Name Date Size #Lines LOC

..29-Nov-2024-

README.mdH A D05-Jul-20204.5 KiB9573

build.infoH A D05-Jun-2021194 54

defn_cache.cH A D19-Jun-20243.9 KiB13798

property.cH A D19-Nov-202428 KiB926629

property_err.cH A D17-Jun-20211.6 KiB4732

property_local.hH A D19-Jun-20241.9 KiB5634

property_parse.cH A D19-Jun-202421.6 KiB764634

property_query.cH A D12-Nov-20212.6 KiB8357

property_string.cH A D22-Jun-20228 KiB272212

README.md

1Selecting algorithm implementations by properties
2=================================================
3
4Properties are associated with algorithms and are used to select between
5different implementations dynamically.
6
7This implementation is based on a number of assumptions:
8
9* Property definition is uncommon.  I.e. providers will be loaded and
10  unloaded relatively infrequently, if at all.
11
12* The number of distinct property names will be small.
13
14* Providers will often give the same implementation properties to most or
15  all of their implemented algorithms.  E.g. the FIPS property would be set
16  across an entire provider.  Likewise for, hardware, accelerated, software,
17  HSM and, perhaps, constant_time.
18
19* There are a lot of algorithm implementations, therefore property
20  definitions should be space efficient.  However...
21
22* ... property queries are very common.  These must be fast.
23
24* Property queries come from a small set and are reused many times typically.
25  I.e. an application tends to use the same set of queries over and over,
26  rather than spanning a wide variety of queries.
27
28* Property queries can never add new property definitions.
29
30Some consequences of these assumptions are:
31
32* That definition is uncommon and queries are very common, we can treat
33  the property definitions as almost immutable.  Specifically, a query can
34  never change the state of the definitions.
35
36* That definition is uncommon and needs to be space efficient, it will
37  be feasible to use a hash table to contain the names (and possibly also
38  values) of all properties and to reference these instead of duplicating
39  strings.  Moreover, such a data structure need not be garbage collected.
40  By converting strings to integers using a structure such as this, string
41  comparison degenerates to integer comparison.  Additionally, lists of
42  properties can be sorted by the string index which makes comparisons linear
43  time rather than quadratic time - the O(n log n) sort cost being amortised.
44
45* A cache for property definitions is also viable, if only implementation
46  properties are used and not algorithm properties, or at least these are
47  maintained separately.  This cache would be a hash table, indexed by
48  the property definition string, and algorithms with the same properties
49  would share their definition structure.  Again, reducing space use.
50
51* A query cache is desirable.  This would be a hash table keyed by the
52  algorithm identifier and the entire query string and it would map to
53  the chosen algorithm.  When a provider is loaded or unloaded, this cache
54  must be invalidated.  The cache will also be invalidated when the global
55  properties are changed as doing so removes the need to index on both the
56  global and requested property strings.
57
58The implementation:
59
60* [property_lock.c](property_lock.c)
61  contains some wrapper functions to handle the global
62  lock more easily.  The global lock is held for short periods of time with
63  per algorithm locking being used for longer intervals.
64
65* [property_string.c](property_string.c)
66  contains the string cache which converts property
67  names and values to small integer indices.  Names and values are stored in
68  separate hash tables.  The two Boolean values, the strings "yes" and "no",
69  are populated as the first two members of the value table.  All property
70  names reserved by OpenSSL are also populated here.  No functions are
71  provided to convert from an index back to the original string (this can be
72  done by maintaining parallel stacks of strings if required).
73
74* [property_parse.c](property_parse.c)
75  contains the property definition and query parsers.
76  These convert ASCII strings into lists of properties.  The resulting
77  lists are sorted by the name index.  Some additional utility functions
78  for dealing with property lists are also included: comparison of a query
79  against a definition and merging two queries into a single larger query.
80
81* [property.c](property.c)
82  contains the main APIs for defining and using properties.
83  Algorithms are discovered from their NID and a query string.
84  The results are cached.
85
86  The caching of query results has to be efficient but it must also be robust
87  against a denial of service attack.  The cache cannot be permitted to grow
88  without bounds and must garbage collect under-used entries.  The garbage
89  collection does not have to be exact.
90
91* [defn_cache.c](defn_cache.c)
92  contains a cache that maps property definition strings to
93  parsed properties.  It is used by property.c to improve performance when
94  the same definition appears multiple times.
95