Project 07: Round-Based PvP with Server-Validated Combat

Build a round-based PvP arena with authoritative damage and fair reward distribution.

Quick Reference

Attribute Value
Difficulty Advanced
Time Estimate 2-3 weeks
Main Programming Language Luau
Alternative Programming Languages None in Roblox runtime; optional external tooling only
Prerequisites Roblox Studio workflow, server-authoritative scripting basics
Key Topics Competitive game states, combat validation, anti-replay

1. Learning Objectives

By completing this project, you will:

  1. Model a secure state flow before implementation.
  2. Implement the main system using deterministic transitions.
  3. Validate behavior under failure and retry scenarios.
  4. Document operational and balancing trade-offs.

2. All Theory Needed (Per-Concept Breakdown)

Prediction versus authority split

Fundamentals

This concept defines the non-negotiable correctness boundary for the project. In Roblox, client devices are untrusted and can only request actions. Server-owned logic must validate, mutate, and replicate every progression or economy impact. Without this boundary, exploit scripts can break fairness and invalidate monetization quality.

Deep Dive into the concept

Treat every player action as an event envelope with explicit constraints. Validate actor identity, cooldown, ownership, and current-state eligibility before mutation. Use deterministic IDs and request nonces to reject replayed or duplicated calls. When actions fail validation, return a clear reason for debugging and player UX. Add telemetry for accepted and rejected requests, then inspect outlier patterns for abuse or design flaws. This approach turns security from reactive patching into proactive architecture.

How this fit on projects

  • Primary: this project.
  • Also used in all projects with progression, rewards, or purchases.

Definitions & key terms

  • Canonical state: server-owned source of truth.
  • Validation envelope: rule set checked before commit.
  • Replay protection: rejecting duplicate logical requests.

Mental model diagram

Input -> Client Feedback -> Request -> Server Validate -> Commit -> Replicate
                                  |                   |
                                  +-> Reject + log    +-> Telemetry + save

How it works

  1. Receive event request.
  2. Validate invariant conditions.
  3. Commit canonical mutation.
  4. Emit feedback and metrics.

Minimal concrete example

PSEUDOCODE
if not validate(event, player): return reject
applyMutation(profile, event)
replicateOutcome(player)

Common misconceptions

  • “Low-latency UI means client authority.” False.
  • “Local tests prove security.” False.

Check-your-understanding questions

  1. Which fields in the request should never be trusted directly?
  2. Why is nonce-based replay rejection useful?
  3. Which telemetry event helps detect abuse fastest?

Check-your-understanding answers

  1. Reward amount, entitlement flags, and authoritative state claims.
  2. It blocks duplicate processing from retries or exploit loops.
  3. Validation reject reason frequency by player cohort.

Real-world applications

  • Purchase grants, daily claims, combat outcomes.

Where you’ll apply it

  • This file and P15-live-seasonal-event-sprint.md.

References

  • Roblox Creator Docs: Client-server runtime.
  • Roblox Creator Docs: Security best practices.

Key insights

  • Trust boundaries are gameplay quality features, not only security features.

Summary

  • Server authority and deterministic validation prevent most live-economy failures.

Homework/Exercises to practice the concept

  1. Define three invariants for this project.
  2. Draft one request contract with validation rules.
  3. Define one replay scenario and mitigation.

Solutions to the homework/exercises

  1. Invariants should include legality, uniqueness, and progression integrity.
  2. Contract should include actor, action, preconditions, and rejection reasons.
  3. Store nonce or tx id and reject duplicates.

Combat envelope validation and anti-farm rewards

Fundamentals

This concept governs reliability under real usage. Live systems fail in partial ways: retries, disconnects, stale state, and delayed callbacks. Explicit state transitions and recovery behavior are mandatory if you want predictable outcomes and fast debugging.

Deep Dive into the concept

Map your project lifecycle as a state machine with explicit transitions, timeouts, and fallbacks. Each transition should define entry criteria, mutation effects, and observability hooks. Use versioned structures for durable data and include migration rules for future updates. Under dependency failures, fail safe first: preserve integrity even if this means temporary degraded functionality. Add runbook notes for expected incidents so release and support workflows stay stable.

How this fit on projects

  • Primary: this project.
  • Also used in projects focused on monetization and live ops.

Definitions & key terms

  • State transition: controlled move between runtime states.
  • Recovery mode: safe degraded operation state.
  • Guardrail metric: key metric that blocks risky rollouts.

Mental model diagram

State A -> State B -> State C
   |         |         |
 Recover    Retry     Commit + Observe

How it works

  1. Define states and transitions.
  2. Attach validation and timeout rules.
  3. Add telemetry for each branch.
  4. Use fallback/rollback if guardrails fail.

Minimal concrete example

PSEUDOCODE
if transitionAllowed(state, event): state = next(state, event)
else: state = RECOVERY

Common misconceptions

  • “Edge cases are rare, so postpone handling.” Costly in live games.
  • “Telemetry can be added later.” Harder to diagnose regressions.

Check-your-understanding questions

  1. What should happen when a critical dependency fails?
  2. Why keep transitions explicit?
  3. Which guardrail metric protects trust in this project?

Check-your-understanding answers

  1. Preserve integrity and enter controlled recovery behavior.
  2. To avoid hidden state drift and simplify debugging.
  3. A reliability or retention metric tied to user trust.

Real-world applications

  • Incident handling, rollout gating, and economy stabilization.

Where you’ll apply it

  • This file and capstone integration in P15-live-seasonal-event-sprint.md.

References

  • Roblox Creator Docs: Data stores and monetization flows.
  • Live ops and experimentation references.

Key insights

  • Deterministic state plus recovery planning reduces incident blast radius.

Summary

  • Reliability architecture turns features into durable products.

Homework/Exercises to practice the concept

  1. Draw full state machine for this project.
  2. Define one rollback threshold.
  3. Draft one failure runbook.

Solutions to the homework/exercises

  1. Include all normal and exceptional transitions.
  2. Choose threshold tied to integrity or retention.
  3. Include detection, mitigation, comms, verification.

3. Project Specification

3.1 What You Will Build

A production-oriented implementation of Round-Based PvP with Server-Validated Combat with secure state handling, clear user outcomes, and iteration-ready telemetry.

3.2 Functional Requirements

  1. Deliver full core behavior for the project goal.
  2. Ensure canonical state updates are server-validated.
  3. Persist relevant progression/entitlement state when required.
  4. Produce operator-facing diagnostics.

3.3 Non-Functional Requirements

  • Performance: Stable behavior in local multiplayer testing.
  • Reliability: No canonical-state corruption in retry/disconnect tests.
  • Usability: Clear user-facing feedback and error states.

3.4 Example Usage / Output

Player performs core action -> receives immediate local feedback -> server confirms outcome
If reconnect occurs -> canonical state remains valid and consistent
If invalid action occurs -> clear rejection and no state corruption

3.5 Data Formats / Schemas / Protocols

  • Event schema for core actions.
  • Versioned profile schema for durability.
  • Metrics schema for funnel and reliability events.

3.6 Edge Cases

  • Duplicate requests.
  • Disconnect during critical transitions.
  • Out-of-order events.
  • Temporary service failures.

3.7 Real World Outcome

Learner can execute deterministic scenario, compare outcome against expected behavior, and verify no integrity regression under one forced failure case.

3.7.1 How to Run (Copy/Paste)

  1. Open Roblox Studio place.
  2. Start local server with 2 clients.
  3. Execute golden path and one failure path.

3.7.2 Golden Path Demo (Deterministic)

  • Complete one full cycle of the project’s primary loop.
  • Verify expected state, UI feedback, and telemetry event.

3.7.3 If CLI: provide an exact terminal transcript

Not applicable for this in-experience Roblox project.

3.7.4 If Web App

Not applicable.

3.7.5 If API

Not applicable as standalone API.

3.7.6 If Library

Not applicable.

3.7.7 If GUI / Desktop / Mobile

Roblox in-experience GUI should show clear success, loading, and error states.

3.7.8 If TUI

Not applicable.

4. Solution Architecture

4.1 High-Level Design

User Action -> Client UX -> Server Validation -> Canonical Mutation -> Persist/Replicate -> Observe

4.2 Key Components

Component Responsibility Key Decisions
Action Controller Accepts and routes core events Deterministic transition mapping
Validation Layer Enforces invariants Rejects replay/invalid state
Persistence Layer Handles durable state Versioned schema and retries
Metrics Layer Emits operational signals Enables safe iteration and rollback

4.4 Data Structures (No Full Code)

ProjectState {
  profileVersion,
  progression,
  balances,
  flags,
  processedEvents,
  updatedAt
}

4.4 Algorithm Overview

Key Algorithm: Deterministic Transition Commit

  1. Validate event.
  2. Compute next state.
  3. Persist or checkpoint.
  4. Replicate and log.

Complexity Analysis:

  • Time: O(1) typical transition cost.
  • Space: O(n) by active player/session entities.

5. Implementation Guide

5.1 Development Environment Setup

  • Configure local server test with multiple clients.
  • Enable developer console logs.
  • Prepare deterministic test profiles.

5.2 Project Structure

experience/
├── server/
│   ├── controllers/
│   ├── validation/
│   └── persistence/
├── client/
│   ├── ui/
│   └── presentation/
├── shared/
│   └── contracts/
└── docs/
    └── runbook.md

5.3 The Core Question You’re Answering

“How do I keep combat responsive on clients while outcomes remain server-authoritative?”

5.4 Concepts You Must Understand First

  1. Prediction versus authority split
    • Which invariants must always hold?
    • Which payload fields are untrusted?
  2. Combat envelope validation and anti-farm rewards
    • What are legal state transitions?
    • What is fallback behavior on failure?

5.5 Questions to Guide Your Design

  1. What is the minimum safe state model for this project?
  2. Which user actions need strongest validation?
  3. Which metric determines rollback if quality drops?

5.6 Thinking Exercise

Draw the transition graph for one full user journey including one failure branch.

5.7 The Interview Questions They’ll Ask

  1. How do you enforce server authority here?
  2. What edge case was hardest and why?
  3. What telemetry did you add first?
  4. How do you prevent duplicate grants/outcomes?
  5. How would you scale this architecture?

5.8 Hints in Layers

Hint 1: Define state first

  • Name transitions before scripting.

Hint 2: Validate all meaningful mutations

  • Client can request, never decide.

Hint 3: Instrument early

  • Log accepted and rejected transitions.

Hint 4: Rehearse failure paths

  • Disconnects and duplicate callbacks are mandatory tests.

5.9 Books That Will Help

Topic Book Chapter
Roblox runtime model Roblox Creator Docs Client-server and scripting
Data durability Roblox Creator Docs Data Stores
Maintainable game systems Game Programming Patterns State and architecture

5.10 Implementation Phases

Phase 1: Foundation

  • Model state transitions and request contracts.
  • Build minimal deterministic happy path.

Phase 2: Core Functionality

  • Add full validation and persistence/retry logic.
  • Verify edge paths.

Phase 3: Polish & Edge Cases

  • Improve UX messaging and telemetry.
  • Tune pacing and finalize runbook checks.

5.11 Key Implementation Decisions

Decision Options Recommendation Rationale
State authority Client-heavy or server-authoritative Server-authoritative Protects fairness and economy integrity
Save strategy Exit-only or periodic checkpoints Periodic + exit flush Reduces loss risk
Rollout mode Instant global or flagged Flagged Limits blast radius

6. Testing Strategy

6.1 Test Categories

Category Purpose Examples
Core flow tests Validate baseline behavior One full loop cycle
Integrity tests Validate trust and idempotency Duplicate request replay
Recovery tests Validate resilience Disconnect/reconnect around transition

6.2 Critical Test Cases

  1. Deterministic happy path completion.
  2. Duplicate callback/request rejection.
  3. Recovery from one forced failure case.

6.3 Test Data

  • Fixed test profile and deterministic event sequence.

7. Common Pitfalls & Debugging

7.1 Frequent Mistakes

Pitfall Symptom Solution
Trusting client values Exploit-friendly outcomes Validate and compute server-side
Missing idempotency Duplicate rewards/grants Track processed transaction ids
Weak recovery paths State desync after failures Add explicit fallback transitions

7.2 Debugging Strategies

  • Reproduce with deterministic event scripts.
  • Compare expected transition logs vs observed logs.
  • Validate canonical state snapshots after each key step.

7.3 Performance Traps

  • Unbounded logging without sampling.
  • Heavy validation on high-frequency loops without batching.

8. Extensions & Challenges

8.1 Beginner Extensions

  • Add one quality-of-life UI improvement.
  • Add one additional telemetry event.

8.2 Intermediate Extensions

  • Add segmentation-based tuning.
  • Add one extra anti-abuse safety check.

8.3 Advanced Extensions

  • Add feature-flagged experiment treatment.
  • Add automated rollback trigger check.

9. Real-World Connections

9.1 Industry Applications

  • Live service game operations with reliable progression.
  • Monetization systems requiring strict entitlement safety.
  • Roblox architecture and tooling references.
  • General game systems and live ops examples.

9.3 Interview Relevance

  • Demonstrates system design plus product operation thinking.

10. Resources

10.1 Essential Reading

  • Roblox Creator Docs for platform APIs and policies.
  • The Art of Game Design for loop and motivation framing.

10.2 Video Resources

  • Roblox creator talks on scaling and monetization strategy.
  • Live ops talks on experimentation and retention.

10.3 Tools & Documentation

  • Roblox Studio Developer Console.
  • Creator analytics dashboards.
  • Previous project for prerequisites.
  • Next project for system integration progression.

11. Self-Assessment Checklist

11.1 Understanding

  • I can explain trust boundaries in this project.
  • I can explain transition and recovery flows.
  • I can justify my key design trade-offs.

11.2 Implementation

  • Functional requirements are complete.
  • Critical tests pass.
  • Edge cases do not corrupt canonical state.
  • Telemetry is emitted and readable.

11.3 Growth

  • I can describe this project in interview terms.
  • I documented one next-iteration improvement.
  • I can map this project to a production equivalent.

12. Submission / Completion Criteria

Minimum Viable Completion:

  • Core flow works reliably.
  • Validation blocks obvious exploit paths.
  • Deterministic demo passes.

Full Completion:

  • Minimum completion plus failure recovery and telemetry quality.
  • Runbook for one likely incident exists.

Excellence (Going Above & Beyond):

  • Controlled experiment added with guardrail metrics.
  • Feature-flagged rollout with documented decision memo.