--- license: bsd task_categories: - text-classification #task_ids: #- binary-classification --- dataset_info: features: - name: Binary dtype: string - name: Addr dtype: string - name: Name dtype: string - name: Type dtype: class_label: names: '0': func '1': method - name: Disassembly dtype: string config_name: ejschwartz--oo-method-test splits: - name: combined num_bytes: 3560837643 num_examples: 1471458 download_size: 1001202060 dataset_size: 3560837643 train-eval-index: - config: default # The dataset config name to use. Example for datasets without configs: default. Example for glue: sst2 task: text-classification # The task category name (same as task_category). Example: question-answering task_id: binary_classification # The AutoTrain task id. Example: extractive_question_answering splits: #train_split: train # The split to use for training. Example: train eval_split: train # The split to use for evaluation. Example: test col_mapping: # The columns mapping needed to configure the task_id. # Example for extractive_question_answering: # question: question # context: context # answers: # text: text # answer_start: answer_start Disassembly: text Type: target metrics: - type: accuracy # The metric id. Example: wer. Use metric id from https://hf.co/metrics name: accuracy # Tne metric name to be displayed. Example: Test WER --- # Dataset Card for OO Method Test Dataset ## Dataset Description ### Dataset Summary This dataset describes compiled functions in various [small, simple C++ programs](https://github.com/sei-eschwartz/buildexes/tree/master/tests/src/oo). These programs were automatically compiled using various versions of Microsoft's Visual C++ compiler and different compilation settings. The details can be found in the [BuildExes](https://github.com/sei-eschwartz/buildexes) repository. For each function, the dataset includes a disassembled (using ROSE's `bat-dis` tool) representation of the compiled code, its name, and whether the function is a OO method or not. **This dataset is largely intended for @ejschwartz to experiment with learning techniques and tools. The programs are artificial and are likely not representative of real programs.** ### Supported Tasks and Leaderboards [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed]