- Compilers and interpreters are two different techniques used to execute programs by converting source code into machine code.
- Compilers break down code into tokens, create parse trees and abstract syntax trees, perform semantic analysis, optimize code, and generate machine code.
- Interpreters execute code line by line or statement by statement, allowing for dynamic typing and the possibility to generate code during runtime.
- Compilers tend to have better performance and efficiency, while interpreters offer greater flexibility and easier debugging.
- There are various types of compilers and interpreters, including bytecode compilers, cross-compilers, JIT interpreters, and embedded interpreters.
From microwaves and refrigerators to GPS and smartphones, there are many examples of technology most of us use every day without really knowing the details of how they work. You may think that programmers would be the exception. But many of them aren’t exactly sure how compilers and interpreters work, or their differences, even though they use them frequently. While this knowledge might not always be strictly necessary for your day-to-day duties, it will help choose an appropriate programming language and troubleshoot your code. With that said, let’s get into the difference between a compiler and an interpreter, and how each of them works.
What Are Compilers and Interpreters, and How Do They Work?
In simple terms, compilers and interpreters are two different techniques that we can use to execute programs. We understand the code we write, known as source code. However, computers can’t communicate using this code, so they convert it into binary digits, known as machine code. To this end, we use compilers and interpreters to enable computers to understand the code we’ve written. You can think of them as language processors since they process our code and convert it into a format computers can understand. Although they accomplish similar objectives, the processes by which they work are different. Let’s cover these next.
The Compilation and Interpretation Processes
Both processes have several moving parts, but they’re fairly easy to understand. Compilers and interpreters share some techniques, but there are some differences. We’ve summarized the steps involved in the following table and noted their applicability.
|First, the compiler breaks down your code into its smallest possible components, such as operators and keywords. These are called tokens.
|A parse tree is constructed to organize the tokens. This is done to verify the code structure and ensure relationships between tokens are correctly represented.
|Usually, an abstract syntax tree (AST) is then created from the parse tree. This is a more compact tree, where extraneous syntax details are removed and the essential meaning of the code is abstracted. ASTs can also be used to generate intermediate code, which can be optimized before the final generation.
|Semantic analysis is then carried out to resolve semantic errors. These occur when the code semantics don’t match up with the language rules or overall program logic. They can include type mismatches, incorrect scopes, and undeclared variables.
|The interpreter performs operations specified by each node of the AST or parse tree.
|Different optimization techniques are applied, aiming to reduce runtime and maximize efficiency.
|The machine code is generated, either from the AST or the intermediate code, depending on the process used. This machine code will then be ready to execute.
|Some interpreters will determine the expression and variable type at this stage to make the code more flexible.
|While executing code, the interpreter can produce an output, and potentially accept input.
What’s the Difference Between a Compiler and an Interpreter?
As we can see from the table, there are some commonalities between compilation and interpretation, but there are also some important differences. The overarching distinction between the two is that the compiler converts the code into machine code ahead of time, whereas the interpreter converts code either statement by statement or line by line as the code is running. As such, the interpreter repeats each step in the process for each line or statement.
Because the compiler has more opportunities to optimize before we execute the program, it tends to have better performance. On the other hand, interpreters generally offer greater flexibility, since they allow for dynamic typing, where variables can hold different value types while being executed. Interpreters can also generate code during runtime, which affords the possibility to dynamically optimize code on the fly. Debugging tends to be more efficient and prompt with interpreters as well because it tends to be easier to pinpoint errors to a specific line or statement.
Examples of Compiler and Interpreter
At this stage, examples of how compilers and interpreters work in practice would be useful. We’ll begin with a simple example of a compiler.
In this example, we use a compiler to translate an arithmetic expression into machine code. Consider the following code block in Python:
self.result = 0
def compile(self, expression):
tokens = expression.split('+')
for token in tokens:
self.result += int(token)
compiler = Compiler()
result = compiler.compile("2+3+4")
Here, we’re using a compiler to translate an arithmetic expression into machine code. We define the “Compiler” class and its initialization method. Then we initialize the “result” attribute to 0.
Next, we define the “compile()” method, which takes the “expression” parameter. We then split the expression by the “+” operator, resulting in “token” substrings which represent operands.
Following that, we initiate a for loop, which iterates over the tokens, converting them into integers using the “int()” function. The program adds these to the result attribute, summing up the operands.
Lastly, we create an instance of the compiler class, assign it to the “compiler” variable, and call the compile method. The console prints the result, as we can see in the image.
For illustrative purposes, we’re going to perform the same computation but using an interpreter instead, as per the following code:
def interpret(self, expression):
tokens = expression.split('+')
result = 0
for token in tokens:
result += int(token)
interpreter = Interpreter()
result = interpreter.interpret("2+3+4")
We define the class, but as “Interpreter” this time. We then define the “interpret()” method, which takes the “expression” parameter as input.
Similar to before, the program splits the expression and converts the tokens to integers. We create an instance of the interpreter class, assign it to the “interpreter” variable, and call the interpret method.
While we receive the same output in both examples, the processes are different. Whereas the compiler translates the expression into an executable form, the interpreter evaluates it line by line. As such, although the results are identical, the way the compilers and interpreters operate differs.
What Are the Pros and Cons of Compilers vs. Interpreters?
We’ve already touched on the advantages and disadvantages of compilers and interpreters, but the tables below summarize these for easy reference.
|Usually superior performance and efficiency due to pre-optimization.
|Debugging can be more difficult since the code must be compiled first.
|Theoretically very portable since programs can be delivered as bytecode or executables
|Recompilation or cross-compilers may be required to execute the program on a different platform.
|Greater flexibility, allowing for situations where frequent modification of code is required.
|Tend to be slower during execution than compilers.
|As the interpreter provides the runtime environment, the programs are easy to execute on different platforms.
|Fewer optimization opportunities.
|Debugging is simpler, as you receive immediate feedback and error messages can pinpoint issues.
|While it can write cross-platform code relatively easily, an interpreter will be required to execute it.
What Types of Compilers and Interpreters Are There?
We’ve discussed compilers and interpreters in general, but there are a lot of specific types within these categories. The tables below give a brief overview.
|Translates source code into a bytecode representation.
|This type can compile its own source code, allowing for an independent and self-sufficient compiler.
|This compiler type generates code intended for a different target platform than the platform where it originated.
|Pass over the source code only once.
|Pass over the source code several times, carrying out different operations and analyses at various stages.
|These handle lexical analysis, parsing, and semantic analysis.
|These handle optimization and code generation.
|We also known these as transpilers, and they convert source code from one language to another.
|Reverses the compilation process, producing the original source code.
|Modifies the source code while maintaining behavioral properties.
|Just-in-Time (JIT) compiler
|Compiles code in portions dynamically at runtime.
|Ahead-of-Time (AOT) compilation
|Compiles source code into an executable form ahead of runtime.
|Translates assembly language code into machine code.
|It generates code specifically for the hardware, without needing a virtual machine or extra runtime environment.
|Executes programs in bytecode format, i.e. JVM and CIL.
|This directly executes the code from traversing the AST.
|Threaded code interpreter
|Traverses instructions as memory addresses, usually from a table of “threads”.
|Used for scripting languages, and executing source code without any compilation.
|Just-in-Time (JIT) interpreter
|Combines dynamic compilation with interpretation by identifying frequently used code selectively and translating it into machine code.
|Interpreters that are integrated into large systems.
In summary, compilers and interpreters convert source code into executable machine code, but differ in their approach and applications. While compilers produce an executable form ahead of time, interpreters evaluate the code statement by statement or line by line at runtime. Compilation tends to provide better performance and efficiency but can be more platform-dependent. Interpretation generally provides more flexibility and debugging opportunities, but tends to be a slower process. Choosing between them depends on the constraints and specific requirements of your project, but in practice, compilers and interpreters often overlap, i.e. in Java, C#, or with Just-in-Time (JIT) compilation. In general, compilers are more suited to larger systems and situations where performance is critical, and interpreters are better in dynamic environments and in scripting languages.
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