Computational Algorithm Analysis – Research Paper Algorithm
This individual coursework for the Computational Algorithms and Paradigms module requires students to thoroughly analyse a computational algorithm proposed in a research paper selected from the list of research papers provided on Canvas. The purpose of the assessment is to develop students' ability to understand, explain and critically evaluate computational algorithms presented in academic research. Students must first identify and describe the computational problem addressed by the selected research paper and clearly state the research questions investigated by the authors. They must then extract the main computational algorithm proposed in the paper and present it in pseudocode. The assessment also requires students to clearly identify the inputs required by the algorithm and the outputs produced by it. The coursework consists of six main analytical sections. The first section focuses on the computational problem and research questions addressed in the selected paper. Students are expected to provide an accurate description of the problem and explain the research questions that the proposed algorithm attempts to address. The second section requires the proposed computational algorithm to be represented using suitable pseudocode. The third section identifies and explains the algorithm's inputs and outputs. The fourth section requires students to explain the proposed algorithm using simple and understandable language. The explanation should demonstrate a clear understanding of how the algorithm operates rather than simply reproducing the description provided in the research paper. The fifth section focuses on analysing the time complexity of the proposed algorithm. Students should evaluate the computational cost of the algorithm and explain its time complexity appropriately. The final section requires a critical evaluation of the algorithm's strengths and weaknesses. Students should identify the advantages and limitations of the proposed approach and discuss potential improvements where appropriate. This section should demonstrate critical thinking about the effectiveness, efficiency and practical applicability of the algorithm. The coursework has a total word count requirement of 800–1,000 words. The inputs and outputs, pseudocode and time-complexity analysis sections are excluded from this word-count limit. The template requires approximately 250 words for the computational problem and research questions, approximately 250 words for the simple explanation of the algorithm, and approximately 300 words for the strengths and weaknesses evaluation. Students must report the word count for sections 1, 4 and 6 after completing the assignment. The submitted work must be original and is subject to plagiarism and collusion checks through Turnitin. The assessment brief also states that generative AI tools may be used for proofreading but are not permitted for creating the coursework content. No figures or images are permitted, and the coursework must be submitted using the provided Word template in DOC or DOCX format.
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