Cross-Module Integration Testing: Having all components in one place allows for seamless integration tests across different modules, ensuring compatibility between underlying components.

Lack of Flexible Release: If one component needs to be released independently, it might be challenging to decouple its release process from the rest of the repository.

Merge Conflicts: With multiple teams working on the same library, the likelihood of merge conflicts increases, especially if there are many simultaneous feature branches.

Increased Build and Test Times: Even if a small part of the codebase changes, the entire repository might need to be built and tested. This can slow down development cycles, especially as more modules are added.

Repository Size and Complexity: As the number components grows, the repository may become large and complex, making it harder to navigate and manage. Cloning, searching, and building may become slower over time.

Independent Release Cycles: Each library can follow its own release schedule, which is beneficial when some libraries evolve faster than others.

Easier Repository Navigation: With smaller libraries, developers and contributors can easily navigate the codebase relevant to their task, making the development process more manageable for newcomers.

Reduced Risk of Merge Conflicts: Since each library is managed separately, developers working in different repositories will not face merge conflicts due to changes in unrelated codebases.

Use What You Need: Developers can choose to use only the libraries they need, reducing the cognitive load and dependencies for projects that do not require the full suite of components.

Potential Duplication: Similar functionality may be duplicated across libraries, especially when different teams manage different components, leading to inconsistencies and redundant work.

Well-established: Lerna has been widely adopted, with strong community support and a rich ecosystem of plugins and extensions.

Dependency Hoisting: Shared dependencies can be hoisted to the root level of the monorepo, minimizing duplication and ensuring consistency across packages.

Independent Versioning: Supports both independent versioning of packages and fixed (locked) versioning for more controlled releases.

Automatic Package Linking: Local packages are automatically linked, which makes cross-package development straightforward without manually managing npm link.

Automated Release Workflow: Lerna provides tools for automated release management, including changelog generation and publishing to npm.

No Built-in Build Optimization: Lerna focuses primarily on versioning and managing packages. It does not include build caching or task orchestration, which are important for optimizing large monorepos.

Scaling Limitations: As the number of packages grows, Lerna’s performance can degrade without additional tools for build performance.

Requires Additional Tools: Lerna doesn’t provide advanced task running or build optimization, so additional scripts or tools (e.g., Webpack, Babel) are often needed.

Advanced Build Caching: Nx caches the results of previous builds and only rebuilds packages when necessary, leading to significant performance improvements.

Dependency Graph Visualization: Nx automatically generates a dependency graph that shows how different packages interact, helping developers manage dependencies effectively.

Task Orchestration: Nx intelligently runs build, test, and lint tasks in the correct order, based on package dependencies, and only when needed.

Language Agnostic: Nx supports not only JavaScript/TypeScript but also other languages, which is helpful if the monorepo eventually incorporates non-JS packages (e.g., Rust, Go).

Scalable for Large Monorepos: Nx is designed to handle the needs of large monorepos, making it suitable for complex projects with many interdependent packages.

Learning Curve: Nx has a more complex setup and configuration than simpler tools like Lerna, especially around caching and task orchestration.

Overhead: For smaller projects, Nx’s comprehensive features may introduce unnecessary complexity.

Complexity: As the monorepo grows, managing Nx’s configuration files and workflows for different environments and tools can become complicated.

Fast Build Caching: Turborepo offers a robust caching system that prevents rebuilding or retesting packages unless absolutely necessary, improving build performance.

Minimal Setup: Turborepo integrates smoothly with existing build systems and requires minimal configuration, making it easy to adopt.

Task Orchestration: Turborepo runs tasks in parallel and in the correct order based on package dependencies, ensuring fast and correct builds and tests.

Modern Tooling Integration: Turborepo works well with other modern JavaScript/TypeScript tools like Webpack, Babel, and TypeScript, providing a good balance of flexibility and performance.

Newer Tool: As a newer tool, Turborepo does not have the same level of community support and ecosystem maturity as Lerna or Nx.

Less Comprehensive Feature Set: Turborepo is primarily focused on build performance and doesn’t offer many project management features (e.g., dependency graphs, testing utilities).

Focused on JavaScript/TypeScript: Turborepo is optimized for JavaScript/TypeScript projects, which could limit its applicability if non-JS packages are added to the monorepo in the future.

Lack of Built-in Testing and Linting: Unlike Nx, Turborepo does not come with built-in support for testing or linting, requiring additional setup for those workflows.

Built-in Package Linking: Yarn Workspaces automatically links local packages, making it easy to develop multiple interdependent packages without needing external tools.

Simplicity: Yarn Workspaces is relatively simple to set up and integrates directly with Yarn, requiring no additional tooling beyond a package.json configuration.

Centralized Dependency Management: Dependencies are installed once at the root level and shared among all packages, reducing redundancy and potential version conflicts.

Lightweight Solution: For smaller monorepos, Yarn Workspaces offers an elegant and lightweight approach to managing multiple packages without the overhead of more complex tools like Nx or Lerna.

Minimal Configuration: Yarn Workspaces is configured directly in the package.json file, which simplifies repository management without needing additional configuration files.

No Built-in Task Runner: Yarn Workspaces only handles package linking and dependency management. It doesn’t provide a task runner for building, testing, or linting across packages.

No Advanced Build Caching: Unlike Nx or Turborepo, Yarn Workspaces does not provide advanced build caching or task orchestration, which can lead to longer build times as the monorepo grows.

Requires Additional Tooling: To handle tasks like building, testing, and deployment, additional scripts or tools (e.g., npm/yarn scripts, Webpack) are required.

Limited Dependency Management: Yarn Workspaces lacks advanced features like dependency graph visualization or fine-grained control over package relationships, making it harder to manage complex interdependencies in larger monorepos.

Description: Continue maintaining the BDD test suite within the existing DID-SDK repository.

Pros: Code proximity; no new repository setup required.

Cons: Competition for resources; unclear separation of concerns; impedes independent maintenance; tightly coupled CI/CD; necessitates mixed skillsets.

Description: Migrate the BDD test suite to a dedicated, independent repository.

Pros: Enables independent development and release cycles; facilitates dedicated resource allocation; promotes improved maintainability and organization; establishes clear ownership; increases potential for reuse by other projects; allows for an independent, optimized CI/CD pipeline.

Cons: Introduces repository management overhead; requires careful synchronization with SDK changes; necessitates an initial migration effort.

Description: Abandon the current BDD test suite and explore alternative testing approaches.

Pros: Avoids further investment in the current, flawed implementation; allows exclusive focus on core SDK development.

Cons: Loss of the potential benefits of a language-agnostic BDD test suite; increased risk of regressions without a comprehensive alternative; forfeits the initial investment in the BDD suite.