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Outstanding coders exhibit a distinctive methodology in crafting code, a hallmark of their expertise in the software development realm. Their approach involves meticulous attention to detail, efficient problem-solving, and a commitment to writing clean, maintainable, and highly functional code.

“Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” – Martin Fowler.

It's essential to adhere to a consistent coding standard and style. Consistency greatly enhances code readability and comprehension for both your future self and your fellow team members.

Maintaining a uniform style guide has significant benefits for both teams and the scalability of a codebase. This practice is exemplified by companies like Meta and Google, enabling them to rapidly produce code without it becoming convoluted and hard to maintain over time.

Successful leaders in tech have internalized their team's coding standards and diligently adhered to them, recognizing the advantages this brings.

• Google employs a readability process to ensure clean code.
• Additionally, Google has made some of their style guides available as open source resources.
• Meta has developed a C++ style guide for certain open source code projects.

Use a code linter for your team is undoubtedly a worthwhile endeavor if one hasn't been set up already.

Every exceptional engineer I've encountered produces code that, while it may be intricate to craft, is ultimately straightforward to read and comprehend. The term that best encapsulates this quality is "aesthetically pleasing code."

Their code embodies cleanliness, organization, and logical structure. Each coding decision aligns with reason, and any exceptions are meticulously documented.

One effective approach to writing such pristine code is by adhering to fundamental principles, such as the SOLID principles. Although initially conceived with object-oriented programming in mind, these principles extend to general programming:

1. Single Responsibility: Ensuring that a class has only one responsibility.
2. Open-Closed: Allowing software objects to be open for extension while remaining closed for modification, fostering predictability and maintainability.
3. Liskov Substitution: Guaranteeing that subtypes can seamlessly substitute their base types without impacting program correctness.
4. Interface Segregation: Breaking down unwieldy interfaces into smaller, specific ones, enabling cleaner and more importable packages.
5. Dependency Inversion: Shifting the dependency model so that high-level modules and low-level modules both rely on abstractions, resulting in a more adaptable and loosely coupled system design.

A notable example of this principle in action is reflected in the practice of naming. Sound naming conventions eschew magical values, introduce clear distinctions, employ descriptive function names, and utilize understandable variables.

Code should be devoid of unexpected behaviors, achieved through adherence to coding principles and the implementation of thorough testing procedures.

High-quality code exhibits predictability.

Testing enforces code clarity and predictability, instilling confidence. Effective automated testing empowers teams to make code adjustments without the fear of inadvertently disrupting hidden elements.

Various types of tests include:

1. Unit Tests: These evaluate individual components and isolated functions.
2. Integration Tests: They examine interactions among multiple components.
3. End-to-End Tests: These assess the entire system's functionality from a user's perspective.

Effective tests maintain simplicity. They should readily indicate the source of failure when reviewing a failed test.

Additionally, it's crucial to discern what not to test. For instance, if the resources required for an end-to-end test outweigh the program's actual benefits, it's more effective to replace the test with comprehensive documentation, monitoring, and alerting directed to the appropriate stakeholders, such as the code owner.

Tests should refrain from delving into implementation specifics within the code. This means avoiding the examination of specific CSS selectors in frontend code and, instead, opting for data-attributes or employing screenshot tests.

Remarkable systems are never created in isolation. Exceptional engineers engage in design reviews, actively seek feedback, and persistently refine their initial code designs.

We all possess knowledge gaps that can be bridged by collaborating with others. Novel viewpoints frequently enhance code clarity and introduce innovative approaches that might not have been considered otherwise.

The finest engineers excel in both communication and collaboration, unafraid to invest the time in working together to achieve superior outcomes.

This can manifest in simple actions like reaching out to a colleague for a brief document review or involving additional code reviewers in a critical pull request.

Exceptional engineers maintain a detachment from their code. They exhibit the courage to discard and commence anew, even when they're 90% through, all in pursuit of an improved final outcome. They understand that code isn't a personal entity and embrace feedback readily. Perfection isn't the goal; it's about delivering impactful change. To cultivate this detachment, consider that in two decades, a substantial portion of your code may become technical debt, obsolete, or subject to rewriting.

The most skilled engineers I've encountered achieve rapid project completion through a seemingly paradoxical method: they code methodically and deliberately.

At first glance, this approach may seem counterintuitive. The principles and habits mentioned may indeed extend the initial coding phase, but they serve as building blocks for steady project advancement.

By investing time in adhering to standards, comprehensive testing, principled design, and frequent communication, these engineers ultimately save time in the long term.

In contrast, my personal experiences as an intern and junior engineer, a path shared by many, often involved rushing ahead three steps, encountering insurmountable obstacles, and subsequently retreating five steps.

Code has a broader audience than just computers; it's crafted for humans.

This audience comprises your fellow engineers who engage in reading, maintaining, and expanding upon your codebase.

It extends to users, whether they are young individuals using their phones, developers interacting with your API, or even yourself.

The most skilled engineers, in my experience, prioritize a product-centric approach, focusing on addressing human needs.

They consistently assess the worth of their code for all these user groups. If their code falls short in any of these aspects, it doesn't find its way into production.

The aforementioned "rules" and "principles" are essentially guidelines.

Not every situation neatly aligns with these guidelines. Sometimes, the code you're crafting is like a square trying to fit into a circular mold, and that's perfectly acceptable.

In such cases, it's crucial to document why your code deviates from the norm. Failure to do so may lead to future individuals, including yourself, questioning the departure from standards and potentially investing substantial hours attempting to reconfigure it to comply, only to reach the same conclusion as before. Sound familiar?

The reality of software development acknowledges that not all code can achieve pristine cleanliness or adhere to rules flawlessly.

What it can achieve, however, is consistency, clarity, comprehensibility, testability, and value.