▸case-09 We are building an order fulfillment pipeline that executes inventory reservation, payment charging, and shipping notification over several minutes. We want to avoid setting up a complex dedicated messaging broker cluster or manual retry queues just to guarantee crash recovery. How should we structure this execution? | pass→pass | 14,990 | 13,675 | -9% | 1 | 1 | 0% | 2,514 | 3,011 | +20% | 0 | 0 | — |
▸case-10 We have a large monolithic backend and want to decompose it into microservices. Our engineers want to start by breaking out services based on existing database tables (`users_table`, `orders_table`, `items_table`). How should service boundaries actually be determined? | pass→pass | 14,384 | 14,872 | +3% | 1 | 1 | 0% | 2,471 | 2,927 | +18% | 0 | 0 | — |
▸case-01 We are breaking down a legacy monolithic e-commerce system to improve maintainability and testability. Could you analyze our domain, recommend a suitable backend structural model, and map out the module boundaries and dependency rules? | fail→pass | 17,643 | 19,785 | +12% | 1 | 1 | 0% | 3,126 | 4,064 | +30% | 0 | 0 | — |
▸case-02 I am designing a new backend service that processes multi-step payment and order fulfillment workflows which cannot afford to lose state on failure. Please outline the overall architecture, interface boundaries, and a strategy for handling durable workflow execution during system crashes. | pass→pass | 17,246 | 17,985 | +4% | 1 | 1 | 0% | 3,004 | 3,924 | +31% | 0 | 0 | — |
▸case-03 Our engineering team needs to transition our tightly coupled codebase into a decoupled architecture. Please produce an architectural plan that defines module interfaces, dependency flow, a step-by-step migration path, and verification checks to ensure success. | fail→pass | 17,374 | 19,428 | +12% | 1 | 1 | 0% | 3,026 | 3,999 | +32% | 0 | 0 | — |
▸case-04 I have a single 15-line helper function in Python that formats user dates and strings. It has a nested if-statement that I want to clean up. How should I rewrite this function? | fail→pass | 8,276 | 6,159 | -26% | 1 | 1 | 0% | 1,613 | 1,557 | -3% | 0 | 0 | — |
▸case-05 Our PostgreSQL database query for fetching active user subscriptions with `SELECT * FROM subscriptions WHERE status = 'active'` is running slowly. How should we write an index and optimize this specific SQL query? | pass→pass | 11,791 | 10,499 | -11% | 1 | 1 | 0% | 2,288 | 2,292 | +0% | 0 | 0 | — |
▸case-06 We are building a React application and need to pass user authentication tokens down to a deeply nested component tree without prop drilling. How should we handle this in React? | pass→pass | 10,361 | 7,123 | -31% | 1 | 1 | 0% | 2,087 | 1,721 | -18% | 0 | 0 | — |
▸case-07 We are building a financial ledger with strict audit trails and complex accounting rules. The team is considering whether to use a basic CRUD model or Clean/Hexagonal Architecture with Domain-Driven Design. What structural model should we adopt? | pass→pass | 16,248 | 16,922 | +4% | 1 | 1 | 0% | 2,819 | 3,556 | +26% | 0 | 0 | — |
▸case-08 In our payment processing system, our core business logic directly imports database driver packages and third-party Stripe SDKs. Is this dependency structure sound, or how should dependencies flow between core logic and external services? | pass→pass | 16,437 | 14,376 | -13% | 1 | 1 | 0% | 2,871 | 2,880 | +0% | 0 | 0 | — |
▸case-11 We are refactoring our backend service from a monolithic controller-service-repository pattern into a Hexagonal Architecture. What validation checks should we put in place to ensure our domain core remains isolated during migration? | pass→pass | 16,767 | 13,480 | -20% | 1 | 1 | 0% | 2,558 | 2,573 | +1% | 0 | 0 | — |
▸case-12 In our healthcare application, both the Scheduling module and the Billing module refer to a 'Patient', but they require different fields and validation rules. Should we create a single shared `Patient` database model class used by both modules? | pass→pass | 11,925 | 9,444 | -21% | 1 | 1 | 0% | 1,971 | 2,020 | +2% | 0 | 0 | — |
▸case-13 Our team has a tightly coupled Node.js monolith where controllers directly query the database. We want to migrate to Clean Architecture without halting feature delivery. What phased migration plan should we follow? | pass→pass | 17,961 | 16,847 | -6% | 1 | 1 | 0% | 3,127 | 3,607 | +15% | 0 | 0 | — |
▸case-14 We have a user onboarding workflow that sends a verification email, provisions a cloud environment, and initializes default tenant data. If the server restarts halfway through step two, the process fails silently. How can we ensure automatic recovery without writing state-machine boilerplate? | pass→pass | 11,178 | 13,747 | +23% | 1 | 1 | 0% | 1,995 | 2,786 | +40% | 0 | 0 | — |
▸case-15 We currently send emails directly using the SendGrid API inside our core checkout code. We want to be able to switch to AWS SES or a mock emailer during integration testing without modifying core checkout logic. How should we structure this module? | pass→pass | 13,688 | 13,036 | -5% | 1 | 1 | 0% | 3,082 | 3,243 | +5% | 0 | 0 | — |
▸case-16 We are starting a new logistics tracking project. The lead developer wants to pick MongoDB and Kafka immediately before evaluating the business domain requirements. What process should we follow when designing this new system? | pass→pass | 14,773 | 14,245 | -4% | 1 | 1 | 0% | 2,451 | 2,593 | +6% | 0 | 0 | — |
▸case-17 In our e-commerce domain, we need to handle customer delivery addresses. Should an address be treated as an Entity with a unique database primary key ID or as a Value Object defined solely by its attribute values? | pass→pass | 15,176 | 12,756 | -16% | 1 | 1 | 0% | 2,760 | 2,656 | -4% | 0 | 0 | — |
▸case-18 When a customer requests a refund, our system calls a payment gateway, updates account balances, and revokes license keys. If a crash occurs during balance update, refund state is corrupted. How should this multi-step payment workflow be handled to guarantee state recovery without adding heavy architectural complexity? | fail→fail | 15,030 | 12,895 | -14% | 1 | 1 | 0% | 2,587 | 2,737 | +6% | 0 | 0 | — |
▸case-19 Our domain classes are pure data structures with only getters and setters, while all business validation logic resides in huge service classes. Is this an effective domain design? | pass→pass | 13,189 | 14,923 | +13% | 1 | 1 | 0% | 2,261 | 2,949 | +30% | 0 | 0 | — |
▸case-20 Our engineering organization is growing rapidly and PR reviews frequently dispute where new business logic and database queries should be placed. How can we establish clear architectural standards for layer separation? | pass→pass | 16,717 | 15,863 | -5% | 1 | 1 | 0% | 2,849 | 3,200 | +12% | 0 | 0 | — |
▸case-21 We spend 80% of our test execution time spinning up PostgreSQL containers just to test basic discount calculation rules in our checkout logic. How should Clean Architecture improve our test suite efficiency? | pass→pass | 13,054 | 13,907 | +7% | 1 | 1 | 0% | 2,434 | 2,777 | +14% | 0 | 0 | — |
▸case-22 We are writing a small internal CLI script that reads a CSV file and posts formatted strings to a Slack webhook once a week. Should we apply Clean Architecture with entities, use-cases, and repository interfaces? | pass→pass | 10,457 | 7,267 | -31% | 1 | 1 | 0% | 1,872 | 1,585 | -15% | 0 | 0 | — |