diff --git a/akka-protobuf/src/main/java/akka/protobuf/ByteString.java b/akka-protobuf/src/main/java/akka/protobuf/ByteString.java index 3f5ae45531..b453331c1e 100644 --- a/akka-protobuf/src/main/java/akka/protobuf/ByteString.java +++ b/akka-protobuf/src/main/java/akka/protobuf/ByteString.java @@ -373,7 +373,7 @@ public abstract class ByteString implements Iterable { * Concatenate the given {@code ByteString} to this one. Short concatenations, * of total size smaller than {@link ByteString#CONCATENATE_BY_COPY_SIZE}, are * produced by copying the underlying bytes (as per Rope.java, + * href="https://www.cs.ubc.ca/local/reading/proceedings/spe91-95/spe/vol25/issue12/spe986.pdf"> * BAP95 . In general, the concatenate involves no copying. * * @param other string to concatenate diff --git a/akka-protobuf/src/main/java/akka/protobuf/RopeByteString.java b/akka-protobuf/src/main/java/akka/protobuf/RopeByteString.java index 19a02016dd..d76aad6a36 100644 --- a/akka-protobuf/src/main/java/akka/protobuf/RopeByteString.java +++ b/akka-protobuf/src/main/java/akka/protobuf/RopeByteString.java @@ -53,7 +53,7 @@ import java.util.Stack; * represented as a tree whose leaf nodes are each a {@link LiteralByteString}. * *

Most of the operation here is inspired by the now-famous paper + * href="https://www.cs.ubc.ca/local/reading/proceedings/spe91-95/spe/vol25/issue12/spe986.pdf"> * BAP95 Ropes: an Alternative to Strings hans-j. boehm, russ atkinson and * michael plass * diff --git a/akka-remote/src/main/scala/akka/remote/PhiAccrualFailureDetector.scala b/akka-remote/src/main/scala/akka/remote/PhiAccrualFailureDetector.scala index e6a26b1cc8..c36cb40903 100644 --- a/akka-remote/src/main/scala/akka/remote/PhiAccrualFailureDetector.scala +++ b/akka-remote/src/main/scala/akka/remote/PhiAccrualFailureDetector.scala @@ -21,7 +21,7 @@ import akka.util.Helpers.ConfigOps /** * Implementation of 'The Phi Accrual Failure Detector' by Hayashibara et al. as defined in their paper: - * [http://www.jaist.ac.jp/~defago/files/pdf/IS_RR_2004_010.pdf] + * [https://oneofus.la/have-emacs-will-hack/files/HDY04.pdf] * * The suspicion level of failure is given by a value called φ (phi). * The basic idea of the φ failure detector is to express the value of φ on a scale that diff --git a/akka-remote/src/main/scala/akka/remote/artery/LruBoundedCache.scala b/akka-remote/src/main/scala/akka/remote/artery/LruBoundedCache.scala index 59e8d4832e..4387648453 100644 --- a/akka-remote/src/main/scala/akka/remote/artery/LruBoundedCache.scala +++ b/akka-remote/src/main/scala/akka/remote/artery/LruBoundedCache.scala @@ -16,8 +16,8 @@ private[akka] case class CacheStatistics(entries: Int, maxProbeDistance: Int, av * INTERNAL API * * This class is based on a Robin-Hood hashmap - * (http://www.sebastiansylvan.com/post/robin-hood-hashing-should-be-your-default-hash-table-implementation/) - * with backshift (http://codecapsule.com/2013/11/17/robin-hood-hashing-backward-shift-deletion/). + * (https://www.sebastiansylvan.com/post/robin-hood-hashing-should-be-your-default-hash-table-implementation/) + * with backshift (https://codecapsule.com/2013/11/17/robin-hood-hashing-backward-shift-deletion/). * * The main modification compared to an RH hashmap is that it never grows the map (no rehashes) instead it is allowed * to kick out entires that are considered old. The implementation tries to keep the map close to full, only evicting diff --git a/akka-remote/src/main/scala/akka/remote/artery/compress/TopHeavyHitters.scala b/akka-remote/src/main/scala/akka/remote/artery/compress/TopHeavyHitters.scala index 129298bd32..bc8d75d169 100644 --- a/akka-remote/src/main/scala/akka/remote/artery/compress/TopHeavyHitters.scala +++ b/akka-remote/src/main/scala/akka/remote/artery/compress/TopHeavyHitters.scala @@ -16,7 +16,7 @@ import scala.reflect.ClassTag * * Keeps a number of specific heavy hitters around in memory. * - * See also Section 5.2 of http://dimacs.rutgers.edu/~graham/pubs/papers/cm-full.pdf + * See also Section 5.2 of https://dimacs.rutgers.edu/~graham/pubs/papers/cm-full.pdf * for a discussion about the assumptions made and guarantees about the Heavy Hitters made in this model. * We assume the Cash Register model in which there are only additions, which simplifies HH detection significantly. *