Design a Rule-Driven Process Graph Validator

Problem Statement

You are designing a validator for a process automation engine. A process is defined as a directed graph where nodes represent tasks and edges represent dependencies. The validator must ensure that a given execution sequence of tasks satisfies two types of rules:

1. Presence Rules: A list of tasks that must appear in the execution.
2. Ordering Rules: A set of constraints defined as (TaskA, TaskB), meaning TaskA must be completed before TaskB starts.

The validator receives a process_graph (an adjacency list representation), a set of required_tasks, and a list of ordering_rules.

Implement the following interface:

def validate_process(process_graph, execution_sequence, required_tasks, ordering_rules):
    # Returns True if the execution_sequence is valid, False otherwise

Constraints

• process_graph: A dictionary mapping task IDs to lists of downstream task IDs.
• execution_sequence: A list of task IDs representing the actual order of execution.
• required_tasks: A set of strings.
• ordering_rules: A list of tuples (u, v) where u must precede v.

Example 1

• required_tasks: {'A', 'B', 'C'}
• ordering_rules: [('A', 'B'), ('B', 'C')]
• execution_sequence: ['A', 'B', 'C']
• Result: True

Example 2

• required_tasks: {'A', 'B', 'C'}
• ordering_rules: [('A', 'B')]
• execution_sequence: ['B', 'A', 'C']
• Result: False (because A must precede B).

Edge Cases

• The execution_sequence contains tasks not in the process_graph.
• The ordering_rules form a cycle (which should fail validation).
• The execution_sequence omits a required task.