Self-modifying code

In computer science, self-modifying code is code that alters its own instructions, intentionally or otherwise, while it is executing.

Self-modifying code is quite straightforward to write when using assembly language (taking into account the CPU cache). It is also supported by some high level language interpreters such as SNOBOL4, the Lisp programming language, or the ALTER verb in COBOL. It is more difficult to implement on compilers but compilers such as Clipper and Spitbol make a fair attempt at it, and COBOL almost encourages it. One batch programming technique is to use self-modifying code^[1]. Most scripting languages such as Perl and Python are interpreted, which means that the program can generate new code and execute it; usually, this is done in a variable, but it can also be performed by writing out a new file and running it in the scripting language interpreter.

Usage o

Self-modifying code can be used for various purposes:

Semi-automatic Optimization of a state dependent loop.
Runtime code generation, or specialization of an algorithm in runtime or loadtime (which is popular, for example, in the domain of real-time graphics).
Altering of inlined state of an object, or simulating the high-level construction of closures.
Patching of subroutine address calling, as done usually at load time of dynamic libraries. Whether this is regarded as 'self-modifying code' or not is a case of terminology.
Evolutionary computing systems such as genetic programming.
Hiding of code to prevent reverse engineering, as through use of a disassembler or debugger.
Hiding of code to evade detection by virus/spyware scanning software and the like.
Filling 100% of memory (in some architectures) with a rolling pattern of repeating opcodes, to erase all programs and data, or to burn-in hardware.
Compression of code to be decompressed and executed at runtime, e.g. when memory or disk space is limited.
Some very limited instruction sets leave no option but to use self-modifying code to achieve certain functionality. For example, a "One Instruction Set Computer" machine that uses only the subtract-and-branch-if-negative "instruction" cannot do an indirect copy (something like the equivalent of "*a = **b" in the C programming language) without using self-modifying code.
Altering instructions for fault-tolerance

The second and third types are probably the kinds mostly used also in high-level languages, such as LISP.

Optimizing a state-dependent loop

Pseudocode example:

repeat N times {
  if STATE is 1
   increase A by one
  else
   decrease A by one

  do something with A
}

Self-modifying code in this case would simply be a matter of rewriting the loop like this:

 repeat N times {

  increase A by one
  do something with A
 }
 
 when STATE has to switch {
    replace the opcode "increase" above with the opcode to decrease
 }

Note that 2-state replacement of the opcode can be easily written as 'xor var at address with the value "opcodeOf(Inc) xor opcodeOf(dec)"'.

Choosing this solution will have to depend of course on the value of 'N' and the frequency of state changing.

Attitudes

Self-modifying code can either be seen as a feature like any other (or even as just delayed code-editing), or as a bad practice which makes code harder to read and maintain. In the early days of computer, self-modifying code was used often in order to reduce the usage of memory, which was extremely limited, and didn't pose any problem. It was also used to implement subroutine calls and returns when the instruction set only provided simple branching or skipping instructions to vary the control flow. This application is still relevant in certain ultra-RISC architectures, at least theoretically; see for example One instruction set computer. Donald Knuth's MIX architecture also used self-modifying code to implement subroutine calls.

Already, critical systems which are too complex for people to fully manage in real time, such as the Internet and electrical distribution networks routinely rely upon self-modifying behaviors (though not necessarily self-modifying code) in order to function acceptably.

Use as camouflage

Self-modifying code was used to hide copy protection instructions in 1980s disk based programs for platforms such as IBM PC and Apple II. For example, on an IBM PC (or compatible), the floppy disk drive access instruction 'int 0x13' would not appear in the executable program's image but it would be written into the executable's memory image after the program started executing.

Self-modifying code is also sometimes used by programs that do not want to reveal their presence — such as computer viruses and some shellcodes. Viruses and shellcodes that use self-modifying code mostly do this in combination with polymorphic code. Polymorphic viruses are sometimes called primitive self-mutators. Modifying a piece of running code is also used in certain attacks, such as buffer overflows.

Self-referential machine learning systems

Traditional machine learning systems have a fixed, pre-programmed learning algorithm to adjust their parameters. However, since the 1980s Jürgen Schmidhuber has published several self-modifying systems with the ability to change their own learning algorithm. They avoid the danger of catastrophic self-rewrites by making sure that self-modifications will survive only if they are useful according to a user-given fitness function or error function or reward function.

Operating systems

Because of the security implications of self-modifying code, all of the major operating systems are careful to remove such vulnerabilities as they become known. The concern is typically not that programs will intentionally modify themselves, but that they could be maliciously changed by an exploit.

As consequence of the troubles that can be caused by these exploits, an OS feature called W^X (for "write xor execute") has been developed which prohibits a program from making any page of memory both writable and executable. Some systems prevent a writable page from ever being changed to be executable, even if write permission is removed. Other systems provide a back door of sorts, allowing multiple mappings of a page of memory to have different permissions. A relatively portable way to bypass W^X is to create a file with all permissions, then map the file into memory twice. On Linux, one may use an undocumented SysV shared memory flag to get executable shared memory without needing to create a file. On Windows Vista and Windows XP the W^X protection is named Data Execution Prevention and can be disabled via the Control Panel.

Regardless, at a meta-level, programs can still modify their own behavior by changing data stored elsewhere (see Metaprogramming) or via use of Polymorphism.

Just-in-time compilers

Just in time compilers for Java, .NET, ActionScript 3.0 and other programming languages compile blocks of byte-code or p-code into machine code suitable for the host processor and then immediately execute them. Fabrice Bellard's Tiny C Compiler can and has been used as C-Just-in-Time-Compiler-Library, e.g. by TCCBOOT (a bootloader that can compile, load and run its operation system on-the-fly).

Graphics drivers for modern GPUs perform JIT-Compilation of DirectX or OpenGL/GLSL geometry and fragment shaders, and can thus be seen as self-modifying code, sometimes distributed over multiple processors and DSPs (or even self-modifying hardware).

Some CPU Architecture Emulators use similar techniques as JIT-Compilers (simulated instruction set as "programming language" that becomes compiled for the target processor).

Interaction of cache and self-modifying code

On architectures without coupled data and instruction cache (some ARM and MIPS cores) the cache synchronization must be explicitly performed by the modifying code (flush data cache and invalidate instruction cache for the modified memory area).

In some cases short sections of self-modifying code executes more slowly on modern processors. This is because a modern processor will usually try to keep blocks of code in its cache memory. Each time the program rewrites a part of itself, the rewritten part must be loaded into the cache again, which results in a slight delay, if the modified codelet shares the same cache line with the modifying code, as is the case when the modified memory address is located within a few bytes to the one of the modifying code.

The cache invalidation issue on modern processors usually means that self-modifying code would still be faster only when the modification will occur rarely, such as in the case of a state switching inside an inner loop.^{[citation needed]}

(Actually, all self-modifying code involves some performance penalty over static code, simply due to the time necessary to perform the rewrite.)

Most modern processors load the machine code before they execute it, which means that if an instruction that is too near the instruction pointer is modified, the processor will not notice, but instead execute the code as it was before it was modified. See Prefetch Input Queue (PIQ). PC processors have to handle self-modifying code correctly for backwards compatibility reasons but they are far from efficient at doing so^{[citation needed]}.

Example

NASM-syntax self-modifying x86-assembly algorithm that determines the size of the Prefetch Input Queue

 code_starts_here:
   xor cx, cx                  ; zero register cx
   xor ax, ax                  ; zero register ax
 
begin:
   cmp ax, 1                   ; check if ax has been altered
   je found_size               ; if it has, we found the size of PIQ

   mov [nop_field+cx], 0x90    ; stores a "nop" at address nop_field + cx
                               ; (0x90 = machine code for "nop" = no operation)
   inc cx                      ; increase register cx

   jmp far flush_queue         ; this forces the processor to reload its
flush_queue:                   ; instruction decoding queue.

   mov [nop_field+cx], 0x40    ; stores a "inc" at address nop_field + cx
                               ; (0x40 = machine code for "inc ax" = increase ax)

    ; We now try to execute our "inc ax" inside the nop-field. If the content of
    ; register cx was too low, we would have written the "inc ax" in a memory location
    ; that the processor already had cached in its instruction decoding queue (PIQ).
    ; If the content of cx has grown large enough the "inc ax" will be written in a
    ; memory cell that has not been cached, and the test just after "begin" will turn
    ; out to be true, and thus we have the size of the PIQ...
    ; (Notice that a context switch during the run will destroy the cache and make 
    ; this algorithm return a wrong value.)

nop_field:
   nop times 256               ; A field of 256 no operation-codes
   jmp begin                   ; the field ends with a jump to "begin"
found_size:

   ;    register cx now contains the size of the PIQ

Henry Massalin's Synthesis kernel

The Synthesis kernel written by Dr. Henry Massalin as his PhD. thesis is commonly viewed to be the "mother of all self-modifying code." {{citation}}: Empty citation (help) Massalin's tiny Unix kernel takes a structured, or even object oriented, approach to self-modifying code, where code is created for individual quajects, like filehandles; generating code for specific tasks allows the Synthesis kernel to (as a JIT interpreter might) apply a number of optimizations such as constant folding or common subexpression elimination.

The Synthesis kernel was extremely fast, but was written entirely in assembly. The resulting lack of portability has prevented Massalin's optimization ideas from being adopted by any production kernel. However, the structure of the techniques suggests that they could be captured by a higher level language, albeit one more complex than existing mid-level languages. Such a language and compiler could allow development of extremely fast operating systems and applications.

Paul Haeberli and Bruce Karsh have objected to the "marginalization" of self-modifying code, and optimization in general, in favor of reduced development costs; drawing a parallel to the "heavy religious atmosphere" which the Italian Futurist movement rebelled against.

External links

Using self modifying code under Linux
self modifying C code
"Synthesis: An Efficient Implementation of Fundamental Operating System Services" -Henry Massalin's PhD thesis on the Synthesis kernel
Futurist Programming
Certified Self-Modifying Code
Jürgen Schmidhuber's publications on self-modifying code for self-referential machine learning systems
PCASTL: by Parent and Childset Accessible Syntax Tree Language

^ www.csd.net/~cgadd/knowbase/DOS0019.HTM

[1] www.csd.net/~cgadd/knowbase/DOS0019.HTM

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