M.I.M.I.R - Multi-agent Intelligent Memory & Insight Repository

# Debugging Challenge: E-Commerce Order Processing System ## 🎯 Mission This order processing system has **multiple subtle bugs** that only appear in production scenarios. All unit tests pass, but customers are reporting issues: - Duplicate payments being charged - Orders fulfilled at incorrect prices - Inventory showing as unavailable when it should be in stock - Overnight shipping offered to locations that can't receive it - Discount calculations producing unexpected totals Your task: **Find and document the root causes of these production issues.** --- ## 📋 System Overview The system processes customer orders through multiple stages: 1. **Inventory Validation** - Check product availability and reserve stock 2. **Order Calculation** - Calculate item totals and shipping costs 3. **Payment Processing** - Charge customer with retry logic 4. **Order Fulfillment** - Commit inventory and complete order ### Key Components - **`InventoryManager`** - Tracks stock levels and reservations - **`PaymentProcessor`** - Handles payment gateway integration with retries - **`ShippingCalculator`** - Computes shipping rates based on weight and destination - **`OrderProcessor`** - Orchestrates the complete order workflow - **`DiscountCalculator`** - Applies promotional and volume discounts --- ## 🧪 Running Tests All tests currently pass: ```bash npm test testing/agentic/order-processor.test.ts ``` Expected output: ``` ✓ OrderProcessor ✓ Single Order Processing ✓ should process a simple order successfully ✓ should calculate order total correctly ✓ should fail when product is out of stock ✓ Shipping Calculation ✓ should calculate shipping for US addresses ✓ should calculate shipping for international addresses ✓ Payment Processing ✓ should process payment successfully ✓ should handle payment with round numbers ✓ Batch Processing ✓ should process multiple orders sequentially ✓ DiscountCalculator ✓ should apply coupon discount correctly ✓ should apply volume discount for large orders ✓ should handle orders without discounts Tests: 11 passed, 11 total ``` --- ## 🐛 Reported Production Issues ### Issue 1: Duplicate Charges **Report**: "Customer charged twice for the same order during Black Friday sale" **Context**: High traffic, many concurrent requests **Impact**: Finance team processing refunds ### Issue 2: Orders at Wrong Total **Report**: "Order subtotal showing as just shipping cost, items appear free" **Context**: Orders with multiple items **Impact**: Massive revenue loss ### Issue 3: Phantom Inventory Depletion **Report**: "Products showing out of stock but warehouse has inventory" **Context**: Happens after payment failures **Impact**: Lost sales, requires manual inventory reconciliation ### Issue 4: Invalid Overnight Shipping **Report**: "Promised overnight delivery to Hawaii, cannot fulfill" **Context**: Customer entered address with lowercase state code **Impact**: Delivery failures, customer complaints ### Issue 5: Inventory Oversold **Report**: "Accepted more orders than available stock" **Context**: Batch processing of multiple orders **Impact**: Backorders, unable to fulfill commitments ### Issue 6: Incorrect Discounts **Report**: "Discount amount doesn't match promotion terms" **Context**: Orders with both coupon code and volume discount **Impact**: Revenue variance, customer disputes --- ## 🔍 Debugging Guidelines ### Phase 1: Understanding the System 1. Read through the code to understand the workflow 2. Identify complex areas: - Async operations and Promise chains - Shared state and concurrency - Calculation logic - Error handling paths ### Phase 2: Reproducing Issues 1. Think about edge cases not covered by tests 2. Consider concurrency scenarios 3. Test with unusual input values 4. Verify state consistency after failures ### Phase 3: Root Cause Analysis 1. Add strategic debug markers 2. Trace execution paths 3. Check for: - Race conditions on shared resources - Async/await misuse - Resource leaks in error paths - Type coercion issues - Incorrect operators or precedence ### Phase 4: Documentation Document each bug with: - **Location**: File and line number(s) - **Type**: Race condition, async misuse, logic error, etc. - **Root Cause**: Technical explanation of WHY it fails - **Trigger**: Specific conditions that expose the bug - **Impact**: What happens in production - **Fix Direction**: High-level approach (don't implement) --- ## ⚠️ Important Constraints 1. **Do NOT modify the tests** - They represent the current test suite 2. **Do NOT implement fixes** - Only identify and document 3. **Clean up all debug markers** - Verify with `git diff` before finishing 4. **Use inline output filtering** - `grep`, `head`, `tail` only 5. **Provide evidence** - Debug output that proves your analysis --- ## 🎯 Success Criteria Your investigation is complete when you have: - [ ] Identified root causes for all 6 production issues - [ ] Provided specific line numbers for each bug - [ ] Explained the technical reason each bug occurs - [ ] Described how to trigger/reproduce each bug - [ ] Suggested fix direction without implementing - [ ] Cleaned up ALL debug markers (verify with `git diff`) - [ ] Documented findings in clear chain-of-thought format --- ## 💡 Hints (Use Only If Stuck) <details> <summary>Hint 1: Common Bug Patterns</summary> Look for these patterns that often hide bugs: - `Promise.all()` without proper coordination - `forEach` with async callbacks - Shared state accessed without locks - Floating point arithmetic - String comparisons without normalization - `for...in` loops on arrays - Missing cleanup in error paths </details> <details> <summary>Hint 2: Testing Strategies</summary> Try these approaches: - Add properties to arrays before processing - Use concurrent execution (Promise.all) - Test with decimal values like 10.10 - Try mixed case input strings - Force failures at different stages - Verify state after exceptions - Check exact values, not just > 0 </details> <details> <summary>Hint 3: Debug Marker Locations</summary> Strategic places for markers: - Before/after async operations - At state mutation points - In error handling blocks - Before/after shared resource access - Inside loop iterations - At calculation steps </details> --- ## 📊 Difficulty Assessment **Estimated Time**: 2-4 hours for experienced debugger **Bug Distribution**: - Easy: 0 bugs (none are obvious) - Medium: 3 bugs (need specific test cases) - Hard: 4 bugs (need failure scenario analysis) - Very Hard: 2 bugs (need concurrency understanding) **Required Skills**: - JavaScript/TypeScript async patterns - Concurrency and race conditions - Floating point arithmetic - State management - Promise/async debugging --- ## 📝 Deliverable Template ```markdown # Production Bug Analysis: Order Processing System ## Bug 1: [Short Description] **Location**: `filename.ts:lineNumber` **Type**: [Race Condition / Async Misuse / Logic Error / etc.] **Root Cause**: [Technical explanation of WHY it fails] **Trigger Conditions**: - [Specific scenario that exposes bug] - [Example: "Two concurrent calls with same order ID"] **Production Impact**: - [What happens when bug occurs] - [Example: "Customer charged twice"] **Evidence**: ``` [Debug output that proves the bug] ``` **Fix Direction**: [High-level approach without implementing] [Example: "Use atomic operation or mutex for payment check"] --- [Repeat for each bug...] ## Summary **Total Bugs Found**: X **Coverage of Production Issues**: Y/6 **Lines Affected**: [List line numbers] ``` --- Good luck! Remember: the bugs are real, subtle, and mirror actual production issues found in e-commerce systems. Think like the system is under load, with concurrent users, edge case inputs, and failures happening at inconvenient times.