Concatenative Programming Languages - Pros and Cons
Tags: functional, programming, computerscience, learning
Published: 2023-05-03 16:17:11

It was hard to find information online about the advantages and disadvantages of [Concatenative Programming Languages](https://en.wikipedia.org/wiki/Concatenative_programming_language), so I made this article with the help of ChatGPT. I hope someone may find it useful, and that it pops up in search results for the next person.

# Advantages  / Pros:
 
1. **Composition by concatenation:** Concatenative languages allow for programs to be composed by simply concatenating small functions together. This leads to highly modular and composable code, where larger programs can be built from smaller, reusable parts. This approach to composition is often referred to as "point-free" programming.

2. **Implicit data-flow:** Concatenative programming languages maintain a persistent data structure on the stack, making it easy to see the flow of data through a program. This can make it easier to reason about the behavior of a program, and can simplify program design by eliminating the need for explicit data-flow control constructs.

3. **Simple syntax:** Concatenative programming languages often have a simple syntax that is easy to read and write. This can make them more approachable for new programmers or those transitioning from other programming paradigms.

4. **Powerful code factoring:** Because functions are composed by concatenating other functions together, it is easy to factor out common patterns in code into reusable functions. This can lead to more concise and maintainable code.

5. **Dynamic program construction:** Concatenative languages allow for dynamic construction of programs at runtime, which can be useful for building programs that generate other programs or perform dynamic code generation.

# Disadvantages / Cons:

1. **Steep learning curve:** The syntax and semantics of concatenative programming languages can be unfamiliar and difficult to learn, especially for programmers who are used to imperative or object-oriented programming paradigms.

2. **Debugging challenges:** Concatenative programming languages can be challenging to debug, since the program execution model is based on the stack and the state of the program is implicit. Meaning: Each function takes the whole program as input, and thus when debugging then _every_ preceding function (potentially created by another person) could have mutated the program state to create the bug you're currently concerned about way further down in the code. See [example](https://www.reddit.com/r/programming/comments/7jjr5/the_joy_of_concatenative_languages_part_2/c06tzko/))

3. **Limited tooling:** Since concatenative programming languages are not as widely used as more established paradigms, they often have limited tooling and support, making it harder to find libraries, documentation, and community support.

4. **Performance issues:** Some concatenative programming languages may not be as optimized for performance as other languages, due to the overhead of stack manipulation and the need to maintain a persistent data structure on the stack.

5. **Lack of expressiveness:** While concatenative programming languages can be very expressive for certain types of problems, they may not be as expressive for other types of problems, especially those that require more complex control flow or data structures.

# Examples

Examples of some Concatenative Programming Languages:

1. **Forth:** Forth is one of the oldest and most well-known concatenative languages. It was first released in the late 1960s and has since been used in a wide variety of embedded systems, scientific instrumentation, and other applications.

2. **Joy:** Joy is a purely functional concatenative language that is notable for its simplicity and expressive power. It was developed in the late 1980s and has since gained a small but dedicated following.

3. **Factor:** Factor is a modern concatenative language that is known for its expressive syntax and powerful metaprogramming capabilities. It features a large standard library and is often used for web development, data processing, and other general-purpose programming tasks.

4. **Cat:** Cat is a simple, lightweight concatenative language that is designed to be easy to learn and use. It features a minimalistic syntax and is often used for scripting and automation tasks.

5. **Kitten:** Kitten is a statically-typed concatenative language that is designed to be easy to learn and use. It features a modern syntax and is often used for systems programming, scripting, and web development.

# Conclusion

Concatenative programming languages can be a powerful tool for solving certain types of problems, and building modular, reusable, and expressive programs. They can be particularly well-suited for domains such as parsing, compiler construction, and other areas where the flow of data is central to the problem. But they may not be the best choice for all situations, and their use requires careful consideration of the trade-offs involved.

# Addendum:

Since most concatenative languages are stack-based, the following points are also worth considering.

Here are some fundamental limitations of stack-based languages based on the provided search results:

**Limited Capacity:**

Stack data structures have a fixed capacity, which can be a constraint when the number of elements to be stored is unknown or extensive

This limitation can lead to stack overflow if too many elements are pushed onto the stack, resulting in potential data loss


**No Random Access:**

Stack data structures do not allow for random access to elements; they only support adding and removing elements from the top of the stack

Accessing an element in the middle of the stack requires removing all elements above it, which can be inefficient for certain operations


**Memory Management:**

Stack data structures use contiguous memory blocks, which can cause memory fragmentation when elements are frequently added and removed


This memory management approach may not be optimal for scenarios where dynamic memory allocation is crucial.


**Not Suitable for All Applications:**

Stack-based languages may not be suitable for applications requiring access to elements in the middle of the stack, such as searching or sorting algorithms

Their design, focused on LIFO (Last In First Out) operations, may limit their applicability in certain problem domains.

**Recursive Function Call Limitations:**

While stack data structures support recursive function calls, excessive recursion can lead to stack overflow and program termination

This limitation restricts the depth of recursion that can be effectively handled by stack-based languages.

# Further reading

Some great presentations on Concatenative Programming Languages that I've found:

[Stanford Seminar - Concatenative Programming: From Ivory to Metal](https://youtu.be/_IgqJr8jG8M) (From the creator of Kitten)

[Stian Veum Møllersen Revisting Concatenative Languages with Creative Programming - Code Mesh 2017](https://youtu.be/faHB4MGQIG8) (From the creator of [Ait](https://www.youtube.com/watch?v=o5Dc_UQhP3s) [lang](https://functional-art.org/2017/ait))

[Church Encoding in Concatenative Programming Languages (Teodor Ande Elstad)](https://www.youtube.com/watch?v=TcveznrwYtk) (From the creator of STCK)

["Gershwin: Stack-based, Concatenative Clojure" by Daniel Gregoire (2013)](https://youtu.be/0M0djR1M65o)