Dataset assetOpen Source CommunityGait AnalysisCode Clone Detection

CodeNet

The CodeNet dataset was created by the Graduate School of Informatics at Nagoya University and is primarily used to evaluate multilingual code clone detectors. It contains code from two online judge systems (AIZU OJ and AtCoder) in Java, Python, C, and C++. The dataset selects 12 sub‑datasets to reflect edit‑distance similarity ranges targeted by clone detectors, aiming to assess detector correctness. CodeNet is applied in software engineering for code clone detection, addressing limitations of existing detectors in language extensibility and detection performance.

Source

arXiv

Created

Sep 10, 2024

Updated

Sep 10, 2024

Signals

244 views

Availability

Linked source ready

Overview

Dataset description and usage context

MCCD_Benchmarking Dataset Overview

Dataset Download

URL: https://www.dropbox.com/scl/fi/lezo5ul15qg6oudud82fx/RecallBenchmarking.zip?rlkey=pm5grsfq314s2cuw3bbdcm84l&dl=0
Contents after extraction: Two folders benchmark-data and simi-source, to be placed under MCCD_Benchmarking/recall/.

Dataset Usage

Execute Clone Detection

Subset identifiers: "p02263", "p00048", "p00001", "p00000", "p02269", "p02256", "p02257", "p02265", "p00002", "p00003", "p00008", "p00050", "p02271", "p00005"
Result file naming: Language_problemId.csv
File format: Each line represents a clone pair, formatted as "segment1 file path, segment1 start line, segment1 endline, segment2 file path, segment2 start line, segment2 endline"

Add Target Tool

Command: python3 AddDetector.py ToolName
Parameter: ToolName is the identifier of the target clone detector

Import Detection Results

Command: python3 ImportClones.py ToolName ResultFolder [Language+]
Parameters:
- ToolName: tool identifier
- ResultFolder: path to the folder containing results for each subset
- Language: optionally list target languages to import

Evaluation

Command: python3 Evaluation.py [ToolName]
Parameter: ToolName is the tool identifier; if omitted, all registered tools are evaluated

Output All Results

Command: python3 GroupedData.py

Remove Tool or Clone

Command: python3 CloneClones.py ToolName
Parameter: ToolName is the tool identifier
Command: python3 RemoveDetector.py ToolName
Parameter: ToolName is the tool identifier

Dataset Characteristics

Recall: Provided
Precision: To be provided

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