Fix weak tracing and pseudocode writing for exam algorithms, with extra focus on searches and sorts
5 sections · 12 lessons
Trace state tables accurately and build exam-ready pseudocode with variables, assignment, selection, iteration, arrays, and procedures.
2 lessonsTrace and write linear search, binary search, bubble sort, insertion sort, and merge sort, with attention to not-found cases, swaps, shifts, and recursive splitting.
5 lessonsCompare search and sort choices under constraints, then diagnose broken pseudocode by tracing to the first error and correcting it.
2 lessonsConvert unseen descriptions into pseudocode, validate with matching traces, and justify performance from trace counts before linking evidence to Big-O.
2 lessonsRun a weekly revision loop with a checklist to target tracing and pseudocode mistakes before the exam.
1 lessonEvery lesson in order.
12 lessons
Algorithm tracing starts with state tables, where every variable update and array change must be tracked exactly. This course builds the exam skill of turning plain-English algorithm descriptions into correct pseudocode, then checking that code by tracing it back through the same kinds of tables. It is aimed at A-Level Computer Science students who already know the ideas in theory but need cleaner exam execution, especially for search and sort questions.
State tables, pseudocode building blocks, linear and binary search, bubble, insertion, and merge sort are covered through tracing and writing. It also covers choosing algorithms under constraints, debugging pseudocode by tracing, timed mixed practice from descriptions to code, and performance reasoning from trace evidence.
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