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Ensure Smart Contract Success with These Expert Audit Tips

Paulina Lewandowska

03 Jan 2023
Ensure Smart Contract Success with These Expert Audit Tips

The use of smart contracts, a tool that enables the automation of several processes and transactions, has grown significantly in the realm of blockchain technology. Before these smart contracts are implemented, it is crucial to guarantee their security and dependability. Smart contract auditing is useful in this situation.

The finest advice and methods for auditing smart contracts, as provided by seasoned smart contract developers, will be covered in this article. You may make sure that your smart contracts are of the greatest caliber and without flaws by adhering to these suggestions.

We hope that this article will provide valuable insights and guidance for those looking to audit their smart contracts effectively.

Table of Contents:

Understand the purpose and functionality of the contract

Before performing an audit, it is crucial to comprehend the function and intended use of a smart contract. This will enable you to find any potential problems or weaknesses and make sure the contract is functioning as planned.

The following points should be taken into account when figuring out the function and goal of a smart contract:

  1. Who will use the contract, and what are their needs and objectives? Identify the stakeholders.
  2. Establish the business logic: What is the contract meant to accomplish? What are the parameters for the input and output, and how should the contract handle various circumstances?
  3. Recognize the environment: How will the contract be used in that environment? What are the limitations and restrictions of the blockchain platform that will be used for its deployment?
  4. Take into account the long-term effects of the contract: How will the agreement be used going forward? Will it ever require updating or changing, and if so, how will those changes be handled?

You may more easily spot possible problems and make sure the contract is appropriate for its intended use by fully comprehending the function and purpose of a smart contract.

Review the code

Understanding the function and intended use of the contract is crucial when conducting a smart contract audit. This will enable you to find any potential problems or weaknesses and make sure the contract is functioning as planned. A static code analysis tool can be used to evaluate the code and help find potential problems including grammatical mistakes, bugs, and security vulnerabilities. It's also critical to adhere to best practices for developing smart contracts, such as making use of secure libraries, managing exceptions correctly, and carrying out appropriate testing and error management. You should also look for widespread security flaws like uninitialized variables, reentrancy attacks, and unsafe random number generation. Additionally, it's critical to ensure that the code is well-written, simple to comprehend, and maintained, as well as that the contract's logic is right and that it appropriately addresses all potential cases. You can see any problems and make sure the contract is secure and error-free by carefully going over the code.

Test the smart contract

A smart contract must be extensively examined during testing to make sure it works as planned and has no unforeseen repercussions. For this, you need to:

  1. Create test cases that account for all edge situations and potential eventualities. This will make sure that every possible problem is found and that the contract is thoroughly tested.
  2. Automate the testing procedure using a testing framework like Ganache or Truffle. As a result, running test cases and monitoring the outcomes will be simpler.
  3. Utilize tools like Mythril or Oyente to scan for common security flaws. By doing this, you can make that the contract is safe and has no weaknesses that could be used against it.
  4. Verify that the contract operates as planned and generates the desired outcomes. This will support the idea that the contract is operating properly.
  5. Verify that the contract is optimized for gas utilization and free of extra code that can drive up gas prices. This will help to guarantee the contract's effectiveness and economy.

Check for correctness

A crucial step in the audit process is verifying a smart contract's accuracy. Verifying that a contract accomplishes its goals and complies with the contract owner's specifications is part of ensuring its validity. You must first analyze the contract's details and comprehend the conditions and limitations in order to verify that everything is correct. You can use this to find any potential problems or places that require more investigation.

The next step is to check the code for flaws or faults to make sure it follows the contract's logic. This will make it easier to verify that the contract's logic is sound and that it appropriately accounts for all potential outcomes.

It is crucial to confirm that the contract complies with applicable rules and regulations if it will be utilized in a regulated environment. This can entail consulting a legal expert or doing more investigation to verify compliance.

You can make sure the contract is appropriate for its intended use and has no unintended consequences by carefully checking for accuracy. This is crucial to ensuring that the contract operates correctly and meets its intended goals.

Check for efficiency

You should make sure the contract is optimized for gas usage and free of any extraneous code that can raise gas prices in order to verify for efficiency. This could lower the cost of using the contract and increase its usefulness for users.

You should study the contract's code to verify for efficiency and search for any places where gas utilization could be maximized. To reduce gas consumption, this may entail eliminating pointless code or improving certain operations. Additionally, you should test the contract to gauge its gas consumption and make sure it is within acceptable bounds.

Checking for backward compatibility

Checking for backward compatibility is also important if the contract is intended to be used on a specific blockchain platform. To check for backward compatibility, you should ensure that the contract is compatible with the version of the platform it will be deployed on. This may involve reviewing the contract's code to ensure that it uses features and functions that are supported by the platform, and testing the contract to confirm that it functions correctly on the platform.

By checking for efficiency and backward compatibility, you can ensure that the contract is optimized for use and can be deployed smoothly on the intended platform.

Review the contract's dependencies

It is crucial to examine the contract's dependencies during a smart contract audit to make sure that it is utilizing the most recent and safe versions of any external libraries or contracts it depends on. It is vital to ensure that the contract is using the most recent and secure versions because outdated or insecure dependencies can cause flaws or mistakes.

You should first look at the contract's code to find any external libraries or other contracts that it depends on before reviewing the contract's dependencies. The versions of these dependencies should then be checked to make sure they are current and secure. You should suggest updating the contract's dependencies to the most recent and secure versions if you discover that they are out-of-date or unsafe.

Checking the dependencies that the contract is using for any vulnerabilities or known problems is also a smart idea. Researching the dependencies and looking for any security advisories or other warnings will help you achieve this. You can contribute to making sure that the contract is as secure as possible by going over the dependencies in this manner.

Overall, a critical stage in the smart contract audit process is carefully analyzing the contract's dependencies. By doing so, you can lower the possibility that the contract contains flaws or inaccuracies and increase its security.

Review the contract's deployment and ownership

To make sure that a smart contract is secure and that only authorized parties can make modifications to it, it is required to review the deployment and ownership of the contract during an audit. This makes it more difficult for someone to gain access or modify the contract.

You must first determine who the contract's owner is and how it was used before you can analyze the contract's ownership and deployment. The contract should then be owned and deployed securely, utilizing best practices like a secure key management system and adhering to appropriate security protocols.

Additionally, make sure that only those with permission can alter the contract. This can entail checking the permissions and access controls of the contract to make sure that only parties with the proper authorization can change it.

In general, examining the contract's deployment and ownership is an important step in the process of a smart contract audit. In order to avoid unauthorized access or contract tampering, it can assist ensure that the contract is secure and that only authorized parties are able to make changes to it.

Additionally, make sure that only those with permission can alter the contract. This can entail checking the permissions and access controls of the contract to make sure that only parties with the proper authorization can change it.

In general, examining the contract's deployment and ownership is an important step in the process of a smart contract audit. In order to avoid unauthorized access or contract tampering, it can assist ensure that the contract is secure and that only authorized parties are able to make changes to it.

It is advisable to consult a legal expert to ensure that the contract is enforceable if it is meant to have legal ramifications. You can better comprehend the contract's legal ramifications and ensure that it is constructed in a way that makes it enforceable by consulting a legal expert. They can also provide you advice on any further measures that might be required to make sure the contract is legally enforceable.

Overall, a critical stage in the smart contract audit process is taking the contract's legal consequences into account. It can aid in ensuring that the contract complies with all applicable legal requirements and is legally enforceable.

Conclusion

A thorough audit is necessary to make sure a smart contract is trustworthy and safe. As part of a smart contract audit, it is important to thoroughly test the contract to make sure it works as intended and has no unintended consequences. You should also confirm that the contract satisfies the contract owner's requirements, look for efficiency and backward compatibility, review the contract's dependencies, deployment, and ownership, and think about the contract's legal ramifications. These guidelines can help you make sure that a smart contract is trustworthy, safe, and appropriate for its intended use.

Be sure to read our other articles on the subject for more details on smart contract audits. You may gain extra knowledge and best practices for auditing smart contracts from these resources.

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?
Table of Contents

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series

Tagi

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!

Tagi