I have an old piece of Fortran f77 code that I would like to understand and edit for future reuse. For that purpose, I would like this code to be translated to either C or Matlab / Octave language. I have found an instance of f2c exe online, but it wouldn't run because of inappropriate OS ( my OS is Win 7 x64, f2c wanted older x32 ).
My main concern is being able to understand the code. Translation in terms of execution efficiency is not of importance. I am open to any suggestion, apart from learning Fortran 77. I am aware of that option myself, but would do it only as a last resort. Thank you.
Just learn Fortran. The output of machine-translated code may well be functionally correct and suitable for compilation and execution, but it's going to be really hard to understand and maintain. (Just look at what generated code targeting a single language, like the output of a GUI builder wizard, looks like.) In particular, while Matlab is built on Fortran, its idioms at the M-code level are different enough that it would be pretty incomprehensible. If you already know C or any other Algol-like language, picking up Fortran is not that hard. And the idioms and features that are particular to Fortran – that is, the new stuff you'd have to learn – are probably going to be especially weird and incomprehensible when sent through a translator.
The one translator that might actually be useful is a Fortran 77 -> Fortran 90 translator. The modern '90 dialect would be easier to learn and more succinct, and since the translation is within the same language family the output probably wouldn't be too ugly.
Since are using Octave, you can call Fortran code, there is no need to rewrite it. You will need to write a very simple C++ wrapper to it but Octave already provides macros to do all of the hard work. It is all documented on the manual. Actually, Octave itself calls on many fortran subroutines, so this is perfectly normal.
If you want to modify it, you should be learning Fortran then.
Related
I want to learn "old school" programming. A friend suggested Q BASIC.
But another person told me Quick Basic. I want to practice programming
in the OLD Dos operating system.
What is the difference between the two Q Basic and Quick Basic?
Differences between QBasic and QuickBasic:
QBasic is the slimmed-down version of QuickBasic.
Compared to QuickBasic, QBasic is limited as it lacks a compiler.
Therefore QBasic cannot be used to produce executables (.exe files).
The source code (usually files with .bas extension) can only be executed immediately by the built-in QBasic interpreter.
Furthermore, QuickBasic has a more extensive command set than QBasic.
Does choosing a programming language decide performance when all of it is compiled to some 1's and 0's
Eg: printf (in C) vs cout (C++) vs print (in Python)
Do all of the above have same binary compiled code ?
Appreciate any help in understanding this concept of programming language and role on hardware in detail! Thanks in advance
The choice of programming language can have many impacts on the performance of your code, how portable it is, the comparability and among other things, how easily the objective can be put into code. To answer you question directly, C and C++ would likely produce the 'same binary' when printing an output, if they were both done for the same target environment. Python is different because it is an interpreted language, meaning the code is read by a program written in code native to the architecture and acted upon accordingly. Python is something of an edge case in this regard because it is technically compiled at execution time (and can be before distribution) but into an intermediate code similar in principle to Java byte code that is only understood by the Python interpreter.
The difference you bring up between lower language's like C and higher ones like Java, Python and even JavaScript is the nature of their execution being done by native hardware or by the interpreter. Language's running on bare metal are generally understood to be faster than those on interpreters as the interpreter takes time to understand the code and uses it's own system resources. Java tends to break this rule because it's interpreter is a full virtual machine that understands very simple byte code, making it competitive in speed to language's like C.
To what kind of binary code they are compiled depends on the compiler. For C and C++ there are dozens of different compilers which might generate different binary code. Besides that, most compilers even have optimization flags that influence the generated binary code a lot.
Python isn't even directly compiled into "machine code", it's compiled into bytecode for a python interpreter. The Python interpreter itself is a program that runs on the machine, then reads the python-bytecode and executes it probably by internally calling predefined functions (that already exist in machine-code)
I'm looking into installing a disassembler (or decompiler) on my Linux Mint 17.3 OS and I wanted to know what the difference is between a disassembler and a decompiler. I have a rough idea of what they are (the names are fairly self-explanatory), but they are still a bit confusing.
I've read that a disassembler turns a program into assembly language, which I don't know, so it seems kind of useless to me. I've also read that a decompiler turns a 'binary file' into its source code. What exactly is a binary file?
Apparently, decompilers cannot decompile to C, only Python and other similar languages. So how can I turn a program into its original C source code?
A disassembler is a pretty straightforward application that transfers machine code into assembly language statements - This activity is the reverse operation that an assembler program does and is straightforward because there is a strict one-to-one relationship between machine code and assembly. A disassembler aims at a specific CPU. The original assembler that was used to create the executable is only of minor relevance.
A decompiler aims at recreating a compiled high-level language program from machine code into its original format - Thus trying the reverse operation of a C or Forth (popular languages for which de-compilers exist) compiler. Because there are so many high-level languages and thus so many ways in how original high-level language constructs could be expressed in machine code (even a lot of different strategies for the same language and construct, even in the same compiler, and even different strategies depending on the compiler mode and situation), this operation is much more complex and very dependent on the original compiler (and maybe even the command line that was used, it's chosen optimization level and also the used version).
Even if all that fits, most of the work of a decompiler is educated guessing and will most probably never reach a point where it can reconstruct the original program in its source code form 100% - It will rather end up with a version of source code that could have been the original program.
I wish that John McCarthy was still alive, but...
From LISP 1.5 Programmer's Manual :
LISP can interpret and execute programs written in the form of S-
expressions. Thus, like machine language, and unlike most other higher
level languages, it can be used to generate programs for further
execution.
I need more clarification about how machine language can used to generate programs and how Lisp can do it?
All that is saying is that machine code can directly write machine instructions to memory and jump to those instructions to execute them; this is the basis of many attack vectors to break into software, in fact.
The point is, when you're writing machine code, it's easy to generate machine code. But when you're writing in a compiled language like C, you can't just generate C code at run time and then execute it - unless your program includes a C compiler.
Lisp - and, these days, many other languages, especially "scripting languages" like Perl, Python, Ruby, Tcl, Javascript, and command shells - have the ability to execute code that is generated at runtime. In Lisp, since code and data have the same structure, this is usually less work than it is in the other languages, where the code to be evaluated is generally a string that has to be parsed. (Though Perl has the ability to eval a block instead of a string, which lets the compiler do the parsing ahead of time for literal code.)
A machine language can alter itself while running. The last assembly programming i did was for MS DOS and resident program that i used to run before testing other programs. When my program misbehaved, a keystroke switched to the resident program and could peek into the running program and alter it directly before resuming. It was quite handy since I didn't have a debugger.
LISP had this from the very beginning since it was originally interpreted. You could change the definition of a function while you were running and the whole langugage was always available at runtime, even eval and define. When it started getting compiled it wasn't compiled like Algol, but partially, allowing for interpreted and compiled code to intermix at the same time. The fact that its code structure was list structure and that symbols are a data type contributed to this.
Last interview I saw with McCarthy he was asked about what he thought of modern programming languages (Not LISP family but the Algol family language Ruby, that is said to be influenced by LISP), and before answering he asked if they could represent code as data (like list structure). Since it didn't, Ruby is still behind what LISP was in the 60s in his opinion.
Many new programming languages are emerging in the Algol family and some of the most promising ones, like Perl6 and Nemerle, are getting closer to the features LISP had in the 60s.
Machine language programs can fill memory regions with arbitrary bytes. Then they can just jump to the start of such region which will thus get executed right away.
Lisp language programs can easily create arbitrary S-expressions in memory, using cons. Then they can just call eval on these S-expressions to evaluate (interpret) them.
High level languages programs can easily fill memory regions with characters representing new code in the language's syntax. But they can not run such a code.
I am totally a newbie in Matlab
I want to ask that when we write a program in Matlab software or IDE and save it with a
.m (dot m) file and then compile and execute it, then that .m (dot m) file is converted into which file? I want to know this because i heard that matlab is platform independent and i did google this but i got converting matlab file to C, C++ etc
Sorry for the silly question and thanks in advance.
Matlab is an interpreted language. So in most cases there is no persistent intermediate form. However, there is an encrypted intermediate form called pcode and there are also the MATLAB compiler and MATLAB coder which delivers code in other high level languages such as C.
edit:
pcode is not generated automatically and should be platform/version independent. But it's major purpose is to encrypt the code, not to compile it (although, it does some partial compilation). To use pcode, you still need the MATLAB environment installed, so in many ways it acts like interpreted code.
But from your follow-up question I guess you don't quite understand how MATLAB works. The code gets interpreted (although with a bit of Just-In-Time Compilation), so there is no need for a persistent intermediate code file: the actual data structures representing your code are maintained by MATLAB. In contrast to compiled languages, where your development cycle is something like "write code, compile & link, execute", the compilation (actually: interpretation) step is part of the execution, so you end up with "write code, execute" in most of the cases.
Just to give you some intuitive understanding of the difference between a compiler and an interpreter. A compiler translates a high level language to a lower level language (let's say machine code that can be executed by your computer). Afterwards that compiled code (most likely stored in a file) is executed by your computer. An interpreter on the other hand, interprets your high level code piece by piece, determining what machine code corresponds to your high level code during the runtime of the program and immediately executes that machine code. So there is no real need to have a machine code equivalent of your entire program available (so in many cases an interpreter will not store the complete machine code, as that is just wasted effort and space).
You could look at interpretation more or less as a human would interpret code: when you try to manually determine the output of some code, you follow the calculations line by line and keep track of your results. You don't generally translate that entire code into some different form and afterwards execute that code. And since you don't translate the code entirely, there is no need to persistently store the intermediate form.
As I said above: you can use other tools such as MATLAB coder to convert your MATLAB code to other high languages such as C/C++, or you can use the MATLAB compiler to compile your code to executable form that depends on some runtime libraries. But those are only used in very specific cases (e.g. when you have to deploy a MATLAB application on computers/embedded devices without MATLAB, when you need to improve performance of your code, ...)
note: My explanation about compilers and interpreters is a quick comparison of the archetypal interpreter and compiler. Many real-life cases are somewhere in between, e.g. Java generally compiles to (JVM) bytecode which is then interpreted by the JVM and something similar can be said about the .NET languages and its CLR.
Since MATLAB is an interpreter, you can write code and just execute it from the IDE, without compilation.
If you want to deploy your program, you can use the MATLAB compiler to create an stand-alone executable or a shared library that you can use in a C++ project. On Windows, MATLAB code would compile to an .EXE file or a .DLL file, respectively.