Structure Chart:

The top-level module is 'Grade Processor'. It orchestrates the grade processing tasks.

Level 1:

• Grade Processor: The main module.
• Grade Analysis: Performs calculations and identifies passing grades.
• Report Generation: Creates the summary report.

Level 2:

• Grade Analysis:

  • Calculate Average Grade: Takes a list of grades as input. Parameters: grades (a list of floats). Returns: average_grade (a float).
  • Identify Passing Students: Takes a list of grades and the passing grade threshold as input. Parameters: grades (a list of floats), passinggrade (a float). Returns: passingstudents (a list of student names who have passed).

• Report Generation:

  • Format Report: Takes the average grade and list of passing students as input. Parameters: averagegrade (a float), passingstudents (a list of student names). Returns: report_string (a string).
  • Output Report: Takes the formatted report string as input. Parameters: report_string (a string). Returns: None.

Relationships:

Deterministic State-Transition Diagram: In a deterministic state-transition diagram, for each state and transition, there is exactly one possible next state. Given a particular state and a specific event, the next state is uniquely determined. This is the most common type of state-transition diagram used in practice.

Non-Deterministic State-Transition Diagram: In a non-deterministic state-transition diagram, for a given state and event, there may be multiple possible next states. This indicates that the algorithm can proceed in different ways depending on the conditions. This is less common and often used to model algorithms with inherent uncertainty or parallel execution.

Example Scenario: Consider a simple game of chance. A non-deterministic state-transition diagram could represent the states of a game where the outcome of a dice roll determines the next state. For example, a state could be 'WaitingForRoll', and transitions could lead to states like 'Win', 'Lose', or 'RollAgain', each with a certain probability. The non-determinism arises from the random nature of the dice roll.

Challenges with Non-Deterministic Diagrams:

• Complexity: Non-deterministic diagrams can become very complex quickly, especially if there are many possible outcomes.
• Verification: Verifying the correctness of a non-deterministic algorithm can be challenging. It's difficult to prove that the algorithm will always reach a desired outcome because there are multiple possible paths.
• Implementation: Implementing a non-deterministic algorithm in a traditional sequential programming language can be difficult and may require the use of techniques like recursion or switch statements, which can be less efficient.
• Limited Applicability: Non-determinism is not suitable for all algorithms. It's primarily used for modeling scenarios where randomness or multiple possible outcomes are inherent to the process.

While non-deterministic diagrams can be useful for modeling certain types of algorithms, their complexity and the challenges associated with verification and implementation often make deterministic diagrams a more practical choice for most applications.

The key components of a state-transition diagram are:

• States: Represented by circles or ovals. Each state represents a distinct condition or stage in the algorithm.
• Transitions: Represented by arrows connecting states. Each arrow indicates a transition from one state to another, triggered by a specific event or condition.
• Initial State: Indicated by a filled-in circle. This is the state the algorithm starts in.
• Final State(s): Indicated by a double-filled-in circle. This represents the state the algorithm reaches upon completion. An algorithm can have multiple final states, representing different successful outcomes.
• Events/Triggers: Labels on the transitions that specify the event or condition that causes the transition to occur.

Example: Consider modeling a simple traffic light system.

This diagram clearly shows the sequence of states and the events that trigger the transitions, making the traffic light logic easy to understand.