json_serializable.dart VS SonarQube

If you really want to write it yourself, sure. This code is very easily automatically generated.

https://pub.dev/packages/json_serializable

Serializing and deserializing json is easy thanks to the json_serializable integration. Makes it impossible to make mistakes like you would normally when working with dynamic values and strings.

We will now create a new file called build.yaml in the failures directory and add the following code. This will change the behaviour of the json_serializable so that it generates JSON keys in snake_case.

Once the package has been created, we will install freezed for JSON serialization and value equality , as this library provides helpful tools for these tasks. We will use json_serializable for JSON serialization. To install freezed and freezed_annotation, open your terminal inside the models package and use the command:

However, we cannot do this kind of JSON de-serialization in Flutter. Without reflection, we need to consider other approaches for these same tasks. For instance, the package json_serializable uses source code generation for decorating classes with methods to serialize and de-serialize JSON strings.

We could work around having to introduce parsing logic by using a package such as json_serializable to parse data to and from JSON to save ourselves some time. However, you'd need to make sure the native platforms are returning the data in the exact format you are expecting, and vice versa. Otherwise the parsing will fail.

json_serializable - Provides Dart Build System builders for handling JSON.

The other ways involve using a package like json_serializable. They automatically generate boilerplate code to convert between your model classes and JSON. The issue is that Flutter doesn't support reflection (Dart does, but Flutter for mobile doesn't due to performance reasons) so any kind of library that generates code needs to do so statically. All packages involve annotating your classes and then running a builder script that generates the boilerplate code.

Code Review and Quality Assurance: Tools like DeepCode and SonarQube leverage AI to review your code, identify potential issues, and suggest improvements.

2. SonarQube: https://github.com/SonarSource/sonarqube SonarQube enhances code quality and security. It performs automatic reviews to detect bugs, vulnerabilities, and code smells in your code.

SonarQube (Scroll down to the Sonarqube section to see instructions on how to set up and configure SonarQube manually)

SonarQube https://www.sonarqube.org/

There are commercial tools that can be integrated into a CI pipeline and/or a developer's IDE. I've used SonarQube before, but there are others.

having a code review and analysis tool in CI/CD pipeline can help developers to keep their code clean. some examples of these tools are sonarqube and embold.

But back in 2012, tech debt-related tools were in their infancy. JetBrains released IntelliJ IDEA in 2000, and SonarQube was initially released in 2006. Stepsize started in 2015, and Visual studio intellicode wasn't made by Microsoft until 2018.