What is the minimal set of language features/structures that make it Turing-complete?
In general, for an imperative language to be Turing-complete, it needs:
For a lambda-calculus–based functional language to be TC, it needs:
There are of course other ways of looking at computation, but these are common models for Turing tarpits. Note that real computers are not universal Turing machines because they do not have unbounded storage. Strictly speaking, they are “bounded storage machines”. If you were to keep adding memory to them, they would asymptotically approach Turing machines in power. However, even bounded storage machines and finite state machines are useful for computation; they are simply not universal.
Strictly speaking, I/O is not required for Turing-completeness; TC only asserts that a language can compute the function you want, not that it can show you the result. In practice, every useful language has a way of interacting with the world somehow.
From a more practical standpoint: if you can translate all programs in a Turing-complete language into your language, then (as far as I know), your language must be Turing-complete. Therefore, if you want to check whether a language you designed is Turing-complete, you could simply write a Brainf*** to YourLanguage compiler and prove/demonstrate that it can compile all legal BF programs.
To clarify, I mean that in addition to an interpreter for YourLanguage, you write a compiler (in any language) that can compile any BF program to YourLanguage (keeping the same semantics, of course).
A system can only be considered to be Turing complete if it can do anything a universal Turing machine can. Since the universal Turing machine is said to be able to solve any computable function given time, Turing complete systems can, by extension, also do so.
To check to see if something is Turing complete, see if you can implement a Turing machine inside it. In other words, check to see if it can simulate the following:
These are the true minimum requirements for a system to be considered Turing complete. Nothing more, nothing less. If it can't simulate any of these in some fashion, it's not Turing complete. The methods other people proposed are only means to the end as there's several Turing complete systems that doesn't have those features.
Note that there's no known way to actually build a true Turing complete system. This is because there's no known way to genuinely simulate the limitlessness of the Turing machine's tape within physical space.
A programming language is turing complete if you can do any calculation with it. There isn't just one set of features that makes a language turing complete so answers saying you need loops or that you need variables are wrong since there is languages that has neither but are turing complete.
Alan Turing made the universal turing machine and if you can translate any program designed to work on the universal machine to run on your language it's also Turing complete. This also works indirectly so you can say language X is turing complete if all programs for turing complete language Y can be translated for X since all universal turing machine programs can be translated to a Y program.
The time complexity, space complexity, easy of input/output format and easy of writing any program is not included in the equation so such machine can theoretically do all calculations if the calculations are not halted by power loss or Earth being swallowed by the sun.
Usually to prove turing completeness they make an interpreter for any proven to be turing complete language but for it to work you need means of input and output, two things that are really not required for a language to be turing complete. It's enough that your program can alter it's state at startup and that you can inspect the memory after the program is halted.
To make a successful language it needs more than turing completeness though and this is true for even turing tarpits. I don't think BrainFuck would have been popular without
You can't tell if it'll loop infinitely or stop.
Explanation : Given some input, it's impossible to tell in every case (using another Turing machine) if the thing is going to loop infinitely or eventually going to stop, except by running it (which gives you an answer if it does stop, but not if it loops!).
This means that you have to be able to store a potentially unlimited amount data in some way - there has to be an equivalent to the infinite tape, no matter how convoluted! (Otherwise there are only a finite number of states and then you can check if you've been through that state previously and eventually stop). Generally, Turing machines can grow or shrink the size of their state by some controllable means.
Since Turing's original universal Turing machine has an unsolvable halting problem, your own Turing complete machine must also have an unsolvable halting problem.
Turing complete systems can emulate any other Turing complete system, so if you can build an emulator for some well known Turing complete system in your system, that proves that your system is also Turing complete.
For instance, suppose you want to prove that Snakes & Ladders is Turing complete, given a board with an infinitely repeated grid pattern (with a different version on top and left side). Knowing that the 2-counter Minsky machine is Turing complete (which has 2 unlimited counters and 1 state out of a finite number), you can construct an equivalent board where the X and Y position on the grid is the current value of the 2 counters and the current path is the current state. Bang! You just proved that Snakes & Ladders are Turing complete.
One necessary condition is a loop with a maximum iteration count that is not determined ahead of the iteration, or recursion where the maximum recursion depth is not determined ahead. As an example, for ... in ... loops as you find them in many newer languages are not enough to make the language turing complete (but they will have other means). Note that this doesn't mean limited number of iterations or limited recursion depth, but that the maximum iterations and recursion depth must be calculated ahead.
For example, the Ackermann function cannot be a computed in a language without these features. On the other hand, a lot of highly complex and highly useful software can be written without requiring these features.
On the other hand, with every iteration count and every recursion depth calculated ahead, not only can it be decided whether a program will halt or not, but it will halt.
i know this is not the formally correct answer, but once you take the 'minimal' out of 'Turing-complete' and put 'practical' back where it belongs, you'll see the most important features that distinguish a programming language from a markup language are
to test these assertions, start out with a markup language, say, HTML. we could invent an HTML+ with variables only, or conditionals only (MS did that with conditional comments), or some kind of loop construct (which in the absence of conditionals would probably end up as something like
the quest for minimality in logic and programming sure is important and interesting, but if i had to teach n00bies young or old 'what is programming' and 'how to learn to program', i'd hardly start out with the full breadth and width of the theoretical foundations of Turing completeness. the whole essence of cooking and programming is doing stuff, in the right order, repeating until ready, as your mom did it. that about sums it up for me.
then again, i never finished my CS.