One of the key advantages of useGeolocation is its simplicity. By encapsulating the complex logic required for geolocation access and handling, this hook provides a clean and reusable solution. The hook automatically handles the loading state, updating it when geolocation data is being fetched, and sets the error state if any issues arise during the process.
There are two articles on Russian, the author of which writes a virtual machine (interpreter) for executing a simple bytecode and then applies different optimizations to make this virtual machine faster. Besides that, there is a compiler of a simple C-like language into this bytecode. After reading this article and getting familiar with the compiler, I thought that it would be interesting to try writing a virtual machine for this language that would be able to apply JIT-compilation to this bytecode with the libjit library. This article describes the experience of doing that.
I found several articles online that describe the usage of this library, but those that I saw, describe the compilation of concrete programs with libjit, while I was interested in compiling arbitrary bytecode. For people interested in further reading, there is an official titorial, a series of articles and a series of comparisons (in Russian).
The implementation was done in C++ because we aren`t playing games here. All my code is in my repository. The "main" branch has just the interpreter of the PigletVM bytecode; "labels-with-fallbacks" has a partial JIT compilation implementation (that doesn`t support JUMP instructions), "full-jit" has fully working JIT-compilationl; "making-jit-code-faster" makes code generated by JIT work faster and "universal-base-vm*" branches merge the interpreter and JIT-compilation implementations, by implementing a base generalised executor, which can be used for different implementations of PigletVM (both the interpreter and libjit compilation)
Brainstorming is a popular working method which is commonly used by UX design teams. It involves a group of designers meeting (whether offline or via video call) and generating as many ideas as possible to find the best solution to a specific problem or come up with creative design ideas. Brainstorming sessions are usually held at the start of a UX project so that designers could use the ideas they think are the best later in the process of product creation. These sessions can vary in duration and form depending on which problems need to be solved, how many people participate and how many ideas need to be generated.
One of the key advantages of useFetch is its simplicity. By abstracting away the fetch logic into a reusable hook, developers can quickly and effortlessly make HTTP requests and handle responses without repetitive boilerplate code. With just a few lines, useFetch handles the network request, parses the JSON response, and provides the resulting data.
Multidisciplinary project emerges when multiple teams with different expertise areas join to create a product. Despite the fact the product development is not something happining merely my a wish, product leads often perceive it as an easy walk. Usually this easy walk becomes a crash course. Let's uncover what leads to crash and what is necessary to succeed.
Python, Java, C++, Delphi, PHP—these programming languages were used create a virtual crypto ATM machine to be tested by the participants of the $NATCH contest at Positive Hack Days 12. The entire code was written by ChatGPT and proved to be exceptionally good. This time, we had reviewed the contest concept and decided to use a report system. In addition to standard tasks (kiosk bypass, privilege escalation, and AppLocker bypass), this year's participants faced new unusual tasks. Read on below to find out which ones.
The useEventListener hook is a versatile tool that can be used in a wide range of scenarios. Whether you need to capture keyboard events, listen for scroll events, or interact with user input, this hook has got you covered. Its simplicity and elegance make it an ideal choice for any React project, from small-scale applications to large-scale enterprise solutions.
The general trend of technology development is characterized by surges and declines. Consider, for instance, the mass movement of human bodies. Initially, horses and wagons were used, which gradually evolved into a distinct industry. Then trains appeared abruptly. Horses were quickly forgotten, and the focus shifted to a new avenue. Steam became an object of study and evolved into a complex science. Diesel and electricity developed concurrently. At a certain point, steam engines became obsolete, and everyone transitioned to diesel and electricity. Similarly, we are now transitioning to electric cars that require significantly fewer fluids.
Technologies evolve and function until new technologies completely replace them. I believe we are entering an era where framework and Electron technologies may be eclipsed by generative AI. Let's examine some examples.
One of the key advantages of useDeepCompareEffect is its ability to prevent unnecessary re-renders. By performing a deep comparison between the current and previous dependencies, the hook intelligently determines if the effect should be triggered, leading to optimized performance in scenarios where shallow comparisons fall short.
The useDebugInformation hook can be applied in various scenarios. For instance, imagine you're working on a complex form component where certain props trigger updates or affect rendering. By utilizing useDebugInformation, you can easily monitor how these props impact your component's performance and whether unnecessary re-renders are occurring. Additionally, the hook can be invaluable when investigating why a specific component is not updating as expected or when fine-tuning optimizations in a performance-critical application.
Time complexity: O(max(nums) * log(max(nums)) + n * log(n)). Accounting for computing prime scores, using the stack to compute next greater elements, and sorting the tuples.
Space complexity: O(max(nums) + n). Considering the space required for arrays and the stack used for computation.
When using older version of Java with not updated truststore, you may face an error while connecting to web hosts, that Java is unable to find a valid certification path to the requested target.
This happens because JRE truststore is unaware of the new root certificate that is being used by Let's Encrypt nowadays. Below I tried to clarify detail behind this issue and how to solve it. I hope newcomers might find this material helpful.
In our previous post, we presented a modified Schnorr protocol compatible with the Instant Digital Signature (IDS) mode and also announced the design of other protocols with this feature. In this post we describe such protocols based on the pairing function.
Currently I am investigating firmware development for STM32 microcontrollers and I would like to share with you my experience for doing it in Qt Creator IDE.
There are a lot of IDEs, which are used for firmware development of STM32. Some of them, being quite comfortable, have restrictions for trial license. For example, the one of the most known IDE, IAR Embedded, suggests either a limited amount of product usage time (30 days) or the limited firmware size of 32 MB, which is not too much.
Within this scope of the publication, we investigate the method of setting up an environment that allows one to develop the full value of the STM32 firmware in Qt Creator.
This custom hook is particularly beneficial in scenarios where you need to handle user input, such as search bars or form fields, where you want to delay the execution of an action until the user has finished typing or interacting. It's also useful for optimizing network requests, ensuring that requests are sent only after the user has stopped typing or selecting options.
2809. Min Time to Make Array Sum: Efficient Swift solution, using dynamic programming, for minimizing time to reach a sum in arrays A and B. Time: O(n²), Space: O(n).
2813. Max Elegance of K-Length Subseq: Swift code for elegantly selecting unique k-length subsequences with profit and categories. Solution uses sorting and iteration. Time: O(nlogn), Space: O(n).
One of the main advantages of "useDarkMode" is its simplicity. With just a few lines of code, you can enable dark mode in your React application. By invoking this hook, you'll receive the current dark mode state and a function to toggle it.
The "useDarkMode" hook dynamically updates the HTML body class to apply the "dark-mode" styling whenever dark mode is enabled. This approach ensures consistency across all components without the need for manual class manipulation.
Copying text to the clipboard in a React application can be a tedious task. To simplify this process, I've created a powerful custom hook called useCopyToClipboard. With just a few lines of code, this hook streamlines the copy-to-clipboard functionality, providing developers with a hassle-free solution.
One of the key advantages of this custom hook is the ability to update the cookie value. The updateCookie function, returned by useCookie, enables you to modify the value of the cookie. By invoking this function with a new value and optional options, such as expiration or path, you can instantly update the cookie.
Picture this: A thriving e-commerce platform faces a constant battle against fake reviews that skew product ratings and mislead customers. In response, the company employs cutting-edge algorithms to detect and prevent fraudulent activities. Solutions like these are crucial in the modern digital landscape, safeguarding businesses from financial losses and ensuring a seamless consumer experience.
The industry has relied on rules-based systems to detect fraud for decades. They remain a vital tool in scenarios where continuous collecting of a training sample is challenging, as retraining methods and metrics can be difficult. However, machine learning outperforms rules-based systems in detecting and identifying attacks when an ongoing training sample is available.
With advancements in machine learning, fraud detection systems have become more efficient, accurate, and adaptable. In this article, I will review several ML methods for preventing fraudulent activities and discuss their weaknesses and advantages.