# noCV engineering task library

Content version 5

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Tests, patches, and runbooks are requested deliverables. They become Outcome Evidence only through a qualified Mission and immutable Evidence IDs.

Independent adaptation must be observed under a declared verification policy and cite immutable Evidence IDs. Completing a planning ticket establishes no Ownership Evidence.

## CDOWN — A dependable mobile course-download shelf

Fictional learning app Birch offers synthetic text and small local media fixtures through a loopback adapter. No copyrighted course assets or network accounts are needed.

**Field:** Mobile. **Suggested stack:** React Native, TypeScript, SQLite, Emulator.

**Engineer value:** Practice mobile file lifecycles and background state recovery.

**Company value:** Inspect predictable resource usage and truthful download status.

**Delivery agreement:** Use generated local fixtures; app-store publishing is outside scope.

### Setup prerequisites

- Create small local byte fixtures and a range-response stub.

- Simulate low storage, interruptions and stale manifests.

### Describe downloads

Model local content and sizes.

#### CDOWN-101 — Distinguish unknown course-download sizes from zero bytes

**Bug · Medium priority · Foundational**

noCV practice brief v5 · CDOWN-101 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Describe downloads. Depends on: No preceding ticket.

Difficulty: Foundational. Estimated focused work: 60 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Mobile 100%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

Unmeasured courses show 0 MB and users assume downloads are free of storage cost. Display size uncertainty.

Acceptance criteria

- Unknown size is labeled

- Zero-byte fixtures remain valid

- Unit formatting has boundary tests

Implementation constraints

- Do not invent estimates without metadata.

Verification

- Render zero and unknown

- Render malformed size

Deliverables

- Size formatter and shelf states

Rollout and recovery: Fall back to byte counts for known values.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

#### CDOWN-102 — Keep mobile download buttons consistent with durable state

**Task · Medium priority · Intermediate**

noCV practice brief v5 · CDOWN-102 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Describe downloads. Depends on: No preceding ticket.

Difficulty: Intermediate. Estimated focused work: 105 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Mobile 80% · Storage systems 20%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

Returning to the shelf shows Download while a transfer is active. Render controls from one persisted lifecycle.

Acceptance criteria

- Active transfer shows pause

- Completed content shows open

- Invalid states do not expose start

Implementation constraints

- Define explicit lifecycle transitions.

Verification

- Navigate away and return

- Load corrupt lifecycle value

Deliverables

- Download-state projection

Rollout and recovery: Disable new downloads if state cannot be read.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

#### CDOWN-103 — Validate course manifest paths before creating files

**Bug · High priority · Intermediate**

noCV practice brief v5 · CDOWN-103 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Describe downloads. Depends on: CDOWN-101.

Difficulty: Intermediate. Estimated focused work: 120 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Security 60% · Storage systems 20% · Mobile 20%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

A malformed manifest filename can escape its course directory. Restrict all destinations to a scoped cache root.

Acceptance criteria

- Traversal is rejected

- Absolute paths are rejected

- Valid nested relative paths stay scoped

Implementation constraints

- Resolve paths before opening files.

Verification

- Write a valid nested fixture

- Reject parent-directory and drive paths

Deliverables

- Manifest path validator

Rollout and recovery: Reject new manifests until path validation is restored.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

### Handle transfer boundaries

Verify and recover bytes.

#### CDOWN-104 — Resume a mobile course transfer only with matching content identity

**Story · High priority · Advanced**

noCV practice brief v5 · CDOWN-104 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Handle transfer boundaries. Depends on: CDOWN-102, CDOWN-103.

Difficulty: Advanced. Estimated focused work: 180 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Storage systems 40% · Networking 30% · Mobile 30%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

A paused transfer resumes after content changed and produces mixed bytes. Bind ranges to a manifest version.

Acceptance criteria

- Resume checks content identity

- Mismatch discards incompatible partial bytes

- Restart remains explicit in UI

Implementation constraints

- Treat ETags as opaque validators.

Verification

- Resume unchanged fixture

- Change validator during pause

Deliverables

- Range-resume coordinator

Rollout and recovery: Disable resume and restart from zero safely.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

#### CDOWN-105 — Verify downloaded course bytes before exposing Open

**Task · High priority · Advanced**

noCV practice brief v5 · CDOWN-105 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Handle transfer boundaries. Depends on: CDOWN-104.

Difficulty: Advanced. Estimated focused work: 180 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Storage systems 60% · Mobile 40%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

A truncated transfer is marked complete because the connection closed normally. Verify length and declared digest.

Acceptance criteria

- Completed means both checks pass

- Mismatch stays unavailable

- Bad partial bytes can be removed

Implementation constraints

- Digest metadata comes from the local trusted manifest.

Verification

- Download valid fixture

- Truncate or flip one byte

Deliverables

- Completion verifier and corruption cases

Rollout and recovery: Disable Open for unverified content.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

#### CDOWN-106 — Pause mobile transfers when storage reservation fails

**Story · High priority · Intermediate**

noCV practice brief v5 · CDOWN-106 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Handle transfer boundaries. Depends on: CDOWN-102, CDOWN-103.

Difficulty: Intermediate. Estimated focused work: 135 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Storage systems 50% · Mobile 30% · Performance engineering 20%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

A nearly full emulator accepts several downloads and fails unpredictably. Reserve a bounded budget before writing.

Acceptance criteria

- Admission accounts for active transfers

- Failure preserves existing content

- User sees required space

Implementation constraints

- Reservation estimates must state uncertainty.

Verification

- Admit fitting transfer

- Start competing transfers exceeding budget

Deliverables

- Storage admission policy

Rollout and recovery: Stop new transfers while preserving installed courses.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

#### CDOWN-107 — Recover a course-download rename interrupted by process death

**Bug · High priority · Expert**

noCV practice brief v5 · CDOWN-107 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Handle transfer boundaries. Depends on: CDOWN-105, CDOWN-106.

Difficulty: Expert. Estimated focused work: 240 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Storage systems 50% · Mobile 30% · Database engineering 20%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

A crash between verification and final rename leaves duplicate shelf entries. Introduce a recoverable promotion record.

Acceptance criteria

- Recovery identifies one installed version

- Unverified partials stay hidden

- Repeated recovery is idempotent

Implementation constraints

- Keep metadata and file promotion reconciliation explicit.

Verification

- Kill at each promotion boundary

- Repeat recovery after missing temp file

Deliverables

- Promotion journal and crash cases

Rollout and recovery: Disable promotion and retain recoverable temporary files.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

### Maintain the shelf

Clean up and explain resource failures.

#### CDOWN-108 — Remove one downloaded course without breaking shared assets

**Task · Medium priority · Advanced**

noCV practice brief v5 · CDOWN-108 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Maintain the shelf. Depends on: CDOWN-107.

Difficulty: Advanced. Estimated focused work: 180 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Storage systems 70% · Mobile 30%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

Deleting a course removes an image another course references. Track local references before reclaiming shared blobs.

Acceptance criteria

- Unreferenced blobs are reclaimed

- Referenced blobs remain

- Failed cleanup is retryable

Implementation constraints

- Keep references scoped to verified manifests.

Verification

- Delete unique course

- Delete course with shared asset

Deliverables

- Reference-aware cleanup

Rollout and recovery: Disable physical reclamation while fixing reference accounting.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

#### CDOWN-109 — Show course-download progress without rendering every chunk

**Bug · Medium priority · Intermediate**

noCV practice brief v5 · CDOWN-109 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Maintain the shelf. Depends on: CDOWN-104.

Difficulty: Intermediate. Estimated focused work: 105 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Performance engineering 60% · Mobile 40%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

Small network chunks trigger excessive mobile renders. Coalesce progress updates while keeping completion immediate.

Acceptance criteria

- Updates have bounded frequency

- Completion bypasses throttle

- Paused bytes remain accurate

Implementation constraints

- Use an injected scheduler.

Verification

- Stream many chunks

- Pause between scheduled updates

Deliverables

- Progress coalescer and render-count check

Rollout and recovery: Reduce to coarse milestones if scheduling regresses.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.

#### CDOWN-110 — Provide a local download repair action with explicit scope

**Story · Medium priority · Intermediate**

noCV practice brief v5 · CDOWN-110 · A dependable mobile course-download shelf

Fictional engineering practice briefs. Starter repositories, fixtures, automated grading, and verified ownership are not included.

Phase: Maintain the shelf. Depends on: CDOWN-108, CDOWN-109.

Difficulty: Intermediate. Estimated focused work: 120 minutes; setup and prerequisite tickets are additional.

Estimated field mix: Mobile 50% · Storage systems 50%.

Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.

Users cannot recover one corrupt course without clearing the entire app. Add repair for the selected course only.

Acceptance criteria

- Repair revalidates selected files

- Other courses remain intact

- Offline repair explains deferred bytes

Implementation constraints

- Never clear account or unrelated application storage.

Verification

- Repair corrupted fixture

- Run repair offline

Deliverables

- Scoped repair flow and isolation checks

Rollout and recovery: Hide repair if deletion scope cannot be established.

Project prerequisites: Create small local byte fixtures and a range-response stub. Simulate low storage, interruptions and stale manifests.

Engineer value: Practice mobile file lifecycles and background state recovery.

Company value: Inspect predictable resource usage and truthful download status.

AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.

Planning status does not create Outcome Evidence or Ownership Evidence.
