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In software, a stack buffer overflow or stack buffer overrun occurs when a program writes to a memory address on the program's call stack outside of the intended data structure, which is usually a fixed-length buffer. [1] [2] Stack buffer overflow bugs are caused when a program writes more data to a buffer located on the stack than what is ...
If we compute the gaps between adjacent values in a list of strictly increasing integers and encode them using unary coding, the result is a bit array with a 1 bit in the nth position if and only if n is in the list. The implied probability of a gap of n is 1/2 n.
Visualization of a software buffer overflow. Data is written into A, but is too large to fit within A, so it overflows into B.. In programming and information security, a buffer overflow or buffer overrun is an anomaly whereby a program writes data to a buffer beyond the buffer's allocated memory, overwriting adjacent memory locations.
If the type "short" is stored in two bytes of memory then each member of the data structure depicted above would be 2-byte aligned. Data1 would be at offset 0, Data2 at offset 2, and Data3 at offset 4. The size of this structure would be 6 bytes.
In computer science, a data buffer (or just buffer) is a region of memory used to store data temporarily while it is being moved from one place to another. Typically, the data is stored in a buffer as it is retrieved from an input device (such as a microphone) or just before it is sent to an output device (such as speakers); however, a buffer may be used when data is moved between processes ...
Canaries or canary words or stack cookies are known values that are placed between a buffer and control data on the stack to monitor buffer overflows. When the buffer overflows, the first data to be corrupted will usually be the canary, and a failed verification of the canary data will therefore alert of an overflow, which can then be handled, for example, by invalidating the corrupted data.
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers:
MessagePack is more compact than JSON, but imposes limitations on array and integer sizes.On the other hand, it allows binary data and non-UTF-8 encoded strings. In JSON, map keys have to be strings, but in MessagePack there is no such limitation and any type can be a map key, including types like maps and arrays, and, like YAML, numbers.