What are the key differences between compiled and interpreted programming languages?

2 Interpreted languages

Interpreted languages are those that do not need to be compiled into machine code before they can be executed by the computer. Instead, they are read and executed by a program called an interpreter, which translates each line of code into machine instructions on the fly. The advantage of interpreted languages is that they are more portable, as they can run on any machine that has the interpreter installed. They are also easier to modify, debug, and test, as they do not require a compilation step. However, the disadvantage is that they are slower, less efficient, and less secure than compiled languages, as they need to be parsed and interpreted at run time. Some examples of interpreted languages for testing are Python, Ruby, and Perl.

3 Hybrid languages

Hybrid languages are those that combine elements of both compiled and interpreted languages. They usually have a two-stage process, where the source code is first compiled into an intermediate code, and then interpreted by a virtual machine or a runtime environment. The intermediate code is platform-independent, which means it can run on any machine that has the virtual machine or the runtime environment installed. The advantage of hybrid languages is that they offer a balance between performance, portability, and flexibility. However, the disadvantage is that they may have some overhead or compatibility issues due to the intermediate layer. Some examples of hybrid languages for testing are C#, Java, and Python.

4 Static vs dynamic typing

Another important difference between programming languages for testing is whether they are statically or dynamically typed. Static typing means that the data types of variables are checked and enforced at compile time, while dynamic typing means that the data types of variables are checked and enforced at run time. Static typing can help prevent errors, improve performance, and enable better tool support, but it can also make the code more verbose and rigid. Dynamic typing can make the code more concise and flexible, but it can also introduce errors, reduce performance, and hinder tool support. Some examples of statically typed languages for testing are C, C++, and Java, while some examples of dynamically typed languages for testing are Python, Ruby, and Perl.

5 Scripting vs programming languages

Another common distinction between programming languages for testing is whether they are scripting or programming languages. Scripting languages are those that are designed for writing short, simple, and reusable scripts that automate tasks or interact with other programs. Programming languages are those that are designed for writing complex, structured, and standalone programs that perform logic or computation. Scripting languages are usually interpreted, dynamically typed, and high-level, while programming languages are usually compiled, statically typed, and low-level. Scripting languages can be easier to learn, write, and test, but they can also be less efficient, scalable, and robust. Programming languages can be more powerful, fast, and reliable, but they can also be more difficult, verbose, and error-prone. Some examples of scripting languages for testing are Python, Ruby, and Perl, while some examples of programming languages for testing are C, C++, and Java.

6 Choosing the best language for testing

There is no definitive answer to which programming language is the best for testing, as it depends on various factors, such as the type, scope, and complexity of the test, the requirements, preferences, and skills of the tester, the availability, compatibility, and support of the tools and frameworks, and the trade-offs between speed, quality, and cost. However, some general guidelines are to choose a language that is widely used, well documented, and easy to integrate with the software under test, that has a rich set of libraries, modules, and packages for testing purposes, that suits the level of abstraction and control needed for the test, and that matches the coding style and standards of the team and the project.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?