specific programming language — syntax-dependent, executable, includes language-specific details. Think: algorithm is the recipe (logic), program is the actual cooking (implementation). You should design the algorithm first, verify it works (dry run), then translate to code. Multiple programs in different languages can implement the same algorithm.
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