Analyzes one .NET project to plan integration tests for an Oracle-to-PostgreSQL migration. Identifies database access methods, prioritizes migration risks, and documents test cases, seed data, and coverage, including empty strings, NULL values, and timezone behavior.
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Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation.
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Analyze a single target project to identify data access artifacts that require integration testing, then produce a structured, actionable testing plan.
Progress:
- [ ] Step 1: Identify data access artifacts
- [ ] Step 2: Classify testing priorities
- [ ] Step 3: Write the testing plan
Step 1: Identify data access artifacts
Scope to the target project only. Find classes and methods that interact directly with the database — repositories, DAOs, stored procedure callers, service layers performing CRUD operations.
Step 2: Classify testing priorities
Rank artifacts by migration risk. Prioritize methods that use Oracle-specific features (refcursors, TO_CHAR, implicit type coercion, NO_DATA_FOUND) over simple CRUD.
Step 3: Write the testing plan
Write a markdown plan covering:
When defining recommended test cases, explicitly include:
NULL/missing values.timestamp without time zone or timestamp(0), with explicit timezone-application expectations.Write the plan to: .github/oracle-to-postgres-migration/Reports/{TARGET_PROJECT} Integration Testing Plan.md
MyApp.Postgres), so each instance targets one database.还没有评价。欢迎分享你的使用感受。
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Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.
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Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.
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Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
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Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.
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Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.
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Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.
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