Finally, our DevOps team uses tools like terraform fmt and predefined templates to ensure consistent formatting. We’ve even extended the clean-code mantra to our documents, which all live in-source next to the code and are rendered automatically with each build.
- Like Carbon Copy Cloner, it can even clone to an external drive connected to another Mac on your network (as long as you install the $10 ChronoAgent utility on that Mac).
- So, there may be different Word and Excel documents on each computer, but the Word and Excel versions and the user interface — how these programs are accessed — are the same on each computer.
- Though SuperDuper and Carbon Copy Cloner are my favorite drive-cloning tools, a third backup app, Econ Technologies’ $40 ChronoSync (4.5 mice) earns an honorable mention here.
- As its name suggests, ChronoSync is primarily a Mac-to-Mac sync tool, but it also includes an extensive set of backup features, including the capability to make bootable clones.
Incorrectly formatted documents will block a merge in the same way as a failing test. The software group prioritizes clean code in all aspects of the software lifecycle, including development, testing and deployment. During development, we use shared libraries, automated start download tools and multi-person review cycles.
We try to outline and document expectations ahead of time for what we expect from ourselves and each other. I really love this approach with a focus on collaboration and ownership because I think we have cultivated a team that loves working both together and for each other. At the end of the day, that’s really why you want to write clean code. Two big pet peeves of mine are when logic seems to live across multiple services with no clear ownership between them and over-optimizations in the name of efficiency. Both make it hard to build on top of the foundation, with new features forcing changes in multiple places or the seemingly "efficient" code being hard to understand.
As well, using tools like Mypy and Black before review helps minimize errors. We also have joint tech planning sessions and team reviews of both tech plans and pull requests.
Our software group uses coding standards and automated tooling that enforces those standards. This allows us to keep a maintainable codebase where any developer can support and contribute, not just the original author. The use of linters and other automated tools allow code reviews to focus on implementation rather than poorly formatted or structured code. Additionally, our codebase has a large library of reusable components that reduces the opportunity for duplicated or divergent code.
Institutional knowledge then becomes a bit too relied upon. There is nothing wrong with a simple IF statement if it’s clean, readable and gets the job done.
No engineer wants to spend more time fixing code than writing it. Berlin said upholding high standards throughout the product lifecycle reduces time spent untangling messy code later. His team leans on automated tools, shared libraries and rigorous code reviews to ensure implementations go smoothly. Aron Szanto, an NLP team lead atKensho, a company that leverages data to develop AI, said they try to avoid artificial coupling of components. Artificial coupling can be avoided by being thoughtful and asking where a method, variable or class should reside, what parameters it should take and where it will be called.
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Our testing is automated and contained in our source code. The automation of the tests through continuous integration tools help keep the merged code accurate and bug-free, leading to less churn and fewer edits in the codebase.