今日固定时间表
只有三个学习窗口：08:50-10:55、14:30-16:15、20:30-21:15。section links 只放在本日页面。
| 08:50-10:55 | System design 读 Payment System 的 Potential Deep Dives、Bonus Deep Dives 与 level expectations；做 Bad/Good/Great：timeout=failure、pending+manual reconciliation、event-driven safety+immutable ledger。 |
|---|---|
| 14:30-16:15 | NeetCode Linked List 三道连续题位，每题 30m solve + 5m pattern/invariant/bug/complexity evidence。 |
| 20:30-21:15 | Recall / Staff Q&A / Mock Staff Q&A drill：durability/auditability, asynchronous network, webhooks, scale and Kafka partitioning. |
算法模块
连续 NeetCode Linked List tag；每天恰好 3 个 slot。
| # | Problem / mode | Pattern | Invariant | Bug risk | Time | Space |
|---|---|---|---|---|---|---|
| 4 | Reorder Linked List NEW · 30m solve + 5m evidence | split reverse weave | first half and reversed second half are consumed alternately | not severing first half before weave | O(n) | O(1) |
| 5 | Remove Node From End of Linked List NEW · 30m solve + 5m evidence | gap pointer | fast is n nodes ahead of slow | removing head without dummy | O(n) | O(1) |
| 6 | Copy Linked List With Random Pointer NEW · 30m solve + 5m evidence | hash map clone | map old node to exactly one clone | random pointer to unseen node | O(n) | O(n) |
Hello Interview 精确目录
保留 live original titles；每行都有 canonical anchor 和 disposition。
| 项目 | 精确 canonical section | Disposition | 今天怎么用 |
|---|---|---|---|
| Payment System | Potential Deep Dives | deep dive | shift to security, auditability, asynchronous networks, scale |
| Payment System | 1) The system should be highly secure | deep dive | API keys, request signing, tokenization/iFrame isolation |
| Payment System | 2) The system should guarantee durability and auditability with no transaction data ever being lost, even in case of failures. | deep dive | database + CDC + immutable event stream as audit trail |
| Payment System | 3) The system should guarantee transaction safety and financial integrity despite the inherently asynchronous nature of external payment networks | deep dive | pending states, reconciliation, compensation |
| Payment System | 4) The system should be scalable to handle high transaction volume (10,000+ TPS) | deep dive | stateless services, Kafka partitioning, database sharding |
| Payment System | Servers | deep dive subheading | service horizontal scale boundaries |
| Payment System | Kafka | deep dive subheading | partition by payment_intent_id for ordered transitions |
| Payment System | Database | deep dive subheading | merchant sharding, read replicas, retention/archive |
| Payment System | Bonus Deep Dives | bonus deep dive | webhook system at overview depth |
| Payment System | 1) How can we expand the design to support Webhooks? | bonus deep dive | merchant callbacks, signed payloads, retry/outbox |
| Payment System | What is Expected at Each Level? | level expectation | calibrate Senior+/Staff depth |
| Payment System | Mid-level | level expectation | basic flow and security awareness |
| Payment System | Senior | level expectation | consistency, race windows, scaling |
| Payment System | Staff+ | level expectation | event sourcing, reconciliation, network uncertainty |
DDIA 精确决策卡
只读 Ch8、Ch12、Ch13 中能改变今天设计选择的小节。
| 项目问题 | 精确 DDIA subsection | 改变的系统决定 |
|---|---|---|
| Should payment service use 2PC across DB, Kafka, provider? | Ch8 · 分布式事务 | avoid heterogenous 2PC for external networks; use outbox/CDC and reconciliation |
| What if completion event is missing after DB commit? | Ch8 · 再谈恰好一次消息处理 | replay durable state and processed-event IDs instead of trusting a single publish |
| How does the ledger prove a six-month-old dispute? | Ch13 · 为可审计性而设计 | append immutable entries and make corrections as compensating events |
本日项目 artifacts
今日产出、修复与英语 recall
| 必须交付 | Payment deep-dive sheet：ledger invariant、timeout failure window、provider callback reconciliation、compensation/refund path、SLIs。 |
|---|---|
| 修复规则 | 如果回答只说组件名，重写为 decision -> mechanism -> invariant -> failure window -> recovery -> metric。 |
| English recall | Correctness is the durable source of truth; low-latency status, aggregates, dashboards, and alerts are views with freshness and repair semantics. |
Detailed lecture notes, audio, recall scripts, PDFs, Staff Q&A, and mock packs are archived locally and are intentionally not published on this site.