Interpreters and Compilers: What Are They and How Are They Different?
The source code of high-level programming languages like PHP, Swift, and JavaScript looks a bit like natural language. You’ll see English words in such code and you’ll be able to understand some of its functionality, even if you don’t know the language itself. But such source code must be in a machine-readable format for the computer to run the final program.
To do this, the machine needs an intermediary to translate your code into something it can process. This intermediary could be an interpreter, a compiler, or an assembler. They all do a similar thing: they translate source code from a human-readable form into a machine-readable one. But how they do it is quite different.
What Is an Interpreter?
An interpreter reads each line of code, one at a time, and executes it immediately at run-time. An interpreter doesn’t wait for the entire source code to get converted into machine code before sending it to the CPU. Instead, it converts each code line into the interpreter-specific byte code and executes each instruction as it gets translated. While the execution task relies on the interpreter directly, the CPU powers the interpreter itself.
Since it parses and runs each line at a time, the process is often relatively slower. With that in mind, errors in interpreted programming languages are easy to spot since they provide instant feedback for each code line.
However, a setback of this behavior is that a run-time error crashes the program during execution, resulting in a poor user experience, especially if your project lacks adequate testing.
What Is a Compiler?
A compiler reads your source code and translates it into a machine-readable executable. Unlike an interpreter, it reads the entire source code in one go, generating machine code for later processing by the CPU. Since the compiler carries out this task just once, compiled programs are typically faster and more memory-efficient.
The compiler doesn’t account for run-time errors, though. Instead, it will flag certain errors at compile-time, which is usually better. This type of error shows up during development, not when the program starts running. However, bear in mind that run-time errors are still possible, even in compiled programs.
The Key Differences
Interpreters and compilers are both common, so it’s useful to know the key differences between them.
Code Execution: Input and Output Processing
An interpreter can only collect, translate, and execute each input per line. It runs each line of the source code sequentially as it comes, and the final output depends on what each line outputs during execution.
A compiler bundles the entire source code and translates it once only. So it takes your whole source code as input, which it converts and sends to the CPU to get an output.
Debugging and Error Traceability
For interpreted code, errors are more traceable since the interpreter can report them by directly referring to the original source. However, once there’s an error at any point during execution, the interpreter stops. So debugging errors can be a bit challenging since you need to reproduce them at run-time. It can even get worse if there’s inadequate run-time logging.
On the other hand, the run-time errors in a compiled language might be more difficult to trace since there is no interpreter to report on them. But errors you discover at compile-time are usually easier to deal with since the compiler will consistently identify them.
Most compiled languages also have a mechanism for detecting unused variables, type incompatibility, and faulty syntax, preventing these kinds of mistakes early on.
Performance and Speed
As expected, a compiler helps the machine run program code faster since the CPU only processes the code once. This isn’t so for interpreters, which translate each line at run-time.
Although there areprogramming principles you may useto optimize interpreted code, the interpreter will still spend time parsing and executing each line before moving to the next. However, compiler helpers are available to make interpreted languages faster.
For instance, the Chrome browser processes JavaScript using the V8 engine; this runs on the Just-In-Time (JIT) compiler. The Pyinstaller module is another helper that bundles and compiles a Python script into an executable package.
While these helpers are handy for bundling an interpreted language into a compiler, it doesn’t change the fact that the baseline translator is still an interpreter.
Memory Usage
The memory usage behavior of the interpreter and the compiler is relative and often depends on the source code and other factors. While some programmers argue that code chunking in interpreters reduces memory usage, interpreters also record aggregate memory usage.
For instance, when you examine thememory usage profile of your Python code, the amount of memory it consumes might surprise you.
Generally speaking, though, compiled programs require less run-time memory. Since they convert the entire source code into machine-readable code in advance, they give the CPU less work. This is in contrast to interpreters, which translate code at run-time only.
Programming Language Support
The interpreter and the compiler have a fair share ofprogramming language distribution. Some popular compiled languages include C, C#, Rust, and Golang. Interpreted languages are also popular, among them Python, JavaScript, and PHP.
More programmers tend to prefer interpreted languages. While JavaScript and Python use interpreters, they’re the two overall most desired languages, according to the2023 Stack Overflow Developer Survey. Rust and C# represent the compiled groups in the fifth and sixth positions.
Where Interpreted Languages Shine
Interpreters shine in these areas:
Where Compiled Languages Win
What about compilers? Here are some aspects their languages show some strength:
Choosing the Right Translator for Your Project
As you’ve seen, the compiler and the interpreter have their respective areas where they excel. While some programmers maintain that compiled languages are faster and better overall, others argue that performance depends on code structure and platform.
But more importantly, your choice of translator should also depend on several other factors besides their technical mechanisms. The ease of learning, community, and the project intent, are among the factors to consider while choosing between interpreted and compiled languages.
What are high-level and low-level programming languages? How does it affect learning to write code? Here’s what you need to know.
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