One way to control this is to define a clipping path , beyond which graphics will not be drawn. In the first few lines, we create a circle as a path, then use the clip author to make that circle the limits for all subsequent graphics. Postscript is powerful enough to compute some very complicated graphics, e.
But, on the slow cheap CPUs embedded into many printers, such calculations could take a long time, giving an impression that the printer was no longer working. Postscript is powerful enough to go into infinite loops, so that the printer truly is no longer working until rebooted. Now, most Postscript programs are not written by human programmers but are generated by printer drivers. But a buggy or poorly designed printer driver can certainly generate programs that hang forever or that take inordinately long times to prepare a page.
Adobe eventually created PDF as a successor to Postscript. Like Postscript, PDF is actually a programming language, so that printer drivers are sending programs, not raw images to printers. No infinite loops. No extraordinarily long computations. It is still a stack-based programming language. Most of the PDF operators existed under different names in Postscript. In fact, the open-source Postscript processor ghostscript has long been able to can read and process PDF as well as the Postscript language it was originally designed to handle.
And, since these programs are not intended to be written or read by humans, the loss in readability is presumably not considered a problem. The source code of a PDF program need not be entirely in plain text.
After a short plain-text header, the bulk of the code can be compressed binary bytes, much as you would get by applying zip or other archiving programs. Again, this is pretty clearly aimed at reducing the size of the programs that need to be transferred to the printer. Most modern compression algorithms would have done as good or better a job of mapping repeatedly used command words onto single-byte values.
No unbounded loops means no infinite loops. The only iterations are fairly simple constructs that apply a procedure to each element of an finite array. With no recursion and no unbounded loops, PDF is clearly not Turing complete. Adobe deliberately sacrificed computing power in favor of predictability. But it is, to my knowledge, the only time that a prominent programming language has been deliberately hobbled so that it would not be Turing complete.
Contents: 1 Turing Completeness. Executing Postscript Programs Later in this section, I will provide links to several simple Postscript programs. So what does a programming language need to have in order to be Turing complete?
One of the key requirements is the scratchpad size be unbounded and that is possible to rewind to access prior writes to the scratchpad. Rather some systems approximate Turing-completeness by modeling unbounded memory and performing any possible computation that can fit within the system's memory. Ans is ' No ', you have to use javascript to perform addition. Mark i think what you are explaining is a mix between the description of the Universal Turing Machine and Turing Complete.
Though it doesn't take consideration for time or storage, as mentioned by others. Super-brief summary from what Professor Brasilford explains in this video. It has conditional branching i. Also, implies "go to" and thus permitting loop.
It gets arbitrary amount of memory e. We call a language Turing-complete if and only if 1 it is decidable by a Turing machine but 2 not by anything less capable than a Turing machine. Truly Turing-complete languages - ones that require the full computing power of Turing machines - are pretty rare. Perhaps the language of strings x. A common imprecise usage confuses Turing-completeness with Turing-equivalence.
Turing-equivalence refers to the property of a computational system which can simulate, and which can be simulated by, Turing machines. We might say Java is a Turing-equivalent programming language, for instance, because you can write a Turing-machine simulator in Java, and because you could define a Turing machine that simulates execution of Java programs.
According to the Church-Turing thesis, Turing machines can perform any effective computation, so Turing-equivalence means a system is as capable as possible if the Church-Turing thesis is true! Turing equivalence is a much more mainstream concern that true Turing completeness; this and the fact that "complete" is shorter than "equivalent" may explain why "Turing-complete" is so often misused to mean Turing-equivalent, but I digress.
In practical language terms familiar to most programmers, the usual way to detect Turing completeness is if the language allows or allows the simulation of nested unbounded while statements as opposed to Pascal-style for statements, with fixed upper bounds. Consider a player piano roll. The player piano can play a highly complicated piece of music, but there is never any conditional logic in the music.
It is not Turing Complete. The piano roll is guaranteed to halt every time. There is no such guarantee for a TM. As Waylon Flinn said :. I believe this is incorrect, a system is Turing complete if it's exactly as powerful as the Turing Machine, i. Can a relational database input latitudes and longitudes of places and roads, and compute the shortest path between them - no. This is one problem that shows SQL is not Turing complete.
Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. What is Turing Complete? Ask Question. Asked 13 years, 3 months ago. Active 7 months ago. Viewed k times. What does the expression "Turing Complete" mean? Can you give a simple explanation, without going into too many theoretical details?
Improve this question. Some very nice links at this SO question. Add a comment. Active Oldest Votes. Here's the briefest explanation: A Turing Complete system means a system in which a program can be written that will find an answer although with no guarantees regarding runtime or memory. Improve this answer. Mark Harrison Mark Harrison k gold badges silver badges bronze badges.
For further reading, see The Annotated Turing. Very approachable. No system is ever Turing-complete in practice, because no realizable system has an infinite tape. What we really mean is that some systems have the ability to approximate Turing-completeness up to the limits of their available memory. But Vi is the only computational engine ever needed in the world Is Emacs a Turning Machine too? XD — alem0lars. Someone recently showed that PowerPoint is Turing Complete too.
Show 6 more comments. Here is the simplest explanation Alan Turing created a machine that can take a program, run that program, and show some result. Prithvi Boinpally 7 7 silver badges 20 20 bronze badges. Raja Rao Raja Rao 4, 2 2 gold badges 24 24 silver badges 28 28 bronze badges. The idea that there would even be a term for this kind of machine makes a lot more sense when I remember Turing and other early computer scientists would build a specific machine each time they wanted to solve a specific problem.
Thank you for the context, Raja. How JavaScript can be Turing Complete? It lacks file system , proper multithreading API. It has tons of limitations, mainly due to its browser security sandbox nature. It's hardly can be called ' a programming language '. See how many variants of scripting abstraction exist react, typescript.. But js? I don't think so. JS is absolutely touring complete. MichaelIV To add to Bax's response, one could consider a modern computer to consist of several Turing machines that work together to allow for all of those nice things that you mention.
JS is absolutely Turing complete - but Turing completeness is a lower bar than you might be imagining. It doesn't mean it's optimal for any computation. Many SREs or DevOps people have horror stories of configurations produced by general-purpose languages that were so complicated that it required a major effort to figure out why a given command line flag had been set to a given value.
In most cases, a non-universal language can save you from your worst impulses by making the connections between items much clearer, sometimes clear enough that you can make the language implementation or a separate debugging tool track the source of values and report on what inputs went into them, or analyze a program and report which portions of the output could be affected if an input value were to change.
It also serves to discourage you from putting business logic into the configuration when it should be in the software being configured. Another area ripe for non-universal DSLs is query languages. However, you can easily stray into universal territory without knowing it. SQL, for instance, is Turing complete due to the fact that common table expressions can recursively call themselves, thus allowing unbounded looping, even though the rest of the language is not.
Again, limiting looping is an important strategy, but the most common way to go about it in this domain is to carefully curate and structure queries in such a way that the only loops available are implicit.
Diving deeper into program language theory is a great way to grow as a developer. Here, we go through the essentials of using compilers in language design.
We might decide to create a language that consists of a pipeline of processing stages in the style of the Unix command line. If the operations available for a stage are limited in how many passes over the data they can make and most typical operations can be done in a single pass , then we can show that no program can loop forever. Most operations that one would want to do on log data, such as filtering or aggregating across time, can be easily phrased in this pipeline style, so despite this restriction, we can still query the logging system effectively.
Here, one of the largest benefits is predictable execution time. Even in cases where you allow joins or other operations that are nonlinear in nature, their execution time can be bounded if chosen properly. If the individual pipeline operations are also distributable, those stages can again be distributed across multiple tasks if necessary. This is far more difficult if the language allows arbitrary combinations of operations. Adam Vartanian is a software engineer at Google, a maintainer of Conscrypt , a board member at General Mischief Dance Theater , and a proud father.
He prefers tau over pi and pie over cake. You can unsubscribe at any time. Please see our Privacy Policy for more information. Also in this issue A crash course in compilers Diving deeper into program language theory is a great way to grow as a developer. About the author Adam Vartanian is a software engineer at Google, a maintainer of Conscrypt , a board member at General Mischief Dance Theater , and a proud father.
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