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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 .
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:
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.
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 ]
In information science, profiling refers to the process of construction and application of user profiles generated by computerized data analysis.. This is the use of algorithms or other mathematical techniques that allow the discovery of patterns or correlations in large quantities of data, aggregated in databases.
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