A · Professional problem solving and implementation

Debugging

Narrowing from a symptom, forming hypotheses, verifying, and fixing.

Classification boundary

Include: Include questions about tracing symptoms, validating hypotheses, and fixing faults.

Choose a neighboring leaf when: Use system design for planned capacity and failure behavior, and quality/security for test or release controls.

This capability may appear in standards across different stages. Explore stage expectations

24 questions

Choose a group based on the evidence you need. Groups follow existing question formats, not difficulty or mandatory prerequisites. Each batch has up to eight questions.

Judgment and options10

Compare goals, constraints, options, and trade-offs.

Questions 1–8

Your endpoint works in local tests, but during integration a frontend colleague insists it errors or returns nothing. What means do you use to locate the problem, and how do you produce evidence the other person will accept?
After cache expiry, many requests hit the origin at once, and recovery causes a second traffic spike. How would you diagnose and suppress a cache stampede and warm-up storm?
In production the same order is occasionally submitted twice, and you cannot reproduce it locally. How would you narrow it down, and would you stop the bleeding first or add observability first?
After splitting a large frontend bundle into several smaller ones, the first screen got slower. What causes would you suspect, and how would you verify them?
A cache key is invalidated and logs show a database reread, yet some users still see old data. Switching to the primary helps but does not eliminate it. How would you investigate caches, replicas, and clients?
API latency rises while database CPU remains low, and application logs show connection waits. How would you distinguish connection leaks, an undersized pool, and slow transactions holding connections?
A reconciliation shows timestamps from two data centers placing event A before B, while the message trace shows B triggered A. How would you distinguish clock skew, processing delay, and business causality, and choose trustworthy diagnostic evidence?
During a cross-time-zone handoff, a critical alert was sent. The outgoing on-call engineer assumed the incoming engineer would handle it, while the incoming engineer never acknowledged it; escalation was delayed. How would you reconstruct the ownership chain, fix acknowledgment and handoff, and verify the change?

Questions 9–10

Average latency is stable while p99 worsens, with large differences across tenants. How would you narrow the cause to queuing, lock contention, downstream fan-out, or resource isolation?
At peak load, the entry service records a request but downstream events are missing, while retries amplify traffic. How would you trace the request through each service to locate loss and duplication?

Implementation and verification14

Examine execution, verification, and correction.

Questions 1–8

An API has been slow since yesterday, and there is no release on record. Given logs, monitoring, and database slow-query records, in what order would you investigate?
A list screen scrolls poorly even though network metrics are normal and memory is stable. How would you determine whether main-thread computation, layout/drawing, or lock waits are responsible?
After a database field change, only some downstream jobs fail intermittently. How would you identify consumers still using the old contract and decide between rollback and a compatibility fix?
Monthly aggregates initially match detail reports, but the gap grows over several weeks. How would you narrow the cause among definition changes, late data, duplicate processing, and historical backfills?
A critical dependency intermittently times out in one region while overall health checks remain green. How would you assess impact and isolate or degrade it safely?
Message backlog often falls after scaling out, then returns a few hours later. What producer, consumer, and message characteristics would you inspect to locate the actual bottleneck?
Average service latency is stable, but p99 has risen for a week and complaints cluster among a few large customers. How would you locate the problem and choose what to verify first?
A page has valid server-rendered HTML, but content flickers after hydration and the console reports a warning. How would you locate the difference between server and client rendering?

Questions 9–14

After a downstream service becomes unstable, upstream traffic appears flat while request counts and queue depth double and several services time out. How would you determine whether retries are amplifying the failure?
Latency is normal after a release, but p99 rises gradually after several hours and temporarily recovers after a restart. CPU is steady while connection counts and heap memory slowly grow. How would you break down hypotheses and design low-risk tests?
A feature works on the corporate network and most home networks, but requests often time out on a particular carrier or under poor connectivity; server error rates do not rise at the same time. How would you isolate causes across client, network path, protocol, and retry behavior?
The client sees one submission, but the server occasionally creates two identical records. It usually happens after a timeout and retry, with no obvious log error. How would you reconstruct the request timeline and verify where duplication occurs?
The default locale renders correctly, but a few buttons overflow and tables shift after switching languages; failures occur only on narrow screens with enlarged system text. How would you narrow the cause and build regression coverage?
Fresh installations work, but users who upgraded across several versions report missing local drafts. The issue is hard to reproduce, and the server has no corresponding deletion record. How would you preserve evidence and investigate migrations, cache cleanup, and lifecycle callbacks?

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