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Referring to solution programs written by other users is helpful for learnersin programming education. However, current online judge systems just list allsolution programs submitted by users for references, and the programs aresorted based on the submission date and time, execution time, or user rating,ignoring to what extent the programs can be helpful to be referenced. Inaddition, users struggle to refer to a variety of solution approaches sincethere are too many duplicated and near-duplicated programs. To motivatelearners to refer to various solutions to learn better solution approaches, inthis paper, we propose an approach to deduplicate and rank common solutionprograms in each programming problem. Inspired by the nature that themany-duplicated program adopts a more common approach and can be a generalreference, we remove the near-duplicated solution programs and rank the uniqueprograms based on the duplicate count. The experiments on the solution programssubmitted to a real-world online judge system demonstrate that the number ofprograms is reduced by 60.20%, whereas the baseline only reduces by 29.59%after the deduplication, meaning that users only need to refer to 39.80% ofprograms on average. Furthermore, our analysis shows that top-10 rankedprograms cover 29.95% of programs on average, indicating that users can grasp29.95% of solution approaches by referring to only 10 programs. The proposedapproach shows the potential of reducing the learners' burden of referring totoo many solutions and motivating them to learn a variety of solutionapproaches.

Deduplicating and Ranking Solution Programs for Suggesting Reference Solutions