Examples
A strong computer science topic identifies a system or method, a comparison or constraint, and an evaluation metric. Scope the work to an implementation and dataset you can realistically obtain and reproduce.
- 01Comparing retrieval strategies for question answering over university policy documents
- 02Energy and accuracy trade-offs in small language models on mobile devices
- 03Detecting dependency confusion risks in open-source JavaScript projects
- 04The effect of code-review response time on defect resolution
- 05Accessible error-message design for users of mobile banking apps
- 06Benchmarking graph and relational databases for transit-network queries
- 07Privacy-preserving analytics for small healthcare datasets
- 08How novice programmers use AI-generated explanations when debugging
Check this topic
- State the baseline, dataset, and evaluation metric.
- Choose a contribution that can be reproduced within your compute budget.
- Separate system performance from user-experience claims.
Search recent literature, confirm the gap, and ask your supervisor to review the scope.