Angular Component Dependency Tracking and Affected Detection

Angular's change detection mechanism can be optimized by only updating components that are actually affected by changes. This challenge asks you to implement a simplified version of affected detection, focusing on tracking component dependencies and determining which components need to be re-rendered when data changes. This is a crucial optimization technique for large Angular applications, improving performance and responsiveness.

Problem Description

You are tasked with creating a utility function that analyzes a component's input properties and determines which other components are affected by a change to a specific input property. The input properties are represented as a map where the key is the property name (string) and the value is the type of the property (string). You'll also be given a dependency graph, represented as a map where the key is a component name (string) and the value is an array of strings representing the names of components that this component depends on.

The function should take the component name (string), the input properties map, and the dependency graph as input. It should return an array of component names that are affected by a change to any of the input properties. If a component has no input properties or is not present in the dependency graph, it should return an empty array.

Key Requirements:

• Dependency Tracking: The function must traverse the dependency graph to identify all components that depend on the input component.
• Input Property Awareness: The function should only consider components that have the specified input properties.
• Recursive Traversal: The dependency graph may contain nested dependencies, so the function must recursively traverse the graph.
• No Circular Dependencies: The function should handle circular dependencies gracefully (avoid infinite loops).

Expected Behavior:

The function should return an array of component names, sorted alphabetically. The array should only contain components that are directly or indirectly dependent on the input component and have at least one of the specified input properties.

Edge Cases to Consider:

• Component not found in the dependency graph.
• Component has no input properties.
• Circular dependencies in the dependency graph.
• Empty dependency graph.
• Empty input properties map.

Examples

Example 1:

Input: componentName = "ComponentA", inputProperties = {"data": "number"}, dependencyGraph = {
    "ComponentA": ["ComponentB"],
    "ComponentB": ["ComponentC"],
    "ComponentC": []
}
Output: ["ComponentB", "ComponentC"]
Explanation: ComponentA depends on ComponentB, and ComponentB depends on ComponentC. All three components have the "data" property.

Example 2:

Input: componentName = "ComponentA", inputProperties = {"data": "number"}, dependencyGraph = {
    "ComponentA": ["ComponentB", "ComponentD"],
    "ComponentB": ["ComponentC"],
    "ComponentC": [],
    "ComponentD": []
}
Output: ["ComponentB", "ComponentC", "ComponentD"]
Explanation: ComponentA depends on ComponentB and ComponentD. ComponentB depends on ComponentC. ComponentB and ComponentC have the "data" property. ComponentD also has the "data" property.

Example 3: (Edge Case - Circular Dependency)

Input: componentName = "ComponentA", inputProperties = {"data": "number"}, dependencyGraph = {
    "ComponentA": ["ComponentB"],
    "ComponentB": ["ComponentA"]
}
Output: ["ComponentA", "ComponentB"]
Explanation: ComponentA depends on ComponentB, and ComponentB depends on ComponentA. Both have the "data" property. The function should detect the circular dependency and avoid an infinite loop.

Example 4: (Edge Case - No Input Properties)

Input: componentName = "ComponentA", inputProperties = {}, dependencyGraph = {
    "ComponentA": ["ComponentB"],
    "ComponentB": []
}
Output: []
Explanation: ComponentA has no input properties, so no components are affected.

Constraints

• componentName will be a non-empty string.
• inputProperties will be a map with string keys and string values.
• dependencyGraph will be a map with string keys and array of string values.
• Component names in dependencyGraph will be strings.
• The function must complete within a reasonable time (e.g., less than 1 second) for graphs with up to 100 components.
• The returned array of component names must be sorted alphabetically.

Notes

• Consider using a Set to keep track of visited components to prevent infinite loops in case of circular dependencies.
• The inputProperties map represents the expected properties of the affected components. You don't need to verify that the components actually have those properties, only that they are listed in the map.
• Focus on the core logic of dependency traversal and affected component identification. Error handling (e.g., for invalid input) is not required for this challenge.
• The goal is to efficiently identify the components that could be affected by a change, not to determine if they will be affected.