If someone told you that some magic machine could create a software app from scratch, you might think of it as some futuristic invention. A long while back, that's probably what people thought about industries that could mass-manufacture products. Today most industries don't think twice about the time and energy saved by machines when they build things like cars, clothes, chemicals, and more. It is that common.
Human intelligence has the unique potential to come up with ingenious ideas, and any business will benefit from employing its smartest resources at the managerial level. What if this level of automation could also be applied to programming languages and coding? This is exactly that source code generation is capable of. On top of freeing up people's time to focus on even more advanced work, source code generation can also demystify the build process of software development and programming languages. Here, we'll explore in detail what all source code generation entails, its numerous benefits, as well as some good platforms that can help you get started with source code generation.
What is a source code generator?
The principle behind generative coding and source code generation is that programs can be designed to create software systems in an automated method. Such platforms can generate code, and this can enhance developer productivity to a great extent. You won't have to write code with programming languages and use complex database schemas. This generated code can be utilized separately from the generating system during the runtime setting. This level of code generation can also be done on platforms like Visual Studio. Visual Studio lets you code, and some of its add-on modules let you auto-complete your code.
Engineers can see user-generated code while it is generated using source generators instead of using programming languages to code. They can generate code in which the new source files can be introduced to the user's assembly on the fly. You can then generate code that executes while compiling. It examines your software to create new source files, which are then compiled alongside the rest of your program. There are also many open-source code generators available. Programmers improve these open-source generators daily, making them easier to use.
A source code generator enables two key functions. The first thing that it can do is to get a compilation object for all the user-generated code that is currently being compiled. Just as with scanners today, you can examine this object and develop software that interacts with the syntactic and semantics frameworks for the program that is currently compiled. The second function that it does is to create source files that can be used to supplement a compilation object. This means that you can add extra source code to a compilation while it is still in progress.
These two factors work well together to make source code generation more practical than programming languages. This can be much easier to follow than learning entire programming languages. All of the detailed information that the compiler accumulates during compilation can be used to analyze user programs. The program from your code generation, which is based on the information you've evaluated, is then delivered into the same compiler. Some common open-source generators include the FreeVASIC compiler. You can also use open-source tools like Visual Studio.
History of source code generators
As with any new technology, source code generation has pros and cons. If used without any control, they can be somewhat frustrating. They might not give you the attention to detail that you can achieve with programming languages. However, with the right code generation tool, you can build good products far easier than with conventional programming languages. Whenever new features, database schemas, or technology are introduced, there are some roadblocks that its users will have to overcome, but the result is worth these obstacles.
Several code generators are available out there, and they are used in .NET 5, and even Microsoft has started in this niche. A common example of a source code generation tool that was in use is ADO.NET's Entity Data Model Designer. It is a visual software development tool that lets you build tables and their relationships. The table class might then be utilized in your generated code and will be automatically created. This saves you a ton of effort that would have been spent making numerous classes that were relatively similar for managing all of your entities. It also does not require any knowledge of programming languages.
Benefits of source code generation
Source code generation has several benefits that make it attractive to its users. Other than being able to be used even without knowing any programming languages, here are some of their main benefits:
- Saves time
Code generation can have a quicker turnaround for release. Because computers are automated devices, writing generated code may be very time-efficient using them. You won't have to do this yourself or memorize random information regarding your manual coding tasks. You also don't need to spend a lot of time learning a programming language.
- Fewer human mistakes
Patterns are used for developing applications. Machines can leverage these structures to eliminate manual procedures and comprehend common jobs. This results in significantly fewer errors than manually coding a program with a programming language.
- Code reuse
The generated code is adaptable to various applications. By doing so, we can save time and effort on both current and future initiatives. Recycling generated code can help you increase profitability and maintain consistency in your applications.
- Improved testing and standard
Testing using models can improve the quality of the custom code. Businesses can add tests for customizations and use tests to confirm that generated code works as intended. Custom code generation makes this easier and ensures better quality, and can improve performance.
- Stable architecture and consistency
Uniform configuration for large systems helps lower technological debt. Following organized training, talented developers can become more productive. Employing the same layout each time will make your generated code appear more professional and consistent. This is especially true for source code generation tools that construct a tree-like structure out of folders or files to make multiple navigating projects simpler. You might need to code every component separately when using conventional programming languages.
- Better documentation
Typically, documentation comes after development while using typical programming languages. You can create documentation using source code generation tools to guarantee consistency as you write the code. This will make things easier during the maintenance of your applications and in case of personnel changes.
Disadvantages of source code generation
There are some disadvantages to source code generation instead of using programming languages. These are some drawbacks of code generation you should be aware of:
- Black-box muddle
A black box mess occurs when a programmer cannot understand the code. The generated code must be user-friendly for developers to enable customizations. The custom code must not be so complex that people don't understand it.
- Complex models
The models that are employed in source code generation tools might get more and more complicated, especially with database schemas.
- Bloated code
Code generation tools might produce too much code. To ensure that the generated code is efficient, the custom code must pass reviews. If the custom code is unnecessarily lengthy, it can cause complications and confusion later.
How do code generators work?
The most prevalent method of generating HTML for webpages makes an excellent example of how code generators also work. There is some type of custom templates system in practically all contemporary web services that help you build applications. This is also how typical target frameworks also work.
To generate any code, such custom templates are used and given some information to work with. The template will typically include a way to perform common programming language operations like looping and selects as well as some method for processing the information. So, rather than spending a week manually coding very identical yet distinct HTML files, you can save a ton of time by using code generation.
What is the best code generator?
AppMaster is the perfect solution if you're looking for a good no-code software development tool to simplify your job. You may assign the same software project to a team of programmers as well as a no-code tool and receive better benefits from the no-code platform. For anything from straightforward operations to API integration, AppMaster can develop the generated code for you. The platform will complete your project more quickly, effectively, and for lower money.
You don't even have to question whether the generated code belongs to you. AppMaster allows you to take the rights to the source code. Because of the platform's extreme durability, you can use it to write the code for any application, even those requiring a complex backend. AppMaster is, without a doubt, one of the best code generators you can find.
How does AppMaster generate code?
The AppMaster platform can generate code because the platform contains all the requirements for the backend, database schemas, frontend, mobile applications, and even data structures. Our platform starts with a data model when the user clicks the publish button. It collects all data models. Based on these data models, it builds a standard database schema that will be placed in the application's backend binary. After the main table structure and SQL queries are built, and as soon as the database schema queries are completed, all business processes that are inside the system begin to generate code. Because the AppMaster platform does everything entirely in RAM, we have achieved a source code generation rate of 22,000 lines of code per second.
Once the bulk of the source code is generated, our intelligent algorithms (we have a trained ai) go through the entire source code's codebase and try to optimize all the inefficient bits generated in the main code generation pass.
Non-optimal places in the source code during the initial code generation were created because we focus on business processes that a person created, and as a rule, few users and developers can make a good abstraction level the first time and correctly place all the blocks and build the logic from the very beginning. But thanks to the fact that we have AI, we go through the so-called post-processing, go through the code base again and improve the entire code base. This causes the binaries to shrink, meaning they become smaller. They load faster. This can improve performance as they work better, and, in general, post-optimization works at the highest level for us.
One of the biggest benefits of code generation is that when requirements change, there is no need to rewrite the source code. Technically, our platform just takes all the conditions again and generates code for new features and applications. That is, no old code, no old dependencies, and no old requirements in this code generation. The platform does everything from scratch since it does it very quickly. This approach allows you to avoid technical debt completely, which is responsible for more than 30% of the budget in significant developments. So we are doing it faster and saving a huge amount of money on software product support, which lowers the total cost of ownership.
A typical code generation approach can be very simple, especially when all the requirements are already displayed inside our system, that is, models are generated, then business processes are generated, then endpoints, and finally, all this is optimized and compiled. However, the biggest challenge is changing user requirements. There is a lot of cross-dependency in the system. For example, business logic is very dependent on the data model, and endpoints depend on business logic and data models. UI elements, in turn, depend on everything, including the endpoints of the data model and business logic. And often, our platform automatically has to solve the problem of what to do when the user makes very big drastic changes. For example, in the data model, it deletes some entities, changes the type of fields, and so on. That is, our system, based on previous experience and our neural network, automatically rebuilds all connections in blocks of business logic, endpoints, and in some cases, UI elements too.
Conclusion
We have summarised some of the important things you should be aware of about source code generation. It is important to understand how source code generation works and what its pros and cons are. You can build better web services and applications by understanding this.
