<p>Many code similarity detection techniques have been developed to maintain academic integrity in programming. However, most of them assume that the student programs are locally available, and the computation can be run on any computer specification. Further, their comparison in raising suspicion is time-consuming as the student programs are pairwise compared to one another. This paper proposes a scalable code similarity detection with online architecture and focused comparison. The former enables student programs shared among lecturers and guarantees that the computation is runnable. The latter shortens the execution time as only some students are considered, with inclusion criteria determined by the lecturers. To boost up the scalability, the similarity algorithm is cosine correlation, which computation is linear time. Our evaluation shows that focused comparison leads to fewer comparisons and cosine correlation leads to shorter execution time.</p>

Background: Most source code plagiarism detection tools are not modifiable. Consequently, when a modification is required to be applied, a new detection tool should be created along with it. This could be a problem as creating the tool from scratch is time-inefficient while most of the features are similar across source code plagiarism detection tools.Objective: To alleviate researchers' effort, this paper proposes a library for observing two plagiarism-suspected codes (a feature which is similar across most source code plagiarism detection tools).Methods: Unique to this library, it is not constrained by the selected programming language for development. It is executed from command line, which is supported by most programming languages.Results: According to our evaluation, the library is integrable and functional. Moreover, the library can enhance teaching assistants' accuracy and reduce the tasks' completion time.Conclusion: The library can be beneficial for the development of source code plagiarism detection tools since it is integrable, functional, and helpful for teaching assistants.Keywords:Language independency, Plagiarism detection, Reusable library, Source code, Tool development