Interview Question Bank: Setup, Slices, Daily Drills

27 juillet 2026Par Beyz Editorial Team

TL;DR

An interview question bank is your working memory for interviews: a tagged, searchable set of prompts, patterns, and post-mortems that you reuse intentionally. Build a lean core (80–120 items), tag by topic, pattern, difficulty, timebox, and failure modes, then practice in small “slices” that target one or two skills per day. Rotate coding, system design, and behavioral with deliberate drills and quick retros. Avoid random grinding; structure beats volume. For extra leverage, pair your bank with interview cheat sheets, solo practice mode, and an interview question bank you can filter quickly.

What “good” looks like for a bank

A useful interview question bank is lightweight, searchable in seconds, and tells you what to do next without thinking. It’s not a bookshelf of links; it’s a drill map.

Every item has a clear intent: what it trains and when to use it.
Tags are consistent across entries, so filters produce clean “slices”.
Notes are short: a 2–4 line summary, decision points, pitfalls, and test cases.
There’s a rotating “active set” for the week; everything else is shelved.

If you opened your bank now, could you pull five “heap + k-way merge + 30-minute” problems in under 10 seconds? If not, your tags need tightening.

Small banks work if they’re structured. Large banks stall if they’re not.

Build it once, then refine weekly

Start with a seed set. Pull from your past practice, curated lists, and company-specific prompts you’ve seen. Capture only what you intend to reuse.

Add 10–15 high-yield questions per week.
Prune duplicates and retire solved items that no longer teach.
Log misses and reintroduce them as spaced “refresh” items.

Where should you store it? Use a tool you’ll actually open daily. A spreadsheet, a simple database, or a dedicated interview question bank works. If your tool slows you down, it’s the wrong tool.

Two questions to ask while adding anything new:

What is the skill this item builds?
When will I use this again?

The tag schema that keeps you honest

Keep tags boring and consistent:

Topic: arrays, strings, graph, tree, heap, math, DP.
Pattern: sliding window, two-pointers, prefix sums, union-find, backtracking.
Difficulty: easy / medium / hard.
Timebox: 15 / 30 / 45.
Failure mode: misread, incomplete tests, complexity gap, incorrect data structure.
Slice: a weekly theme like “strings+two-pointers” or “caching+idempotency”.

Add 1–2 system design tags: “component” (e.g., cache, queue, sharding) and “constraint” (latency, consistency, durability). For behavioral, tag by competency (ownership, trade-offs, conflict resolution) and principle mapping if the company expects it.

Do your tags help you choose tomorrow’s drills in 30 seconds? If not, cut or tighten them.

Daily drills: the 30-minute block

Most engineers can find 30 minutes. Use it well:

Minute 0–5: Warm-up. Quick flash review of yesterday’s mistakes. One test-writing micro-drill.
Minute 5–25: One slice-driven problem. Talk out loud. State complexity targets early. Implement a clear happy path, then edge cases.
Minute 25–30: Post-mortem. Note the decision points, pitfall, and one sentence on what you’ll do differently next time.

Simple rule: never leave a session without writing what changed in your approach. One practice without reflection is just repetition.

Structured practice beats random grinding

Random grinding feels productive and rarely is. Purposeful drilling gives compounding returns.

Here’s how the three modes differ—use each on purpose, not by habit:

Approach	Primary Goal	When to Use	Time per Session	Common Mistake
Question Bank	Skill acquisition and recall	Daily slices targeting one or two tags	20–40 minutes	Hoarding questions without tags or notes
Practice	Speed and fluency	2–3 times weekly for timed reps	45–60 minutes	Solving without speaking or tests
Mock	Signal under pressure	Weekly or bi-weekly closer to loops	45–60 minutes	Treating it like practice instead of simulating conditions

Are you defaulting to one mode because it’s comfortable? Rotate deliberately: bank → practice → mock, then back to the bank for debrief and adjustments.

The “slice” method: focus beats breadth

A slice is a narrow theme running through your week: “arrays + prefix sums”, “graphs + BFS vs DFS trade-offs”, or “API design + idempotency”. Limit slices to one skill set at a time for faster feedback.

Monday/Wednesday: coding slice
Tuesday: system design slice
Thursday: coding slice or mixed warm-up
Friday: behavioral slice
Weekend: one mock and a short retrospective

A slice reduces decision fatigue. When you sit down, you already know which five questions you’ll pull.

System design and behavioral belong in the same bank

Treat system design prompts like code exercises:

Tag by component (cache, queue, rate limiter) and constraint (consistency vs availability).
Keep one diagram template and one decision checklist.
Record two to three reusable patterns: write-through cache, fan-out on write, read replicas.

Behavioral? Same discipline:

Tag stories by competency and outcomes.
Store a compact STAR (or CARL) outline.
Note follow-ups that often throw you off.

If you stumble in storytelling structure, rehearse with interview cheat sheets and use real-time interview support to pace and keep answers crisp.

Post-mortems: the compounding engine

After each session, write three things:

The one decision you’d change next time.
The smallest test you missed.
The phrase you’ll use to frame this pattern out loud.

Keep it short, two to four lines. Your future self will thank you.

Small post-mortems compound more than big write-ups you never reread.

Common mistakes (and simple fixes)

Mistake: Unsearchable bookmarks or screenshots.
Fix: Centralize and tag. If it’s not tagged, it doesn’t exist.
Mistake: Solving silently.
Fix: Narrate decisions. Use a timer and prompts. Practicing speaking is practicing interviewing.
Mistake: Only solving new problems.
Fix: Revisit high-yield items. Once to build, again to stabilize, later to accelerate.
Mistake: Mixing modes.
Fix: Decide the mode before you start: bank drill, timed practice, or mock.

Do you recognize your pattern in that list? Start by fixing one mistake this week, not all of them.

Using IQB (Interview Question Bank) alongside your tools

IQB is a straightforward way to keep your bank lean and searchable. It’s not a replacement for judgment; it’s a way to reduce friction.

Practical ways to use it:

Filter by topic, pattern, and timebox to create daily slices in seconds.
Attach short post-mortem notes and mark “refresh” intervals for spaced review.
Maintain separate views for coding, system design, and behavioral, but keep one tag schema so your week stays coherent.
Export a weekly “active set” you can run through with solo practice mode or during a commute.

When you move from preparation to live sessions, pair IQB with real-time interview support to keep your structure tight under time pressure.

A weekly plan you can actually sustain

3 × 30-minute coding slices (Mon/Wed/Thu): one topic + one pattern each.
1 × 45-minute system design slice (Tue): one component and one constraint.
1 × 30-minute behavioral slice (Fri): rehearse two stories with follow-ups.
1 × 60-minute mock (weekend): rotate coding and design, then a 10-minute debrief.

Total: ~4.5 hours. Sustainable even during a busy week. If you have more time, add a second mock or extend design to 60 minutes.

How do you adjust before a specific company loop? Shift your slices to mirror the loop emphasis and pull questions that match difficulty and constraints.

From practice to mock: bridging the gap

Mimic constraints gradually. In week one, solve with notes open. In week two, only allow your outline and a minimal checklist. In week three, practice clean-room: no notes, no prior code, just your voice and a timer.

Use a soft cap on time: 25 minutes for mediums, 40 for hards.
State a plan in the first two minutes.
Write tests before optimizing.

If you need a sparring partner or pacing cues, run one session with real-time interview support and one session solo with a timer. Keep variability in your practice so mocks don’t feel like a new environment.

Measuring progress without chasing vanity metrics

Track what matters:

Time to first correct solution with tests.
Number of distinct patterns you can explain cleanly.
Behavioral answers that land under 90 seconds with clear impact.
Design decisions you can justify with a trade-off statement.

A simple monthly checkpoint works: five medium questions, one design scenario, and two behavioral prompts. If you plateau, change your slice and add deliberate constraints (e.g., “no hash maps” week).

Company targeting without overfitting

You don’t need a separate bank per company. You need a lens.

Tag a small subset with “Company X” if there’s a clear theme (e.g., concurrency, logs parsing).
Map behavioral stories to the company’s principles but keep the core story the same.
Add 1–2 design variants that match the team’s domain (e.g., streaming vs batch).

Keep your foundation generic. Your slice does the targeting.

Snippet-ready takeaways

A small, well-tagged interview question bank beats a large, unstructured archive.

Practice in slices: one topic, one pattern, one constraint. Less choice, more progress.

Write post-mortems in 2–4 lines. Reflection drives acceleration, not more problems.

Rotate modes intentionally: drill with your bank, time your practice, simulate with a mock.

Start Practicing Smarter

Keep your bank open during prep and make it the first tab you reach for. If you want structure and recall on tap, consider a dedicated interview question bank for faster filtering. When you’re ready to rehearse delivery, lean on interview prep tools like the AI coding assistant, interview cheat sheets, and solo practice mode to turn your slices into repeatable reps.

References

Questions fréquentes

How big should my interview question bank be before I start serious practice?

You don’t need a giant library to see results. Aim for a focused set of 80–120 questions spread across core categories: data structures and algorithms, system design, and behavioral. The point is distribution and tagging, not raw count. Start with a seed list of 40–60, add 10–15 each week, and retire questions that no longer teach you something new. You’ll learn faster with a well-tagged, rotating set than by hoarding hundreds of unstructured links.

What’s the best way to tag questions so I can find the right drill fast?

Use a small, consistent tag schema: topic (e.g., graph, heap), pattern (e.g., sliding window, two-pointers), difficulty, timebox (15/30/45), and failure mode (e.g., off-by-one, misread constraints, over-optimizing early). Add a ‘slice’ tag for weekly focus themes like ‘arrays+prefix sums’ or ‘API idempotency’. Stick to 5–7 tags per item. Over-tagging causes friction; under-tagging makes retrieval slow.

How should I balance coding, system design, and behavioral in my bank?

Split your week by signal needs. A typical mix for general SWE: 3 coding sessions, 2 system design sessions, and 1 behavioral session. Use slices to align with upcoming interviews: if the loop has two design rounds, double your design allocation and maintain one short coding warm-up for speed. Behavioral should be treated like code—build prompts, write concise STAR/CARL notes, and rehearse delivery.

Can I use AI tools while practicing with my question bank?

Yes—with constraints. Use an AI coding assistant to generate alternative solutions after you’ve written your own, or to suggest edge cases and test inputs. Avoid using it for first-pass solutions. In live preparation, lean on interview cheat sheets for structure and a real-time interview support tool for pacing, timing, and follow-up prompts. The goal is to improve your decision-making, not outsource it.