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@@ -48,7 +48,7 @@ In light of these issues, we have extracted several benchmark datasets from Code
 
 ### Potential use cases
 
-The rich metadata and diversity open Project CodeNet to a plethora of uses cases. The problem-submission relationship in Project CodeNet corresponds to type-4 similarity and can be used for code search and clone detection. The code samples in Project CodeNet are labeled with their acceptance status and we can explore AI techniques to distinguish correct codes from problematic ones. Project CodeNet's metadata also enables the tracking of how a submission evolves from problematic to accepted, which could be used for exploring automatic code correction. Each code sample is labeled with CPU run time and  memory footprint, which can be used for regression studies and prediction. Given  its wealth of programs written in a multitude of languages, Project CodeNet may serve as a valuable benchmark dataset for source-to-source translation.
+The rich metadata and diversity open Project CodeNet to a plethora of uses cases. The problem-submission relationship in Project CodeNet corresponds to [type-4 similarity](https://escholarship.org/uc/item/45r2308g) and can be used for code search and clone detection. The code samples in Project CodeNet are labeled with their acceptance status and we can explore AI techniques to distinguish correct codes from problematic ones. Project CodeNet's metadata also enables the tracking of how a submission evolves from problematic to accepted, which could be used for exploring automatic code correction. Each code sample is labeled with CPU run time and  memory footprint, which can be used for regression studies and prediction. Given  its wealth of programs written in a multitude of languages, Project CodeNet may serve as a valuable benchmark dataset for source-to-source translation.
 
 ### Usability