💻 Help in study · Computer science

Computer science help — algorithms, networks, data structures

Computer Science is the only subject where the exam tests you on code by making you write it on paper, by hand, without syntax highlighting. Practice writing code on paper — it's a separate skill from typing it in an IDE.

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A real computer science question students bring us

Trace bubble sort on [5, 1, 4, 2, 8] step by step, then state its time complexity in Big-O.

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Why computer science is harder than it looks

Computer Science exams test conceptual understanding without the tools you'd use in real coding (IDE, autocomplete, runtime feedback). Writing correct C / Python / Java by hand is an exam skill that needs explicit practice.

Trace tables save you marks

Any algorithm question that asks 'trace this' wants a trace table — a table with one column per variable and one row per loop iteration. Build it neatly and you've already shown the algorithm works. Most students do this badly under time pressure.

Big-O without panic

Big-O reduces to: count the dominant nested loop. One loop = O(n). Loop inside loop = O(n²). Binary search style = O(log n). Master those four, then ratio-test (n!, 2ⁿ, n log n) and you've covered most exam questions.

SQL by hand

Write SELECT, JOIN, GROUP BY, HAVING, ORDER BY queries on paper without an IDE. Use Whiskey-Tango-Foxtrot indentation if needed. Markers want to see the structure even if syntax is slightly off.

Networks — memorise the models

OSI model layers (Physical, Data Link, Network, Transport, Session, Presentation, Application) and TCP/IP model layers (Link, Internet, Transport, Application) appear in every exam. Memorise both, including one example protocol per layer.

What we do specifically well for computer science

Code-on-paper drills with feedback
Trace tables for any algorithm
Big-O analysis walkthrough
SQL query generation + critique
Network diagram practice (OSI + TCP/IP layered)
Boolean expression simplification

Topics covered

Algorithms (sorting, searching)Big-O notationData structures (arrays, stacks, queues, trees, hashes)Databases + SQLNetworks + OSI modelOperating systemsProgramming paradigms (procedural, OOP, functional)Computer ethics + GDPRBoolean logic + truth tablesNumber systems + conversions

Tools that pair well with computer science

Math solver →

Boolean simplification + truth tables

Whiteboard →

Sketch network diagrams, ER diagrams

Quiz generator →

MCQs on networks / algorithms / databases

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