IB Computer Science IA source code requirements

IB Computer Science IA Source Checker

Computer Science IA products must be student-developed. Libraries and references can be cited, but unmodified templates, copied exemplar databases, or significant copied code are high-risk unless substantially transformed and acknowledged.

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AI source auditor

Computer Science IA source check

Marksy reads the links or source notes you provide, applies the selected IB assessment profile, and only stops for clarification when the score depends on it.

Profile
2Sources
3Clarify
4Score

Selected profile

Computer Science IA

Source rules

What usually works for Computer Science IA

Usually strong

  • Official library documentation, API docs, algorithm references, and cited code snippets used narrowly.
  • Client/user evidence, testing data, and design documentation produced by the student.
  • Open-source libraries when licensing and use are acknowledged.

Needs review

  • Starter templates that define most of the product structure.
  • AI-generated code blocks pasted without understanding or attribution.
  • Tutorial apps that match the final product too closely.

Avoid or replace

  • Unmodified exemplar databases or web templates.
  • Copied code that forms the core functionality.
  • Assets or code with unclear license/provenance.

Examples: strong, risky, weak

Strong

Official API documentation plus student-authored code, user interview notes, and testing evidence.

Review

A Stack Overflow snippet used for one utility function with attribution and modification.

Weak

A downloaded app template with only colors and labels changed.

Where to find better Computer Science IA sources

If your current source gets a warning, do not just add more websites. Use searches that match the assessment rule and replace weak evidence with sources that can actually carry analysis.

Replacement moves

Replace unmodified exemplar databases or web templates. with official library documentation, api docs, algorithm references, and cited code snippets used narrowly..

Use starter templates that define most of the product structure. only as context unless your teacher confirms they can carry evidence.

Add one source that gives direct evidence for the IA, not just general background.

Strong places to look

Official library documentation, API docs, algorithm references, and cited code snippets used narrowly
Client/user evidence, testing data, and design documentation produced by the student
Open-source libraries when licensing and use are acknowledged