Datasets:
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---
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] |