Author: aherbert
Date: Mon Nov 11 11:07:47 2019
New Revision: 36697

Log:
Release Commons RNG v1.3 (from RC1)

Added:
    release/commons/rng/binaries/commons-rng-1.3-bin.tar.gz   (with props)
    release/commons/rng/binaries/commons-rng-1.3-bin.tar.gz.asc
    release/commons/rng/binaries/commons-rng-1.3-bin.tar.gz.sha512
    release/commons/rng/binaries/commons-rng-1.3-bin.zip   (with props)
    release/commons/rng/binaries/commons-rng-1.3-bin.zip.asc
    release/commons/rng/binaries/commons-rng-1.3-bin.zip.sha512
    release/commons/rng/source/commons-rng-1.3-src.tar.gz   (with props)
    release/commons/rng/source/commons-rng-1.3-src.tar.gz.asc
    release/commons/rng/source/commons-rng-1.3-src.tar.gz.sha512
    release/commons/rng/source/commons-rng-1.3-src.zip   (with props)
    release/commons/rng/source/commons-rng-1.3-src.zip.asc
    release/commons/rng/source/commons-rng-1.3-src.zip.sha512
Removed:
    release/commons/rng/binaries/commons-rng-1.2-bin.tar.gz
    release/commons/rng/binaries/commons-rng-1.2-bin.tar.gz.asc
    release/commons/rng/binaries/commons-rng-1.2-bin.tar.gz.sha1
    release/commons/rng/binaries/commons-rng-1.2-bin.tar.gz.sha256
    release/commons/rng/binaries/commons-rng-1.2-bin.zip
    release/commons/rng/binaries/commons-rng-1.2-bin.zip.asc
    release/commons/rng/binaries/commons-rng-1.2-bin.zip.sha1
    release/commons/rng/binaries/commons-rng-1.2-bin.zip.sha256
    release/commons/rng/source/commons-rng-1.2-src.tar.gz
    release/commons/rng/source/commons-rng-1.2-src.tar.gz.asc
    release/commons/rng/source/commons-rng-1.2-src.tar.gz.sha1
    release/commons/rng/source/commons-rng-1.2-src.tar.gz.sha256
    release/commons/rng/source/commons-rng-1.2-src.zip
    release/commons/rng/source/commons-rng-1.2-src.zip.asc
    release/commons/rng/source/commons-rng-1.2-src.zip.sha1
    release/commons/rng/source/commons-rng-1.2-src.zip.sha256
Modified:
    release/commons/rng/HEADER.html
    release/commons/rng/README.html
    release/commons/rng/RELEASE-NOTES.txt

Modified: release/commons/rng/HEADER.html
==============================================================================
--- release/commons/rng/HEADER.html (original)
+++ release/commons/rng/HEADER.html Mon Nov 11 11:07:47 2019
@@ -19,7 +19,7 @@
 <p>
     The most recent source and binary releases for the Apache Commons project 
are available from this
     directory listing. For older releases, please use the
-    <a href="http://archive.apache.org/dist/commons/";>archives</a>.
+    <a href="https://archive.apache.org/dist/commons/";>archives</a>.
 </p>
 
 <h2>Important Notices</h2>

Modified: release/commons/rng/README.html
==============================================================================
--- release/commons/rng/README.html (original)
+++ release/commons/rng/README.html Mon Nov 11 11:07:47 2019
@@ -14,9 +14,9 @@
  See the License for the specific language governing permissions and
  limitations under the License.
 -->
-<h1>Commons-RNG v1.2.</h1>
+<h1>Commons-RNG v1.3.</h1>
 
-<p>This is the 1.2 version of commons-rng. It is available in both binary and 
source distributions.</p>
+<p>This is the 1.3 version of commons-rng. It is available in both binary and 
source distributions.</p>
 
 
 <p><font color="red" size="+2">Note:</font>
@@ -28,9 +28,9 @@
 
 <p>The changes in this release are detailed in the release notes.</p>
 
-<p>Thank you for using <a 
href="http://commons.apache.org/proper/commons-rng/commons-rng/";>RNG</a>.</p>
+<p>Thank you for using <a 
href="https://commons.apache.org/proper/commons-rng/commons-rng/";>RNG</a>.</p>
 
-<p>From the Apache Commons Project<br><a 
href="http://commons.apache.org/";>http://commons.apache.org/</a></p>
+<p>From the Apache Commons Project<br><a 
href="https://commons.apache.org/";>https://commons.apache.org/</a></p>
 
 <h2><a name="mirrors">Download from your
     <a href="http://www.apache.org/dyn/closer.cgi/commons/";>nearest mirror 
site!</a></a></h2>
@@ -55,12 +55,12 @@
 
 <pre>Always test available signatures, <i>e.g.</i>,
 $ pgpk -a KEYS
-$ pgpv commons-rng-1.2-bin.tar.gz.asc
+$ pgpv commons-rng-1.3-bin.tar.gz.asc
 or,
 $ pgp -ka KEYS
-$ pgp commons-rng-1.2-bin.tar.gz.asc
+$ pgp commons-rng-1.3-bin.tar.gz.asc
 or,
 $ gpg --import KEYS
-$ gpg --verify commons-rng-1.2-bin.tar.gz.asc
+$ gpg --verify commons-rng-1.3-bin.tar.gz.asc
 </pre>
 <p>
\ No newline at end of file

Modified: release/commons/rng/RELEASE-NOTES.txt
==============================================================================
--- release/commons/rng/RELEASE-NOTES.txt (original)
+++ release/commons/rng/RELEASE-NOTES.txt Mon Nov 11 11:07:47 2019
@@ -1,4 +1,125 @@
 
+              Apache Commons RNG 1.3 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache 
Commons RNG 1.3
+
+The Apache Commons RNG project provides pure-Java implementation of 
pseudo-random generators.
+
+This is a minor release of Apache Commons RNG, containing a few new features 
and performance improvements. Apache Commons RNG 1.3 contains the following 
library modules:
+ commons-rng-client-api (requires Java 6)
+ commons-rng-core (requires Java 6)
+ commons-rng-simple (requires Java 6)
+ commons-rng-sampling (requires Java 6) The code in module 'commons-rng-core' 
should not be accessed directly by applications as a future release might make 
use of the JPMS modularization feature available in Java 9+.
+Additional code is provided in the following module:
+ commons-rng-examples (requires Java 9) It is however not part of the official 
API and no compatibility should be expected in subsequent releases.
+It must be noted that, due to the nature of random number generation, some of 
unit tests are bound to fail with some probability.
+The 'maven-surefire-plugin' is configured to re-run tests that fail, and pass 
the build if they succeed within the allotted number of reruns (the test will 
be marked as 'flaky' in the report).
+
+Changes in this version include:
+
+New features:
+o RNG-117:  Additional "XorShiRo" family generators. This adds 4 PlusPlus 
general purpose variants
+        of existing generators and 3 variants of a large state (1024-bit) 
generator. 
+o RNG-117:  "RandomSource": Support creating a byte[] seed suitable for the 
implementing
+        generator class. 
+o RNG-116:  "RandomSource": Expose interfaces supported by the implementing 
generator class
+        with methods isJumpable() and isLongJumpable(). 
+o RNG-111:  New "JenkinsSmallFast32" and "JenkinsSmallFast64" generators. 
+o RNG-19:  "JDKRandomWrapper": Wraps an instance of java.util.Random for use 
as a
+        UniformRandomProvider. Can wrap a SecureRandom to use functionality
+        provided by the JDK for cryptographic random numbers and platform 
dependent
+        features such as reading /dev/urandom on Linux. 
+o RNG-112:  New "DotyHumphreySmallFastCounting32" and 
"DotyHumphreySmallFastCounting64" generators. 
+o RNG-85:  New "MiddleSquareWeylSequence" generator. 
+o RNG-110:  Factory methods for Discrete and Continuous distribution samplers. 
The factory method
+        can choose the optimal implementation for the distribution parameters. 
+o RNG-84:  New Permuted Congruential Generators (PCG) from the PCG family.
+        Added the LCG and MCG 32 bit output versions of the XSH-RS and XSH-RR 
operations,
+        along with the 64 bit RXS-M-XS edition. Thanks to Abhishek Singh 
Dhadwal. 
+o RNG-102:  New "SharedStateSampler" interface to allow a sampler to create a 
new instance with
+        a new source of randomness. Any pre-computed state can be shared 
between the samplers. 
+o RNG-108:  Update "SeedFactory" to improve performance. 
+o RNG-99:  New "AliasMethodDiscreteSampler" that can sample from any discrete 
distribution defined
+        by an array of probabilities. Set-up is O(n) time and sampling is O(1) 
time. 
+o RNG-100:  New "GuideTableDiscreteSampler" that can sample from any discrete 
distribution defined
+        by an array of probabilities. 
+o RNG-98:  New "LongJumpableUniformRandomProvider" interface extends 
JumpableUniformRandomProvider
+        with a long jump method. 
+o RNG-97:  New "JumpableUniformRandomProvider" interface provides a jump 
method that advances
+        the generator a large number of steps of the output sequence in a 
single operation. A
+        copy is returned allowing repeat invocations to create a series of 
generators
+        for use in parallel computations. 
+o RNG-101:  New "MarsagliaTsangWangDiscreteSampler" that provides samples from 
a discrete
+        distribution stored as a look-up table using a single random integer 
deviate. Computes
+        tables for the Poisson or Binomial distributions, and generically any 
provided discrete
+        probability distribution. 
+o RNG-91:  New "KempSmallMeanPoissonSampler" that provides Poisson samples 
using only 1 random
+        deviate per sample. This algorithm outperforms the 
SmallMeanPoissonSampler
+        when the generator is slow. 
+o RNG-70:  New "XorShiRo" family of generators. This adds 6 new general 
purpose generators with
+        different periods and 4 related generators with improved performance 
for floating-point
+        generation. 
+o RNG-82:  New "XorShift1024StarPhi" generator. This is a modified 
implementation of XorShift1024Star
+        that improves randomness of the output sequence. The XOR_SHIFT_1024_S 
enum has been marked
+        deprecated as a note to users to switch to the new 
XOR_SHIFT_1024_S_PHI version. 
+o RNG-78:  New "ThreadLocalRandomSource" class provides thread safe access to 
random generators. 
+o RNG-79:  Benchmark methods for producing nextDouble and nextFloat. 
+o RNG-72:  Add new JMH benchmark ConstructionPerformance. 
+o RNG-71:  Validate parameters for the distribution samplers. 
+o RNG-67:  Instructions for how to build and run the examples-stress code. 
+o RNG-69:  New "GeometricSampler" class. 
+
+Fixed Bugs:
+o RNG-115:  "JDKRandom": Fixed the restore state method to function when the 
instance has not
+        previously been used to save state. 
+o RNG-96:  "AhrensDieterMarsagliaTsangGammaSampler": Fix parameter 
interpretation so that alpha
+        is a 'shape' parameter and theta is a 'scale' parameter. This reverses 
the functionality
+        of the constructor parameters from previous versions. Dependent code 
should be checked
+        and parameters reversed to ensure existing functionality is 
maintained. 
+o RNG-93:  "SmallMeanPoissonSampler": Requires the Poisson probability for 
p(x=0) to be positive
+        setting an upper bound on the mean of approximately 744.44. 
+o RNG-92:  "LargeMeanPoissonSampler": Requires mean >= 1. 
+
+Changes:
+o RNG-122:  "SeedFactory": Use XoRoShiRo1024PlusPlus as the default source of 
randomness. 
+o RNG-121:  "ChengBetaSampler": Algorithms for different distribution 
parameters have
+        been delegated to specialised classes. 
+o RNG-120:  Update security of serialization code for java.util.Random 
instances. Implement
+        look-ahead deserialization or remove the use of 
ObjectInputStream.readObject(). 
+o RNG-76:  "SplitMix64": Added primitive long constructor. 
+o RNG-119:  Add LongJumpable support to XoShiRo generators previously only 
supporting Jumpable. 
+o RNG-114:  "ListSampler": Select the shuffle algorithm based on the list 
type. This improves
+        performance for non-RandomAccess lists such as LinkedList. 
+o RNG-109:  "DiscreteProbabilityCollectionSampler": Use a faster enumerated 
probability
+        distribution sampler to replace the binary search algorithm. 
+o RNG-90:  "BaseProvider": Updated to use faster algorithm for nextInt(int). 
+o RNG-95:  "DiscreteUniformSampler": Updated to use faster algorithms for 
generation of ranges. 
+o RNG-106:  Ensure SeedFactory produces non-zero seed arrays. This avoids 
invalid seeding of
+        generators that cannot recover from a seed of zeros. 
+o RNG-103:  "LargeMeanPoissonSampler: Switch from SmallMeanPoissonSampler to 
use
+        KempSmallMeanPoissonSampler for the fractional mean sample. 
+o RNG-75:  "RandomSource.create(...)": Refactor internal components to allow 
custom seeding routines
+        per random source. Improvements were made to the speed of creating 
generators with small
+        seeds. 
+o RNG-77:  "NumberFactory": Improve performance of int and long array to/from 
byte array conversions. 
+o RNG-88:  Update the generation performance JMH benchmarks to have a 
reference baseline. 
+o RNG-87:  "MultiplyWithCarry256": Performance improvement by advancing state 
one step per sample. 
+o RNG-81:  "NumberFactory": Evenly sample all dyadic rationals between 0 and 
1. 
+o RNG-73:  Add the methods used from UniformRandomProvider to each sampler in 
the sampling module. 
+o RNG-74:  "DiscreteUniformSampler": Algorithms for small and large integer 
ranges have
+        been delegated to specialised classes. 
+o RNG-68:  "AhrensDieterMarsagliaTsangGammaSampler": Algorithms for small and 
large theta have
+        been delegated to specialised classes. 
+
+
+For complete information on Apache Commons RNG, including instructions on how 
to submit bug reports,
+patches, or suggestions for improvement, see the Apache Commons RNG website:
+
+https://commons.apache.org/proper/commons-rng/
+
+
+=============================================================================
+
               Apache Commons RNG 1.2 RELEASE NOTES
 
 The Apache Commons RNG team is pleased to announce the release of Apache 
Commons RNG 1.2
@@ -41,6 +162,90 @@ o RNG-51:  "PoissonSampler": Performance
 For complete information on Apache Commons RNG, including instructions on how 
to submit bug reports,
 patches, or suggestions for improvement, see the Apache Commons RNG website:
 
-http://commons.apache.org/proper/commons-rng/
+https://commons.apache.org/proper/commons-rng/
+
+
+=============================================================================
+
+              Apache Commons RNG 1.1 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache 
Commons RNG 1.1
+
+The Apache Commons RNG project provides pure-Java implementation of 
pseudo-random generators.
+
+This is a minor release of Apache Commons RNG, containing a few new features 
and performance improvements.
+Apache Commons RNG 1.1 contains the following library modules:
+ commons-rng-client-api (requires Java 6)
+ commons-rng-core (requires Java 6)
+ commons-rng-simple (requires Java 6)
+ commons-rng-sampling (requires Java 6)
+The code in module 'commons-rng-core' should not be accessed directly by 
applications as a future release might make use of the JPMS modularization 
feature available in Java 9+.
+Additional code is provided in the following module:
+ commons-rng-examples (requires Java 9) It is however not part of the official 
API and no compatibility should be expected in subsequent releases.
+We would like to also note that unit tests in module 'commons-rng-sampling' 
are bound to fail with some probability; this is expected due to the nature of 
random number generation.
+The 'maven-surefire-plugin' can be configured to re-run tests that fail and 
pass the build if they succeed (the test will be marked as 'flaky' in the 
report).
+
+Changes in this version include:
+
+New features:
+o RNG-37:  Implementation of the "Ziggurat" algorithm for Gaussian sampling. 
+o RNG-47:  "DiscreteProbabilityCollectionSampler": Sampling from a collection 
of items
+        with user-defined probabilities (feature ported from "Commons Math"). 
+o RNG-43:  "LogNormalSampler" with user-defined underlying 
"NormalizedGaussianSampler". 
+o RNG-39:  "UnitSphereSampler": generate random vectors isotropically located
+        on the surface of a sphere (feature ported from "Commons Math"). 
+o RNG-36:  "MarsagliaNormalizedGaussianSampler": Faster variation of the
+        Box-Muller algorithm.
+        This version is used within "AhrensDieterMarsagliaTsangGammaSampler"
+        "MarsagliaLogNormalSampler" and "PoissonSampler" (generated sequences
+        will thus differ from those generated by version 1.0 of the library). 
+o RNG-35:  New generic "GaussianSampler" based on "NormalizedGaussianSampler"
+        marker interface.
+        Implementation of "BoxMullerNormalizedGaussianSampler" deprecates
+        "BoxMullerGaussianSampler". 
+
+Fixed Bugs:
+o RNG-53:  Class "SamplerBase" has been deprecated.  It was meant for internal 
use
+        only but, through inheritance, it allows incorrect usage of the sampler
+        classes. 
+
+Changes:
+o RNG-50:  "PoissonSampler": Algorithms for small mean and large mean have
+        been separated into dedicated classes.  Cache precomputation has
+        been disabled as it is only marginally used and is a performance
+        hit for small sampling sets. Thanks to Alex D. Herbert. 
+o RNG-42:  Use "ZigguratNormalizedGaussianSampler" within the library. 
+o RNG-46:  Following RNG-43, "BoxMullerLogNormalSampler" has been deprecated. 
+
+
+For complete information on Apache Commons RNG, including instructions on how 
to submit bug reports,
+patches, or suggestions for improvement, see the Apache Commons RNG website:
+
+https://commons.apache.org/proper/commons-rng/
+
+
+=============================================================================
+
+              Apache Commons RNG 1.0 RELEASE NOTES
+
+The Apache Commons RNG team is pleased to announce the release of Apache 
Commons RNG 1.0
+
+The Apache Commons RNG project provides pure-Java implementation of 
pseudo-random generators.
+
+This is the first release of Apache Commons RNG.
+Apache Commons RNG 1.0 contains the following modules:
+ commons-rng-client-api (requires Java 6)
+ commons-rng-core (requires Java 6)
+ commons-rng-simple (requires Java 6)
+ commons-rng-sampling (requires Java 6)
+ commons-rng-jmh (requires Java 6)
+ commons-rng-examples (requires Java 7)
+
+No changes defined in this version.
+
+For complete information on Apache Commons RNG, including instructions on how 
to submit bug reports,
+patches, or suggestions for improvement, see the Apache Commons RNG website:
+
+https://commons.apache.org/proper/commons-rng/
 
 

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11:07:47 2019
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==============================================================================
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==============================================================================
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