On completion of this module, students should be able to:

• Explain standard algorithmic methods, algorithm efficiency, algorithm complexity and the ability to apply these.
• Explain the nature of computationally intractable problems and the role of heuristics.
• Demonstrate improved analytical thinking and problem-solving skills.
• Explain the interaction between low- and high-level software and hardware and knowledge of the architecture of a typical RISK processor at the conventional machine level.
• Explain the limitations and bottlenecks in modern processors and how hardware components and their interconnection affect the performance of a computer.

Algorithms, and Complexity

• Recursion, searches, and traversal, divide and conquer, greedy algorithms, dynamic programming.
• Program correctness; primitive recursive functions, mu- recursive functions, partial functions, Church-Turing thesis, time complexity of algorithms, average-case complexity.
• Classes P and NP, reducibility, NP-completeness, decidability, certificates.
• Probabilistic algorithms. Architecture
• System buses.
• Internal memory and external storage.
• Input/Output.
• Instruction sets.
• Operands and operations.
• Addressing modes and formats.
• Processor and register organization.

Continuous Assessment (CA): 50%

Final Assessment (FA): 50%