Phase 07 · Lesson 11

Debugging Workshop

≈ 2 min core reading · 448 source/companion words
Learning contract

What you should be able to do after this

  • Explain Debugging Workshop without relying on framework buzzwords.
  • Connect the lesson to the phase outcome: Use relational modeling and SQL deliberately: keys, constraints, joins, transactions, indexes, and query reasoning.
  • Reproduce the relevant behavior and verify it with evidence.
  • Diagnose at least one representative failure instead of guessing.
Figure 7.11 — TaskFlow boundary map
Business invariant
table design
key/constraint
SQL query
query plan/index
transaction
durable rows
This lesson belongs to Phase 07. Keep the full request/data path visible even when today's code changes only one box.
Instructor workflow: predict first → implement the smallest slice → run it → inspect evidence → break one assumption → diagnose → explain it back. Do not copy the whole code block before understanding the first failing boundary.

Debugging Workshop — Phase 07: PostgreSQL Fundamentals

Goal Learn to diagnose this phase's failures systematically instead of reinstalling packages, changing random configuration, or copying a fix without understanding it.

The debugging loop 1. Reproduce the failure with the smallest reliable action. 2. Capture the exact symptom: command, status code, stack trace, network request, database state, or UI state. 3. Locate the earliest boundary where actual behavior diverges from expected behavior. 4. Form one hypothesis. 5. Change one variable. 6. Re-run the same reproduction. 7. Keep the fix only if the evidence supports the hypothesis.

Boundary walk Business invariant -> table design -> key/constraint -> SQL query -> query plan/index -> transaction -> durable rows

Start at the visible symptom and walk backward. Do not debug the database when the browser never sent the request. Do not debug React state when the API is returning a deterministic 403. The boundary walk tells you which evidence to collect next.

Failure drill 1 — Treating IDs as the only integrity mechanism Create or imagine this failure in a safe development environment. Write the expected symptom first. Then list the two or three observations that would distinguish this failure from neighboring causes. Repair it with the smallest change and verify the original reproduction no longer fails.

Failure drill 2 — Missing composite uniqueness on membership-like tables Create or imagine this failure in a safe development environment. Write the expected symptom first. Then list the two or three observations that would distinguish this failure from neighboring causes. Repair it with the smallest change and verify the original reproduction no longer fails.

Failure drill 3 — N+1 query patterns hidden by application loops Create or imagine this failure in a safe development environment. Write the expected symptom first. Then list the two or three observations that would distinguish this failure from neighboring causes. Repair it with the smallest change and verify the original reproduction no longer fails.

Failure drill 4 — Adding indexes without understanding query patterns Create or imagine this failure in a safe development environment. Write the expected symptom first. Then list the two or three observations that would distinguish this failure from neighboring causes. Repair it with the smallest change and verify the original reproduction no longer fails.

Do not hide the evidence Avoid immediately clearing caches, deleting lockfiles, resetting the database, disabling security checks, or reinstalling everything. Those actions may erase the evidence that teaches you what was wrong. Use them only after you can explain why they are relevant.

Debugging exit ticket Pick one failure from this workshop and write a short incident note: symptom, scope, root cause, fix, verification, and prevention. This is the same communication pattern used in professional bug reports and production incident follow-ups.

Executable lesson studio · sql

Now turn the explanation into engineering skill.

ORMs do not remove the database. SQL literacy lets you reason about correctness, constraints, query cost, transactions, and the evidence stored in PostgreSQL.

By the end, you should be able to

  • Explain Debugging Workshop in terms of concrete inputs, ownership, outputs, and evidence.
  • Implement or reproduce the smallest TaskFlow slice that demonstrates this sql concept.
  • Diagnose one representative sql failure using observable evidence instead of trial-and-error.
Figure 7.11B — Mental model
application intent
SQL statement
query planner
table/index
rows returned
Read left-to-right while implementing. When debugging, walk right-to-left until the first observed fact differs from your prediction.
Code-along sequence

One coherent change at a time

  1. 01

    Restate the goal of “Debugging Workshop” as one observable behavior. Write the success signal before touching code.

  2. 02

    Trace the boundary map: application intent → SQL statement → query planner → table/index → rows returned. Mark the one boundary this lesson changes.

  3. 03

    Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.

  4. 04

    Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.

  5. 05

    Connect the slice to TaskFlow’s phase artifact: A TaskFlow relational sketch plus SQL exercises that create, query, join, update, and constrain representative data.. Verify behavior from the outside as a user or API client would.

  6. 06

    Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.

  7. 07

    Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.

sqlQuery from TaskFlow data directly
SELECT t.id, t.title, u.name AS assignee
FROM tasks AS t
LEFT JOIN users AS u ON u.id = t.assignee_id
WHERE t.workspace_id = $1
ORDER BY t.created_at DESC, t.id DESC;

Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.

Verification

Prove the happy path

  1. Run the narrowest relevant command or request and require a clean exit/status.
  2. Inspect the boundary-specific evidence: terminal output, Network panel, database row/query plan, test report, container health, or deployment logs.
  3. Repeat the behavior once after the change so a one-off cached or stale result cannot masquerade as success.
Break it on purpose

Build debugging memory

  1. N+1 query patterns hidden by application loops
  2. Change one assumption in the sql example—identity, input, configuration, ordering, connectivity, or state—and predict the exact symptom before running it.
SymptomInvestigation path
Query is correct but slow

Capture EXPLAIN ANALYZE, row counts, filters, sort keys, and indexes before adding an index.

Unexpected duplicate/missing rows

Inspect join cardinality and constraints; do not hide a modeling bug with DISTINCT until you understand it.

Closed-reference challenge

Can you transfer the idea?

Without copying the final source, create a second small scenario that applies “Debugging Workshop” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.

Explain-back

Answer these without reopening the solution

  1. What problem does Debugging Workshop solve in TaskFlow, and what would be observably wrong without it?
  2. Which part of the sql boundary owns the decision, and which neighboring layer must not own it?
  3. What evidence proves the happy path instead of merely suggesting it worked?
  4. Name one realistic failure or abuse case and the first place you would inspect.
  5. If requirements doubled tomorrow, which part of this design should stay stable and which part is allowed to change?
Lesson studio

Turn the reading into skill

01

Do it

Wrap a multi-step change in a transaction and prove rollback preserves consistency.

Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.
02

Break it safely

N+1 query patterns hidden by application loops

Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.
03

Explain it back

Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?

If your explanation is vague, repeat the boundary trace before moving on.
Exit ticket

Before marking complete

Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.