Was sind einige effiziente Low-Level-Codierungspraktiken, die Sie kennen müssen?

In my experienced opinion by choosing the right language for the task, programmers can write efficient low-level code that meets the performance requirements of the application. Here are some recommended approaches for choosing the right low-level language: a) Consider the experience and expertise of the development team b) Consider the availability of libraries and tools c) Consider the future of the language

You should be careful about how you ask your questions to the coder, because most of us are on the autism spectrum. For me, low-level coding means programs produced in symbolic machine language, such as assembly. Speaking of them, I recommend keeping your stacks clean, your mind calm, and may the Force be with you. In the case of a higher-level programming language, I recommend learning the basics of structured programming, familiarizing yourself with the object-oriented paradigm and the framework of each language. That's where it starts.

Based on my experience, the choice of programming language is largely contingent upon the specific requirements of the client. Having worked across diverse industries such as Banking and Entertainment, I've found that each sector often has a preferred language that aligns with their specific needs. Take, for example, Java—it serves as a prominent illustration. In many cases, the selection of a programming language is not a decision to be made by the development team; rather, it is predetermined by the client based on their preferences and existing infrastructure.

Before even starting, you should consider how critical performance is. Performance comes at the cost of simplicity, significantly raising development and maintenance costs. Determine how the system can be scaled: horizontally, by adding cores or server instances, or vertically, by upgrading the hardware. If your system can be scaled, performance is likely a function of the right architecture rather than the code. Analyze all application components one by one for their performance requirements. You may not choose the same language and frameworks for all components.

Optimize your code for the hardware you are working with, taking advantage of its features, avoiding its limitations, and handling its errors. Use efficient algorithms and data structures, and avoid unnecessary operations and memory usage. Learn from existing code and libraries, and reuse code whenever possible.

keeping my experience in view, i can say that by understanding the hardware, programmers can write code that takes advantage of its features, avoids its limitations, and handles its errors. For example: 1) Bitwise operations: Programmers can use bitwise operations to manipulate data more efficiently than using arithmetic operations. 2) Pointers: Coders can use pointers to access memory locations directly, which can improve performance. 3) Inline assembly: Coders can use inline assembly to optimize code for specific hardware platforms.

Each hardware component possesses distinct architecture and underlying circuitry. A thorough comprehension of this architecture is pivotal for programmers, facilitating the crafting of optimized code. This understanding aids in navigating hardware limitations such as memory constraints and call stack considerations. Leveraging the internal instruction set can further enhance the development of performant code tailored to the intricacies of the specific hardware.

Once a very accomplished colleague of mine had a transient problem with some embedded code he wrote for an automotive application. The code worked most of the time, but very rarely & randomly it would fail to properly initialize the hardware. It took him a couple of days to find the bug: there were two 16 bit memory-mapped hardware registers beside each other, which he wrote with one 32 bit memory write. Which worked most of the time, but rarely there was some race condition which made the write(s) ineffective, thus failing to initialize both registers. Moral of the story: if the hardware specification says it is a 16 bit register, then write it as a word (16 bit) access, don't try to get cute.

A programmer should have deep knowledge about the hardware their software will run on because it enables them to optimize performance and resource utilization. Understanding the underlying hardware helps in efficient coding, minimizing bottlenecks, and ensuring the software runs smoothly. Coding for the lowest possible hardware is important to ensure broader compatibility and reach a larger user base. By designing software that can run efficiently on less powerful hardware, programmers make their applications accessible to a wider audience and enhance their software's usability and market reach.

Knowing about the hardware is an important thing when you're coding at a low level. It means understanding how the computer's parts, like CPU, memory, and storage, work together. When you know this, you can write your code in a way that matches how the computer handles information. This helps you make smart choices about things like organizing data and designing algorithms. For example, knowledge of cache behavior can guide you in minimizing cache misses for improved performance. Additionally, understanding hardware constraints is crucial for writing code that is resource-efficient and takes full advantage of the available computational power.

Optimize code using specific imports, local variables, and efficient data structures to achieve better time and space complexity, represented by Big O notation. Employ list comprehensions, generator expressions, and built-in functions judiciously for streamlined execution. Profile the code to identify and address bottlenecks, cache results for repeated calculations, and minimize function calls within loops. Strive for readability while considering performance implications.

Along with techniques for code optimization like loops, functions, and macros wisely, avoiding unnecessary variables and calculations, using constants and literals instead of variables here are couple of additional tips for code optimization: a) Measure before you optimize. It is important to measure the performance and memory usage of code before you start optimizing it. This will help you to identify the areas of code that need to be optimized and to measure the effectiveness of your optimizations. b) Test your optimizations. Once you have optimized your code, it is important to test it to make sure that it is still correct and that the optimizations have not introduced any new bugs.

Be mindful of the over-optimization traps. Over-optimization occurs when we focus too much on making our code perfect at the expense of losing sight of the actual problem we’re trying to solve. There can be long-term consequences if optimization leads to a complex codebase that only a few domain experts can understand. It’s important to be mindful of available compiler optimization techniques and use them appropriately. Try not to sacrifice code clarity for a negligible performance gain. Critically evaluate the overall architecture of the codebase. If the problem is with the architecture, it might not make sense trying to optimize individual code blocks.

Before starting optimization, set up a benchmark suite. Add one benchmark for each performance-sensitive use case. Optimizations can be surprising. You can easily degrade performance by adding caching to a method that does not need it.

Following coding standards is must. It increases your code quality and reliability and eventually it helps you become better programmer. Following are some benefits of it. 1. Coding standards helps you to write clean code, that’s easy to understand for other stakeholders like testers or reviewers. 2. Following coding standards polices your programming skills over time and you will emerge as good trainer later. 3. If we are continuously follow coding standards, it improves our code quality and reliability and help us gain more confidence in self. 4. Coding standards improve whole organization’s product quality as it improves individual performance. And many more….

Adopter des pratiques comme : - une nomenclature cohérente, - une documentation claire, - une gestion efficace des erreurs C’est essentiel, peu importe le langage utilisé. C’est d’autant plus important dans des projets mixant des langages anciens et modernes, où la clarté et la cohérence sont vitales pour une intégration fluide.

Coding standards are there for a reason, & code that doesn’t follow standards sticks out like a sore thumb. Lower level languages that don't otherwise incorporate containers for documentation can be particularly susceptible, as can dynamically typed languages where ill-disciplined variable declaration & use leads to extended development times. I've seen bad practice weaponised to make it difficult for another company to serve a common client. And I've seen really excellent practice that makes development frictionless. It's not difficult to appreciate which is preferable.

I would love to add few points that will be useful while testing the code: a) Start testing early: It is important to start testing low-level code as early as possible in the development process. b) Use a variety of testing methods: No single testing method can detect all errors. It is important to use a variety of testing methods to catch as many errors as possible. c) Automate your tests: Automating your tests can save time and effort. d) Get feedback from others: Ask other people to test your code, such as testers, peers, and managers.

Testing is the best friend of any software developer because it helps identify and fix bugs and issues early in the development process, ensuring a more reliable and robust final product. Developers should not avoid testing and writing predefined tests as doing so can lead to the release of unreliable software, causing user frustration, increased support costs, and potential damage to the developer's reputation. Effective testing helps maintain code quality, improve user satisfaction, and save time and resources in the long run.

Use a profiler to understand the performance bottlenecks of your code. Focus on the hotspots first. There are two kinds of profilers: CPU usage and memory allocation. Use both. Add your benchmarks to your test suites and specify acceptable thresholds. Make sure that the benchmark tests always run in an exclusive environment, where the hardware resources are not shared by other processes. Always test your code on the target hardware platforms. If your code is multi-threaded, be aware that some race conditions have a probability of 1 on 1 million. Therefore, some core tests must be repeated several million times.

Learning from others is an essential part of becoming a proficient low-level coder. By taking the time to learn from other programmers, you can improve your skills, knowledge, and confidence. Also, it is especially important for low-level coding, which is a complex and challenging discipline.

I completely agree that learning from experienced coders is crucial for efficient low-level coding. It’s like unlocking a treasure trove when you dive into books, blogs, forums, or open-source projects. You see different problem-solving methods and pick up on elegant coding techniques. And there’s immense value in seeking advice from fellow programmers, either online or in person. Their feedback and tips are like shortcuts to better coding. It’s not just about improving skills; it’s about cultivating a mindset of continuous learning and adapting. This step isn’t just a part of the journey; it’s what makes us grow as coders.

Being open to different approaches, and having a yen for learning is a fundamental attribute for any developer. Access to Large Language Models, and more specifically trained AI, are very useful, even refactoring tools, but they can lull a developer into thinking they have the best alternative. However, to discern the difference, the developer must sharpen themselves against as many sources as practicable.

Command on multi threading and memory management are very important to write low level programs. At low level you have more control but down side is that you are responsible for everything. Having strong grasp of basic building blocks like dead locks, crtical sections, byte level data seralization and deseralization are a must in writing reliable low level applications.

Might seem like a minor thing but always look for null reference errors so it does not break the application. Also have regular code reviews or peer-to-peer programming approach. Always perform exception handling and log error for auditing issues in Production environments.

An effective strategy I've adopted is to prefer stack allocation over heap whenever feasible when programming for embedded microprocessors. Stack allocation is typically faster due to the way memory is managed, and it also avoids the pitfalls of heap fragmentation. Additionally, this practice helps in preventing memory leaks, as stack-allocated memory is automatically reclaimed when a function exits.

Try coding to understand: 1. Processors internal structure such registers, caches, buses and frequency. 2. Memory and types of it RAM/ROM/FLASH/EEPROM. 3. Communication baudrates and frequencies. 4. Error handling and resource managment. 5. Software/Hardware compatibility testing.

Some often overlooked coding best practices for beginner programmers 1. Code indentation Proper indentation is the most important thing you can do to ensure that your code is readable and easy to understand. 2. Meaningful naming Your code’s variable names and function names should be intuitive 3. Comments that add context 4. Don’t repeat yourself 5. Low coupling and high cohesion 6. Consider your context