Contract Sizes: Comparisons EVM Vs. WASM Contract Code Sizes

Contract Code Size Comparison

The goal of this repository is to compare the sizes of compiled solidity contracts when compiled to EVM (with solc) versus WASM (with solang).

After some experimentation it turned out that a huge contributor to WASM code sizes is the smaller word size of WASM. Solidity treats 256bit variables as value types and passes them on the stack. Solang generates four 32bit stack accesses to emulate this. In order to improve comparability we do the following:

  • Patch all contracts used for comparisons to not use wide integers (use uint32 everywhere).
  • Pass --value-size 4 --address-size 4 to solang so that 32bit is usedfor the builtin types (address, msg.value).

How to use this repository

Put solang in your PATH and run compile.sh which is located in the root of this repository. The solc compiler will be downloaded automatically.

Test corpus

The current plan is to use the following sources as a test corpus:

Adding a new contract to the corpus from either of those sources is a time consuming process because solang isn't a drop in replacement. It tries hard to be one but there are some things that won't work on solang: First, almost all contracts use EVM inline assembly which obviously won't work on a compiler targeting another architecture. Second, differences in builtin types (address, balance) will prevent the compilation of most contracts.

Therefore we need to apply substantial changes to every contract before it can bea dded to the corpus in order to make it compile and establish comparability.

Results

The following results show the compressed sizes (zstd) of the evm and wasm targets together with their compression ratio. Wasm relative describes the relative size of the compressed wasm output when compared to the evm output.

The concatenated row is what we get when we concatenate the uncompressed results of all contracts.

Used solang version is commit c2a8bd9881e64e41565cdfe088ffe9464c74dae4.

ContractEVM CompressedWASM CompressedEVM RatioWASM RatioWasm Relative
UniswapV2Pair.sol3986691244%33%173%
UniswapV2Router02.sol5826921930%28%158%
ERC20PresetFixedSupply.sol2162289150%34%133%
concatenated111121739734%28%156%

Download Details:
Author: paritytech
Source Code: https://github.com/paritytech/contract-sizes
License:

#blockchain  #polkadot  #smartcontract  #substrate 

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Contract Sizes: Comparisons EVM Vs. WASM Contract Code Sizes
Tyrique  Littel

Tyrique Littel

1604008800

Static Code Analysis: What It Is? How to Use It?

Static code analysis refers to the technique of approximating the runtime behavior of a program. In other words, it is the process of predicting the output of a program without actually executing it.

Lately, however, the term “Static Code Analysis” is more commonly used to refer to one of the applications of this technique rather than the technique itself — program comprehension — understanding the program and detecting issues in it (anything from syntax errors to type mismatches, performance hogs likely bugs, security loopholes, etc.). This is the usage we’d be referring to throughout this post.

“The refinement of techniques for the prompt discovery of error serves as well as any other as a hallmark of what we mean by science.”

  • J. Robert Oppenheimer

Outline

We cover a lot of ground in this post. The aim is to build an understanding of static code analysis and to equip you with the basic theory, and the right tools so that you can write analyzers on your own.

We start our journey with laying down the essential parts of the pipeline which a compiler follows to understand what a piece of code does. We learn where to tap points in this pipeline to plug in our analyzers and extract meaningful information. In the latter half, we get our feet wet, and write four such static analyzers, completely from scratch, in Python.

Note that although the ideas here are discussed in light of Python, static code analyzers across all programming languages are carved out along similar lines. We chose Python because of the availability of an easy to use ast module, and wide adoption of the language itself.

How does it all work?

Before a computer can finally “understand” and execute a piece of code, it goes through a series of complicated transformations:

static analysis workflow

As you can see in the diagram (go ahead, zoom it!), the static analyzers feed on the output of these stages. To be able to better understand the static analysis techniques, let’s look at each of these steps in some more detail:

Scanning

The first thing that a compiler does when trying to understand a piece of code is to break it down into smaller chunks, also known as tokens. Tokens are akin to what words are in a language.

A token might consist of either a single character, like (, or literals (like integers, strings, e.g., 7Bob, etc.), or reserved keywords of that language (e.g, def in Python). Characters which do not contribute towards the semantics of a program, like trailing whitespace, comments, etc. are often discarded by the scanner.

Python provides the tokenize module in its standard library to let you play around with tokens:

Python

1

import io

2

import tokenize

3

4

code = b"color = input('Enter your favourite color: ')"

5

6

for token in tokenize.tokenize(io.BytesIO(code).readline):

7

    print(token)

Python

1

TokenInfo(type=62 (ENCODING),  string='utf-8')

2

TokenInfo(type=1  (NAME),      string='color')

3

TokenInfo(type=54 (OP),        string='=')

4

TokenInfo(type=1  (NAME),      string='input')

5

TokenInfo(type=54 (OP),        string='(')

6

TokenInfo(type=3  (STRING),    string="'Enter your favourite color: '")

7

TokenInfo(type=54 (OP),        string=')')

8

TokenInfo(type=4  (NEWLINE),   string='')

9

TokenInfo(type=0  (ENDMARKER), string='')

(Note that for the sake of readability, I’ve omitted a few columns from the result above — metadata like starting index, ending index, a copy of the line on which a token occurs, etc.)

#code quality #code review #static analysis #static code analysis #code analysis #static analysis tools #code review tips #static code analyzer #static code analysis tool #static analyzer

Samanta  Moore

Samanta Moore

1621137960

Guidelines for Java Code Reviews

Get a jump-start on your next code review session with this list.

Having another pair of eyes scan your code is always useful and helps you spot mistakes before you break production. You need not be an expert to review someone’s code. Some experience with the programming language and a review checklist should help you get started. We’ve put together a list of things you should keep in mind when you’re reviewing Java code. Read on!

1. Follow Java Code Conventions

2. Replace Imperative Code With Lambdas and Streams

3. Beware of the NullPointerException

4. Directly Assigning References From Client Code to a Field

5. Handle Exceptions With Care

#java #code quality #java tutorial #code analysis #code reviews #code review tips #code analysis tools #java tutorial for beginners #java code review

Houston  Sipes

Houston Sipes

1604088000

How to Find the Stinky Parts of Your Code (Part II)

There are more code smells. Let’s keep changing the aromas. We see several symptoms and situations that make us doubt the quality of our development. Let’s look at some possible solutions.

Most of these smells are just hints of something that might be wrong. They are not rigid rules.

This is part II. Part I can be found here.

Code Smell 06 - Too Clever Programmer

The code is difficult to read, there are tricky with names without semantics. Sometimes using language’s accidental complexity.

_Image Source: NeONBRAND on _Unsplash

Problems

  • Readability
  • Maintainability
  • Code Quality
  • Premature Optimization

Solutions

  1. Refactor the code
  2. Use better names

Examples

  • Optimized loops

Exceptions

  • Optimized code for low-level operations.

Sample Code

Wrong

function primeFactors(n){
	  var f = [],  i = 0, d = 2;  

	  for (i = 0; n >= 2; ) {
	     if(n % d == 0){
	       f[i++]=(d); 
	       n /= d;
	    }
	    else{
	      d++;
	    }     
	  }
	  return f;
	}

Right

function primeFactors(numberToFactor){
	  var factors = [], 
	      divisor = 2,
	      remainder = numberToFactor;

	  while(remainder>=2){
	    if(remainder % divisor === 0){
	       factors.push(divisor); 
	       remainder = remainder/ divisor;
	    }
	    else{
	      divisor++;
	    }     
	  }
	  return factors;
	}

Detection

Automatic detection is possible in some languages. Watch some warnings related to complexity, bad names, post increment variables, etc.

#pixel-face #code-smells #clean-code #stinky-code-parts #refactor-legacy-code #refactoring #stinky-code #common-code-smells

david harper

1610429951

Hire Smart Contract Developers | Smart Contract Development Company India

What are smart contracts?

Smart contracts is a digital code stored in a blockchain and automatically executes when predetermined terms and conditions are met. In Simple terms, they are programs that run by the setup of the people who developed them.They are designed to facilitate, verify, and execute a digital contract between two parties without the involvement of third parties.

Benefits of Smart Contracts

Greater efficiency and speed
Accuracy and transparency
Trust
Robust Security
Independent verification
Advanced data safety
Distributed ledger
Ease of use
Open source technology
Better flexibility
Easy integration
Improved tractability

Where could smart contracts be used?

Today Smart contracts are used in various platforms such as supply-chain management,cross-border financial transactions,document management,enforceability and more. Here are the Sectors where smart contracts plays a huge role ,

  • Supply chain management
  • Insurance
  • Mortgage loans
  • Financial industry
  • Trade Finance
  • Government
  • IT Sector
  • Records
  • Property ownership
  • Medical Research
  • Voting
  • Peer-to-Peer transactions
  • Product development
  • Stocktaking

Steps For Successful Smart Contract Development

There are a few Important things that you need to consider before you develop a Smart Contract,

Ask Yourself -

  • Do You Need A Smart Contract In Your Project?
  • How can i Implement Smart Contract in My Business?
  • If yes, Find out Your Business Requirements
  • Plan your Requirements
  • Find a Trustworthy Smart Contract Developer
  • Develop , Test Your Smart Contract

Ready to develop your smart contract?

I hope this blog was helpful. We think this is the right time for companies to invest in building a blockchain powered Smart Contracts as Blockchain technology and the ecosystem around it is changing fast. If you’re thinking about building a Smart Contract but not sure where to start, contact us, we’re happy to provide free suggestions about how blockchain’s Smart Contracts may fit into your business.

We Employcoder Leading IT Outsourcing Company with a team of Smart Contract Experts. Hire Smart Contract Developers from us who can code bug-free, scalable, innovative, fully-functional smart contracts for your business and make your business or enterprise eye-catchy & trutworthy among the people in the digital globe.

#hire smart contract developers #smart contract developer #smart contract development #smart contract development services, #smart contract development company, #smart contract programmers

Contract Sizes: Comparisons EVM Vs. WASM Contract Code Sizes

Contract Code Size Comparison

The goal of this repository is to compare the sizes of compiled solidity contracts when compiled to EVM (with solc) versus WASM (with solang).

After some experimentation it turned out that a huge contributor to WASM code sizes is the smaller word size of WASM. Solidity treats 256bit variables as value types and passes them on the stack. Solang generates four 32bit stack accesses to emulate this. In order to improve comparability we do the following:

  • Patch all contracts used for comparisons to not use wide integers (use uint32 everywhere).
  • Pass --value-size 4 --address-size 4 to solang so that 32bit is usedfor the builtin types (address, msg.value).

How to use this repository

Put solang in your PATH and run compile.sh which is located in the root of this repository. The solc compiler will be downloaded automatically.

Test corpus

The current plan is to use the following sources as a test corpus:

Adding a new contract to the corpus from either of those sources is a time consuming process because solang isn't a drop in replacement. It tries hard to be one but there are some things that won't work on solang: First, almost all contracts use EVM inline assembly which obviously won't work on a compiler targeting another architecture. Second, differences in builtin types (address, balance) will prevent the compilation of most contracts.

Therefore we need to apply substantial changes to every contract before it can bea dded to the corpus in order to make it compile and establish comparability.

Results

The following results show the compressed sizes (zstd) of the evm and wasm targets together with their compression ratio. Wasm relative describes the relative size of the compressed wasm output when compared to the evm output.

The concatenated row is what we get when we concatenate the uncompressed results of all contracts.

Used solang version is commit c2a8bd9881e64e41565cdfe088ffe9464c74dae4.

ContractEVM CompressedWASM CompressedEVM RatioWASM RatioWasm Relative
UniswapV2Pair.sol3986691244%33%173%
UniswapV2Router02.sol5826921930%28%158%
ERC20PresetFixedSupply.sol2162289150%34%133%
concatenated111121739734%28%156%

Download Details:
Author: paritytech
Source Code: https://github.com/paritytech/contract-sizes
License:

#blockchain  #polkadot  #smartcontract  #substrate