Project 15: Leaderboards and Fairness Guards

Global and friends leaderboards with submission validation windows and anti tamper heuristics.

Quick Reference

Attribute Value
Difficulty Level 4
Time Estimate 1 to 2 weeks
Main Programming Language C# (.NET 8) + MonoGame
Alternative Programming Languages F#, C++ (raylib), Godot C#
Coolness Level Level 4
Business Potential Level 3
Prerequisites Deterministic loop basics, debugging discipline, content pipeline fundamentals
Key Topics Server authoritative checks, Submission throttling, Cheat signal triage

1. Learning Objectives

  1. Translate one concrete production question into a testable implementation plan.
  2. Implement and validate the feature in a MonoGame runtime context.
  3. Instrument success and failure paths with actionable diagnostics.
  4. Produce a repeatable demo artifact for portfolio or interview use.

2. All Theory Needed (Per-Concept Breakdown)

Server authoritative checks

Fundamentals Server authoritative checks is central to this project because it defines the non-negotiable behavioral contract for the feature. You should be able to describe valid inputs, legal state transitions, and expected outputs under normal and failure conditions.

Deep Dive into the concept Treat Server authoritative checks as a boundary-setting mechanism. Start by defining the smallest deterministic scenario that proves the feature works. Stress that scenario under altered timing, altered content inputs, and altered user actions. If behavior changes unexpectedly, document hidden coupling and sequence assumptions. Keep transitions explicit and observable via logs or debug panels. Connect each transition to an event record so regression analysis is possible after refactors.

Submission throttling

Fundamentals Submission throttling ensures the project scales from local prototype behavior to repeatable system behavior.

Deep Dive into the concept Use Submission throttling to reason about data flow ownership and mutation timing. Document where writes occur, when validation runs, and how rollback behaves if a write fails.

Cheat signal triage

Fundamentals Cheat signal triage connects this project to shipping reality by forcing you to think about operational constraints early.

Deep Dive into the concept Define one production-like failure mode related to Cheat signal triage and build a mitigation checklist. The solution is complete when you can demonstrate both a golden path and a controlled failure path.

3. Project Specification

3.1 What You Will Build

A leaderboard integration with ranking views and anti-abuse validation guards for suspicious score submissions.

Visible game deliverable:

  • Leaderboard table with global/friends tabs
  • Around-player panel highlights nearby ranks
  • Submission audit panel for rejected outliers

3.2 Functional Requirements

  1. Submit validated score payloads to Steam leaderboards.
  2. Display global, friends, and around-player standings.
  3. Reject outlier submissions via configurable sanity thresholds.
  4. Log rejection reasons for fairness audits.

3.3 Non-Functional Requirements

  • Performance: Must remain inside project-appropriate frame budget.
  • Reliability: Must recover from at least one injected failure mode.
  • Usability: Outcome must be observable by a reviewer in under two minutes.

3.4 Example Usage / Output

[LB] submit score=45123 accepted=true
[LB] submit score=99999999 accepted=false reason=threshold_guard
[LB] around_player rank=847 score=45123

3.5 Data Formats / Schemas / Protocols

  • Event record: {timestamp, module, action, result}
  • Feature state snapshot: {version, state, counters, flags}

3.6 Edge Cases

  • Duplicate submissions in same second.
  • Negative or impossible score values.
  • Temporary API timeout during standings fetch.

3.7 Real World Outcome

This is a game-facing outcome you can see and play immediately.

What you will see in the game window:

  • Leaderboard table with global/friends tabs
  • Around-player panel highlights nearby ranks
  • Submission audit panel for rejected outliers

Project 15 Leaderboards and Fairness Guards Window Mockup

How you interact:

  • G global tab
  • F friends tab
  • Submit test score button in diagnostics

3.7.1 How to Run (Copy/Paste)

$ dotnet restore
$ dotnet build
$ dotnet run --project src/Game -- --scene leaderboards

3.7.2 Golden Path Demo (Deterministic)

  1. Start the scene and confirm all HUD panels load.
  2. Perform the three core interactions listed above.
  3. Verify the success signal appears without warnings.

3.7.3 If CLI: exact transcript

$ dotnet run --project src/Game -- --scene leaderboards
[LB] submit score=45123 accepted=true
[LB] submit score=99999999 accepted=false reason=threshold_guard
[LB] around_player rank=847 score=45123

3.7.7 If GUI / Desktop

+------------------------------------------------------+
| leaderboards                                   [F1 HUD] |
|------------------------------------------------------|
| PLAYFIELD: gameplay objects and interactions         |
| HUD: key metrics + status badges                    |
| STATUS: success/failure cues and prompts            |
+------------------------------------------------------+

4. Solution Architecture

4.1 High-Level Design

Score Event -> Validator -> Submission Queue -> Steam Leaderboard -> Ranking Views

Score Event -> Validator -> Submission Queue -> Steam Leaderboard -> Ranking Views

4.2 Key Components

Component Responsibility Key Decisions
ScoreValidator Applies fairness and sanity checks Guard rails before network submission
LeaderboardClient Submits/fetches leaderboard data Retry with bounded backoff
RankingViewModel Formats global/friends/around-player views Stable sorting and highlighting rules

4.4 Algorithm Overview

  1. Validate preconditions.
  2. Apply deterministic transition.
  3. Emit feedback and telemetry.
  4. Persist if required.

5. Implementation Guide

5.3 The Core Question You’re Answering

“How do you keep leaderboards meaningful when clients are untrusted?”

5.4 Concepts You Must Understand First

  1. Server authoritative checks
  2. Submission throttling
  3. Cheat signal triage

5.5 Questions to Guide Your Design

  1. Which heuristic filters obvious cheats without blocking legitimate highs?
  2. How will you present rejected submissions to developers?
  3. What fallback should UI use when standings fetch fails?

5.6 Thinking Exercise

Trace one full success path and one failure path on paper before implementation.

5.7 The Interview Questions They’ll Ask

  1. Why did you pick this architecture boundary?
  2. Which failure mode did you prioritize first and why?
  3. How does your instrumentation accelerate debugging?
  4. How would you scale this feature to a larger game?

5.8 Hints in Layers

  • Hint 1: Stabilize one invariant before feature expansion.
  • Hint 2: Add diagnostics before optimization.
  • Hint 3: Keep platform calls at system boundaries.
  • Hint 4: Re-run deterministic scenario after each refactor.

5.9 Books That Will Help

Topic Book Chapter
Core concept “Multiplayer Game Programming by Glazer and Madhav” Relevant concept chapter
Reliability “Release It!” Failure handling chapters
Architecture “Clean Architecture” Boundary and dependency chapters

6. Testing Strategy

  1. Golden path completes and emits success signal.
  2. Injected failure path recovers without crash.
  3. Re-run scenario after restart and confirm consistency.

7. Common Pitfalls & Debugging

  • Hidden initialization order coupling
  • Time-coupled behavior tied to render rate
  • Missing fallback behavior on platform call failure

8. Extensions & Challenges

  • Beginner: add one extra diagnostics panel metric.
  • Intermediate: add replay capture for event flow.
  • Advanced: add automated stress test harness.

9. Real-World Connections

This project mirrors shipping feature-module work in real indie and mid-size game teams.

10. Resources

  • Steamworks official docs
  • MonoGame docs
  • Gemini image generation docs (for asset-related projects)

11. Self-Assessment Checklist

  • I can explain the feature invariant and prove it in a demo.
  • I can trigger and handle one deterministic failure scenario.
  • I can describe tradeoffs and future scaling choices.

12. Submission / Completion Criteria

Minimum Viable Completion:

  • Feature works in deterministic golden path.
  • One controlled failure path is handled gracefully.
  • Core diagnostics are visible and documented.

Full Completion:

  • All minimum criteria plus edge-case coverage and regression checks.

Excellence:

  • Includes polished instrumentation and clear productionization notes.