Merge pull request #18 from thomwiggers/bump-version

Bump to version 0.4.0

CHANGELOG.md

@@ -1,4 +1,9 @@
-== 0.3.0 ==
+== 0.4.0 ==
+
+* Fixed a bug (#16) in the implementation which meant that Factorials 37!, 1200!, and possibly others were not computed correctly.
+  * Thanks to @marcantoinem for stepping up with the bugfix in (#17)
+
+== 0.3.0 (YANKED) ==
 
 * Implement Prime Swing algorithm, which should massively improve performance, especially for larger factorials. (#9)
   Thanks a lot @marcantoinem!

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "factorial"
-version = "0.3.0"
+version = "0.4.0"
 authors = ["Thom Wiggers <thom@thomwiggers.nl>"]
 description = "Convenient methods to compute the factorial, optionally checked."
 repository = "https://github.com/thomwiggers/factorial/"
@@ -16,15 +16,12 @@ maintenance = { status = "passively-maintained" }
 
 [dependencies]
 num-traits = "0.2"
-primal-sieve = "0.3.5"
+primal-sieve = "0.3.6"
 
 [dev-dependencies]
 num-bigint = "0.4"
 criterion = { version = "0.5", features = ["html_reports"] }
 
-[build-dependencies]
-primal-sieve = "0.3.5"
-
 [[bench]]
 name = "benchmark"
 harness = false

README.md

@@ -1,3 +1,10 @@
-This crate provides some convenient and safe methods to compute the factorial with an efficient method. More precisely it uses the prime swing algorithm to compute the factorial. See [this paper](https://oeis.org/A000142/a000142.pdf) for more detail.
+# Compute factorials
 
-It can compute the factorial in `O(n (log n loglog n)^2)` operations of multiplication. The time complexity of this algorithm depends on the time complexity of the multiplication algorithm used.
+This crate provides some convenient and safe methods to compute the factorial
+with an efficient method. More precisely it uses the prime swing algorithm to
+compute the factorial. See [this paper](https://oeis.org/A000142/a000142.pdf)
+for more detail.
+
+It can compute the factorial in `O(n (log n loglog n)^2)` operations of
+multiplication. The time complexity of this algorithm depends on the time
+complexity of the multiplication algorithm used.