Time-space tradeoff
A time-space tradeoff is a design choice that exchanges computational time for storage or memory, or storage or memory for computational time.
Hacking Cryptography
A design trade-off in which additional storage or memory reduces computation time, or reduced storage increases computation time.
- How it is used
- Optimizes dictionary attacks against hashed passwords by trading stored guesses for repeated computation.
- How deep it goes
- Explains chain construction, collision reduction, endpoint lookup, and verification through executable Go implementations.
- Examples
- Uses PIN dictionaries, SHA-256 chains, Go code, stored table endpoints, and a 100-user cracking test.
- What you can do after
- Evaluate/understand how attackers compress password-guessing tables and recover candidates through recomputation.
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Fast Python: High performance techniques for large datasets
- How it is used
- Optimizes critical Cython code by exchanging additional array storage for fewer boundary checks.
- How deep it goes
- Explains allocation, boundary copying, and indexing costs, but gives no generalized decision rule beyond workload and resource dependence.
- Examples
- Uses a cellular-automaton board, an extended wraparound array, and a Cython live-core loop.
- What you can do after
- Apply it via Cython by allocating copied boundary storage and simplifying the main computation loop.
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