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In computer programming, profile-guided optimization (PGO, sometimes pronounced as pogo [1]), also known as profile-directed feedback (PDF) [2] or feedback-directed optimization (FDO), [3] is the compiler optimization technique of using prior analyses of software artifacts or behaviors ("profiling") to improve the expected runtime performance of the program.
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series .
A pluggable authentication module (PAM) is a mechanism to integrate multiple low-level authentication schemes into a high-level application programming interface (API). PAM allows programs that rely on authentication to be written independently of the underlying authentication scheme.
passwd is a command on Unix, Plan 9, Inferno, and most Unix-like operating systems used to change a user's password.The password entered by the user is run through a key derivation function to create a hashed version of the new password, which is saved.
A profiler can be applied to an individual method or at the scale of a module or program, to identify performance bottlenecks by making long-running code obvious. [1] A profiler can be used to understand code from a timing point of view, with the objective of optimizing it to handle various runtime conditions [ 2 ] or various loads. [ 3 ]
The first iteration of PRF uses Password as the PRF key and Salt concatenated with i encoded as a big-endian 32-bit integer as the input. (Note that i is a 1-based index.) Subsequent iterations of PRF use Password as the PRF key and the output of the previous PRF computation as the input: F(Password, Salt, c, i) = U 1 ^ U 2 ^ ⋯ ^ U c. where:
Social profiling is the process of constructing a social media user's profile using his or her social data. In general, profiling refers to the data science process of generating a person's profile with computerized algorithms and technology. [ 1 ]
Data profiling is the process of examining the data available from an existing information source (e.g. a database or a file) and collecting statistics or informative summaries about that data. [1] The purpose of these statistics may be to: Find out whether existing data can be easily used for other purposes