We introduce Leaplist, a concurrent data-structure that is tailored to provide linearizable range queries. A lookup in Leaplist takes O (log n) and is comparable to a balanced binary search tree or to a Skiplist. However, in Leaplist, each node holds up-to K immutable key-value pairs, so collecting a linearizable range is K times faster than the same operation performed non-linearizably on a Skiplist.

Transactional Memory (TM) is considered as one of the most promising paradigms for developing concurrent applications. TM has been shown to scale well on >multiple cores when the data access pattern behaves "well," i.e., when few conflicts are induced. In contrast, data patterns with frequent write sharing, with long transactions, or when many threads contend for a smaller number of cores, result in numerous conflicts. Until recently, TM implementations had little control of transactional threads, which remained under the supervision of the kernel's transaction-ignorant scheduler. Conflicts are thus traditionally resolved by consulting an STM-level contention manager. Consequently, the contention managers of these "conventional" TM implementations suffer from a lack of precision and often fail to ensure reasonable performance in high-contention workloads.

Transactional memory (TM) is a key concurrent programming abstraction. Several software-based transactional memory (STM) implementations have been developed in recent years. All STM implementations must guarantee transaction atomicity but different STM implementations may provide different progress guarantees. In order to ensure progress, an STM implementation must resolve transaction conflicts. This is done either by the implementation itself or by delegating conflict resolution to a separate contention manager module that tries to resolve transaction collisions once they are detected.