Is speed of the (main/only viable) implementation of an interpreted programming language a criteria today?
What would be the optimal balance between speed and abstraction?
Should scripting languages completely ignore all thoughts about performance and just follow the concepts of rapid development, readability, etc.?
I'm asking this because I'm currently designing some experimental languages and interpreters
Compiled Languages As a result, they tend to be faster and more efficient to execute than interpreted languages. They also give the developer more control over hardware aspects, like memory management and CPU usage.
Every line is read, analysed, and executed. Having to reprocess a line every time in a loop is what makes interpreted languages so slow. This overhead means that interpreted code runs between 5 - 10 times slower than compiled code. The interpreted languages like Basic or JavaScript are the slowest.
In general, interpreted programs are slower than compiled programs, but are easier to debug and revise. Other examples of interpreted languages include JavaScript and Python. Intermediate to computer-specific compiled programs and interpreted scripts are programs designed for runtime environments.
An interpreter takes very less time to analyze the source code. However, the overall time to execute the process is much slower. A compiler takes a lot of time to analyze the source code. However, the overall time taken to execute the process is much faster.
Speed is important, yes, but usually scripting languages are used in cases where speed of execution is outweighed by I/O costs, so it's not the end-all, be-all. Of far more importance is the language structure and features. Work on those first, then deal with execution speed.
That said, I think ultimately if you're looking to build a new general purpose language, you're going to go the route that most of them are going, which is pre-compilation into a bytecode and JIT compilation during execution.
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