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Decimal accuracy error in Solan Phantoms: Change change
As a developer that consists of a decentralized application (DAPP) that exchange chips from the liquidity fund is one of the most common problems you are facing to deal with mistakes for the accuracy of decimal accuracy. In this article, we will examine why this problem occurs and how to reduce it using Phantom’s popular Platform Platform.
Problem: Mistakes for accuracy of decimal accuracy in marker swaps
The replacement of chips is associated with the exchange of one token for another in the liquidity area. In such a replacement, you must collect the input amount for the speed of the swap (ie J. The ratio of the required output marker to the input authority). For example, if you want to replace 1,000 x tokens for markers y and exchange rate is 2: 1 (y = x), your calculation should be:
1000 * 2 = 2000
However, if you are using Phantom to interact with the Solan Node, it does not accurately perform this calculation. Instead, it uses the SOL mark as a basic block for all calculations. This leads to mistakes for the accuracy of decimal accuracy, especially in solving large inputs, such as 1000.
Question: Phantom’s decimal accuracy
Phantom, who is a user -friendly and integrated Solana Platform, has a number of limitations that contribute to the question:
1
SOL token as a basic unit : As mentioned above, Phantom uses SOL Marker (SOL) as a basic unit for all calculations. This means that they are produced with SOL in decimal calculations.
- There is no clear rounding : During Phantom calculations, rounding is not clear. Instead, it makes arithmetics with a moving comma that can cause minor errors due to characteristic limitations of the accuracy of binary fractions.
Reduction of error for accuracy of decimal accuracy
You can take a few steps to avoid these problems and secure the accurate swaps of the brands:
1
Use decimal arithmetic libraries : Consider the use of external libraries such as ten.JS or JS-Decimal.js, Provide support for arithmetic arithmetic. These libraries allow you to perform high accuracy calculations without creating numbers on SOL tokens.
- This helps to ensure accuracy and reduces the possibility of decimal accuracy accuracy.
3
Use Phantom’s Built -in Rounding : Phantom has a built -in feature that allows you to enable rounding during calculations. Check the “rounding” option in the Settings menu that can help improve accuracy.
Conclusion
Decree for accuracy of decimal accuracy is common by changing tokens on Solane using Phantom. By understanding the basic principles and applying solutions, for example using decimal arithmetic libraries or clearly rounding the entrance and output, you can provide accurate marker swaps and maintain your DAPP integrity. Be sure to carefully check and monitor the performance of optimal results.
Example of code
To view these concepts, write an example of a code fragment in the strength that shows how decimal arithmetic works with Phantom:
`Solidity
Pragma of solidity ^0.8.0;
TOKENSWAP contract {
// Define the addresses of the input and output marks
reach out to public Xtokenaddress;
address the public ytkenaddress;
// Define the exchange rate as a fraction (eg 2: 1)
Uint256 public swaprate = 2000; // equivalent 1000 * 2
Function Swaptokens (UInt256 _xamount, Uint256 _yamount) public {
// Calculate the amount of output using decimal arithmetics
uint256 outputamount = (_xamount * swap) / (replace – 1);
// rounding from output up to 18-19 digits for reading
Outputamount = output.