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Good code reviews look at the change itself and how it fits into the codebase. They will look through the clarity of the title and description and "why" of the change. They cover the correctness of the code, test coverage, functionality changes, and confirm that they follow the coding guides and best practices. They will point out obvious improvements, such as hard to understand code, unclear names, commented out code, untested code, or unhandled edge cases. They will also note when too many changes are crammed into one review, and suggest keeping code changes single-purposed or breaking the change into more focused parts.Better code reviews look at the change in the context of the larger system, as well as check that changes are easy to maintain. They might ask questions about the necessity of the change or how it impacts other parts of the system. They look at abstractions introduced and how these fit into the existing software architecture. They note maintainability observations, such as complex logic that could be simplified, improving test structure, removing duplications, and other possible improvements. Engineer Joel Kemp describes great code reviews as a contextual pass following an initial, light pass.
The tone of code reviews can greatly influence morale within teams. Reviews with a harsh tone contribute to a feeling of a hostile environment with their microaggressions. Opinionated language can turn people defensive, sparking heated discussions. At the same time, a professional and positive tone can contribute to a more inclusive environment. People in these environments are open to constructive feedback and code reviews can instead trigger healthy and lively discussions.Good code reviews ask open-ended questions instead of making strong or opinionated statements. They offer alternatives and possible workarounds that might work better for the situation without insisting those solutions are the best or only way to proceed. These reviews assume the reviewer might be missing something and ask for clarification instead of correction.Better code reviews are also empathetic. They know that the person writing the code spent a lot of time and effort on this change. These code reviews are kind and unassuming. They applaud nice solutions and are all-round positive.
Starting at a new company is overwhelming for most people. The codebase is new, the style of programming is different than before, and people review your code very differently. So should code reviews be gentler for new starters, to get them used to the new environment, or should they keep the bar just as high, as it is for everyone else?Good code reviews use the same quality bar and approach for everyone, regardless of their job title, level or when they joined the company. Following the above, code reviews have a kind tone, request changes where needed, and will reach out to talk to reviewers when they have many comments.Better code reviews pay additional attention to making the first few reviews for new joiners a great experience. Reviewers are empathetic to the fact that the recent joiner might not be aware of all the coding guidelines and might be unfamiliar with parts of the code. These reviews put additional effort into explaining alternative approaches and pointing to guides. They are also very positive in tone, celebrating the first few changes to the codebase that the author is suggesting.
Code reviews get more difficult when reviewers are not in the same location. They are especially challenging when reviewers are sitting in very different time zones. I have had my fair share of these reviews over the years, modifying code owned by teams in the US and Asia, while being based in Europe.Good code reviews account for the time zone difference when they can. Reviewers aim to review the code in the overlapping working hours between offices. For reviews with many comments, reviewers will offer to chat directly or do a video call to talk through changes.Better code reviews notice when code reviews repeatedly run into timezone issues and look for a systemic solution, outside the code review framework. Let's say a team from Europe is frequently changing a service that triggers code reviews from the US-based owner of this service. The system-level question is why these changes are happening so frequently. Are the changes done in the right codebase or should another system be changed? Will the frequency of changes be the same or go down over time? Assuming the changes are done in the right codebase and the frequency will not go down, can the cross-office dependency be broken in some way? Solutions to these kinds of problems are often not simple and could involve refactoring, creating of new services/interfaces or tooling improvements. But solving dependencies like this will make the life of both teams easier and their progress more efficient for the long term, meaning the return on investment is often quite impressive.
A review snippet is a short excerpt of a review or a rating from a review website, usually an average of the combined rating scores from many reviewers. When Google finds valid reviews or ratings markup, we may show a rich snippet that includes stars and other summary info from reviews or ratings. In addition to the text of the review, a rating is an evaluation described on a numeric scale (such as 1 to 5). Review snippets may appear in rich results or Google Knowledge Panels. You can supply ratings for the following content types (and subtypes):
Structured data is a standardized format for providing information about a page and classifying the page content. If you're new to structured data, you can learn more about how structured data works.
You must include the required properties for your structured data to display in search results. You can also include the recommended properties to add more information to your structured data, which could provide a better user experience.
The name of the item that is being reviewed. If the review is nested into another
schema.org type using the review property, you still need to provide the name of the thing that is being reviewed. For example:
A numerical quality rating for the item, either a number, fraction, or percentage (for example, 4, 60%, or 6 / 10). Google understands the scale for fractions and percentages, since the scale is implied in the fraction itself or the percentage. The default scale for numbers is a 5-point scale, where 1 is the lowest value and 5 is the highest value. If another scale is intended, use bestRating and worstRating.
For decimal numbers, use a dot instead of a comma to specify the value (for example 4.4 instead of 4,4). In Microdata and RDFa, you can use content attributes to override the visible content. That way, you can show the user whatever style convention you want, while also satisfying the dot requirement for structured data. For example:
Search Console is a tool that helps you monitor how your pages perform in Google Search. You don't have to sign up for Search Console to be included in Google Search results, but it can help you understand and improve how Google sees your site. We recommend checking Search Console in the following cases: After deploying structured data for the first time After releasing new templates or updating your code Analyzing traffic periodically After deploying structured data for the first time After Google has indexed your pages, look for issues using the relevant Rich result status report. Ideally, there will be an increase of valid items, and no increase in invalid items. If you find issues in your structured data:
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