# Unit 19 Data Structures and Algorithms - BTEC Higher National Diploma (HND) in Computing Examine abstract data types, concrete data structures, and algorithms

Unit 19 Data Structures and Algorithms - BTEC Higher National Diploma (HND) in Computing

Learning Outcome 1: Explore abstract data types, concrete data structures, and algorithms Learning Outcome 2: Specify abstract data types and algorithms using formal notation Learning Outcome 3: Implement advanced data structures and algorithms Learning Outcome 4: Evaluate the effectiveness of data structures and algorithms

Assignment Objective:

This coursework aims to demonstrate comprehensive understanding and knowledge of the module, assessing the student`s analytical strength across four key sections. The coursework is to be submitted as a single document in a report format.

Assignment Scenario:

Data structures are essential for efficient management of large datasets, particularly in contexts like large databases and internet indexing services. Effective data structures play a crucial role in designing efficient algorithms. Some formal design methodologies and programming languages prioritize data structures as the foundational element in software design over algorithms. Data structures enable organized storage and retrieval of information in both primary and secondary memory. While primitive data structures like int, float, and char represent basic values, non-primitive data structures such as arrays, lists, stacks, and trees are essential for managing complex data. Object-oriented languages like C# and Java use classes as data structures to facilitate easy replication of attributes and functions.

1. Data Structure Design Specification:

• Define valid operations for three specific data structures.
• Illustrate the use of stacks for implementing function calls and queues for "First in First out" (FIFO) operations.
2. Sorting Algorithm Comparison:

• Compare the performance of two sorting algorithms commonly used in various applications.
3. Graph Theory Exploration:

• Analyze shortest path algorithms like Bellman Ford, Dijkstra, and Floyd-Warshall within the context of graph theory.
4. Stacks and Object-Oriented Programming (OOP) Analysis:

• Investigate the advantages of encapsulation and information hiding in Abstract Data Types (ADTs).
• Explain why imperative ADTs serve as a foundation for object orientation.
5. Console-based Application Development:

• Develop a console-based application to manage student information and course details.
• Implement custom data structures using Array, List, or Linked List.
• Utilize encapsulation, inheritance, and polymorphism in the application design.
6. Implementation and Evaluation:

• Integrate error-handling mechanisms into the programming code.
• Provide screenshots and test cases to demonstrate the application`s functionality.
• Critically evaluate the complexity of implemented ADTs and algorithms.

Conclusion and Evaluation:

Assess the efficiency of developed applications using asymptotic analysis, demonstrating understanding of algorithmic complexity. Explore trade-offs between time and space efficiency with practical examples from the application code. Finally, highlight the benefits of implementing independent data structures to enhance application performance and maintainability.