Q1. Explain caching strategies and common failure modes.
Strategies: - Cache-aside (lazy loading): app checks cache, on miss reads DB and populates. Most common. - Read-through: cache library fetches on miss. - Write-through: w...
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Q2. Compare write-through, write-behind and write-around caching.
- Write-through: write to the cache and the database in the same operation, synchronously. The cache stays fresh and reads are fast, but writes are slower and every write...
Q3. How do you invalidate cached data?
Invalidation is the hardest part of caching. Options, often combined: - TTL expiry: every entry has a lifetime; simple and self-healing, but data can be stale until it ex...
Q4. What is cross-validation and why use it?
Cross-validation repeatedly splits data into training and validation folds to estimate how well a model generalizes. In k-fold, the data is split into k parts; the model ...
Q5. How do you trace requirements through to delivery and validate they were met?
Traceability means being able to follow a requirement from its origin through design, build and testing to delivery, in both directions. Forward traceability shows that e...
Q6. How do you keep a cache consistent with the database?
Perfect consistency is not achievable without giving up caching; aim for bounded staleness and correct behavior. Practical rules: - On write, commit to the database first...
Q7. How do the different Next.js caches and revalidation layers work?
Next.js has several cache layers. The Data Cache stores individual fetch results and can be tagged. The Full Route Cache stores rendered HTML and RSC payloads for static ...
Q8. What is data leakage in machine learning?
Data leakage is when information unavailable at prediction time seeps into training, producing optimistic validation scores that collapse in production. Common sources: -...