PASO (PArser for SOlidity)

An online Parser for Solidity language Analysis

Requires Node >= v11.3.0

Usage

Web tool

https://aphd.github.io/paso/

https://github.com/aphd/paso/settings/pages

Website deployment

npm install
npm start

CLI tool

node --experimental-modules src/services/client.mjs --d=src/fixtures/smart-contracts/ --o /tmp/metrics.csv

Data analysis

cd src/fixtures
python

import pandas as pd
df = pd.read_csv('src/fixtures/metrics.csv', \
    parse_dates=['submission_date'],  index_col='submission_date')
df[['mapping', 'total_lines', 'interfaces', 'libraries']] \
    .resample('Y').mean() \
    .transform(lambda x: x/x.max())

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import pylab as plot

df = pd.read_csv('src/fixtures/metrics.csv', \
    parse_dates=['submission_date'],  index_col='submission_date')
df.index = df.index.strftime('%Y')
df = df.loc[df.index > '2015']
ax = df[['interfaces', 'libraries', 'contracts']] \
    .groupby(df.index).mean() \
    .plot(kind = 'bar', figsize=(40,20)) 
for p in ax.patches:
    ax.annotate(str(round(p.get_height(),2)), (p.get_x() * 1.005, p.get_height() * 1.005), fontsize=40)

import pandas as pd

df = pd.read_csv('src/fixtures/metrics.csv', \
    parse_dates=['submission_date'],  index_col='submission_date')

df.index = df.index.strftime('%Y')

df = df.loc[df.index > '2016']

df[['mapping', 'total_lines', 'interfaces', 'libraries', 'modifiers']] \
    .groupby(df.index).mean().apply(lambda x: x / max(x)) \
    .plot(kind = 'bar', figsize=(40,20)) 

import pandas as pd

df = pd.read_csv('src/fixtures/metrics.csv')

df.replace({'submission_date': r'^(201\d).*$'}, {'submission_date': r'\1'}, \
    regex=True, inplace=True )
df.loc[df.submission_date > '2016', \
    ['submission_date', 'mapping', 'total_lines', 'interfaces', 'libraries', 'modifiers']] \
    .groupby(df['submission_date']).mean() \
    .apply(lambda x: x / max(x)) \
    .plot(kind = 'bar', figsize=(40,20)) 

print(df.describe().transpose().round(1).to_latex())

Data analysis - plots

import pandas as pd
df = pd.read_csv('./metrics.csv')
udf = df.drop_duplicates(subset=['address'])
%matplotlib inline

udf[udf['version'].str.contains("0.5")==True]['functions'][udf['functions']<100].plot.kde()

df[df['version'].str.contains("0.4")==True].hist(column='functions', bins=20, range=(0, 100))

References

1. This project was bootstrapped with Create React App.
2. This project is using a solidity parser built on top of a ANTLR4 grammar.