When it comes to programming, everyone makes mistakes. Errors are bad for developers since they are difficult to handle. But handling as many as possible errors will bring out the strong developers. Some faults result in glitches that perplex users. The two most critical concessions for an application are safety and security. Safety and security are the top most prior in the present scenario of hackers world. It makes no difference what type of application we are creating. As a result, preventing these problems is critical for developers. It is for this reason that many developers rely on the linter linting process. This section will explain what a linter is and the top ten Java linters.
What so linting is called in programming?
Linting is the automated process of reviewing source code for programmatic and stylistic faults. The lint (or linter) tool is used to do this. Linting is an essential component of development since it lowers mistakes and improves overall code quality. So, improving code quality and reducing mistakes will improve the safety scope of the code. We may expedite development and lower the code of identifying mistakes sooner by using the linting method. Linting occurs prior to code review and testing.
What is a Linter?
Let us begin by defining a linter. A linter, as mentioned in the introduction, is a tool that may assist you improve your code. But how does it accomplish this? The answer is to check for flaws in your source code and tries to evaluate it.
The name "linter" originated from a program that evaluated C source code and was originally called "lint." This tool was created in 1978 by computer scientist Stephen C. Johnson while working at Bell Labs.
The original lint tool, as well as early related programs, were designed to analyze source code and recommend compiler improvements. Lint-like tools gradually included many additional sorts of inspections and verification.
However, as stated in the introduction, linters are not limited to compiled languages. On the contrary, linters are far more beneficial for interpreted languages because there is no compiler to discover problems during development.
The linter functions essentially as a static code analyzer. It is a program or tool that assists developers in improving their code. When we use standard rules, it detects mistakes. It is important to note that a linter checks our code for stylistic and programming problems against the rules it is familiar with. If a section of our code violates the usual guidelines, it may cause a problem. It's common in dynamically typed languages.
Advantages of Linters :
- Production mistakes are reduced : The usage of linters aids in the diagnosis and correction of technical flaws in code, such as code smells. As a result, fewer errors are introduced into manufacturing.
- Code is more readable and consistent: Linters, by enforcing its standards, can assist teams in achieving a more legible and uniform style.
- During code reviews, there are less conversations concerning code style and aesthetic decisions. Discussions regarding code should not be filled with interminable disputes over aesthetic choices. Linters can take care of the issues.
- Code quality may be measured objectively. Discussions on code quality frequently devolve into subjectivity. Linters give a measured and objective assessment of code quality.
- Code that is more secure and performant. Some linters, but not all, examine source code for efficiency and safety.
- More developers are being educated about code quality. Linters can assist developers, particularly novice ones, in learning about code quality.
Checks provided by linters :
When it comes to interpreted languages, the most fundamental and critical sort of checks that a linter may give are syntax error verifications. Developers should not even push code to the mainline unless it passes syntax checks.
One method is to utilize pre-commit hooks to prohibit users from submitting their work when the linter verification shows that there are issues with the code.
Code Standards Adherence :
Adherence to code standards is another important sort of check that linters give. Some may dismiss this as a simply aesthetic problem, but they would be incorrect. Having a single consistent coding style is advantageous for reducing the cognitive strain of reading, interpreting, and updating code. A codebase with a uniform coding style is easier to comprehend, and the developers who use it are less likely to contribute defects.
That is why linters specialize in checking codebases for conformity to code styles. Some tools are opinionated, which means they come with a set of pre-defined rules and norms that cannot be modified. However, some tools are extensively adjustable, allowing the user to tailor the tool to their chosen coding methods.
Code Smells :
Code smells are indicators that something is amiss with your code. It's really important to have a program that automatically detects certain indications so you may study them further if necessary.
Long functions, for example, are frowned upon by many individuals, including myself. As an example, you might configure your linter to identify functions that are more than a certain number of lines long.
Another often mentioned code smell is too complicated code. But we're not talking about complexity in a subjective sense here, but rather in a very objective sense. The number of potential execution pathways within a function is represented by cyclomatic complexity, which is a valuable code statistic. Linters may compute the cyclomatic complexity of your functions and highlight those that exceed a specific threshold.
Security Checks :
Finally, there is security, which is without a doubt the most important aspect of a contemporary program, particularly a web app. If you get it wrong, the ramifications may be disastrous, not only financially and professionally, but also legally (think GDPR and similar regulations.)
Fortunately, there exist tools that perform critical security verifications, so linters can aid here as well.
Examples of Linters in Java :
It is a well-known linter among developers. Its popularity grows as a result of regular updates, community support, and extensive documentation. It is naturally compatible with Ant and CLI. Its plugin is also available for many IDEs, allowing for easy integration. It includes pre-configured configuration files that support both Sun coding norms and Google Java style.
Checkstyle is one of the most widely used linters. With this level of popularity comes frequent updates, extensive documentation, and an active community. Checkstyle is naturally compatible with Ant and CLI. It is also available as a plugin for a variety of IDEs and toolsets, including Eclipse, Codacy, Maven, and Gradle - albeit these plugins are handled by third parties, so long-term maintenance is not guaranteed.
Checkstyle includes pre-made configuration files that support both Sun Code Conventions and Google Java Style, but because these files are XML, they are highly configurable to meet your workflow and production requirements.
It is also worth noting that a project with Checkstyle integrated into its build process would fail to build even if small faults exist. This might be an issue if you're only interested in catching larger problems and don't have the resources to repair minor ones.
The second item on our list is not a linter per such, but it will assist you in improving your code quality and preventing errors before they become severe issues. Lightrun is a runtime debugger, whereas everything up to this point has been a static code analysis. At the end of the day, static code analysis and linting can only go you so far, thus Lightrun is worth adding to your workflow if you require a bit more.
It is not a linter, but it does help to enhance code quality. It is a debugger that runs in the background. It also prevents bugs from becoming a major issue. We may use Lightrun to insert logs, metrics, and snapshots into our code, even during runtime or directly from the IDE or CLI. It also enables us to diagnose production bugs and do data analysis on our code without slowing or disrupting the application.
In the age of cloud computing, production is the peak stress test for any codebase. Lightrun allows you to incorporate logs, stats, and snaps into your code directly from your IDE or CLI, even during runtime. Lightrun allows you to diagnose production issues and perform analysis of data on your code without shutting down or stopping your application.
It detects typical programming errors such as unused variables, empty catch blocks, superfluous object construction, and so on. Another feature is a copy-paste detector that detects duplicate code blocks, making it easy to locate code that can be refactored.