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The array, set and dictionary binary types are made up of pointers - the objref and keyref entries - that index into an object table in the file. This means that binary plists can capture the fact that - for example - a separate array and dictionary serialized into a file both have the same data element stored in them.
In computer science, an associative array, map, symbol table, or dictionary is an abstract data type that stores a collection of (key, value) pairs, such that each possible key appears at most once in the collection.
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
A small phone book as a hash table. In computer science, a hash table is a data structure that implements an associative array, also called a dictionary or simply map; an associative array is an abstract data type that maps keys to values. [3]
^ ASN.1 has X.681 (Information Object System), X.682 (Constraints), and X.683 (Parameterization) that allow for the precise specification of open types where the types of values can be identified by integers, by OIDs, etc. OIDs are a standard format for globally unique identifiers, as well as a standard notation ("absolute reference") for ...
Tries are also disadvantageous when the key value cannot be easily represented as string, such as floating point numbers where multiple representations are possible (e.g. 1 is equivalent to 1.0, +1.0, 1.00, etc.), [12]: 359 however it can be unambiguously represented as a binary number in IEEE 754, in comparison to two's complement format.
The minimum information contained in a symbol table used by a translator and intermediate representation (IR) includes the symbol's name and its location or address. For a compiler targeting a platform with a concept of relocatability, it will also contain relocatability attributes (absolute, relocatable, etc.) and needed relocation information for relocatable symbols.
A derived format, directly suitable for speech recognition engines is also available as part of the distribution; this format collapses stress distinctions (typically not used in ASR). The following is a table of phonemes used by CMU Pronouncing Dictionary. [2]