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Most concurrent data structures being designed today are versions of known sequential data structures. However, in various cases it makes sense to relax the semantics of traditional concurrent data structures in order to get simpler and possibly more efficient and scalable implementations. For example, when solving the classical producer-consumer problem by implementing a concurrent queue, it might be enough to allow the dequeue operation (by a consumer) to return and remove one of the two oldest values in the queue, and not necessarily the oldest one. We define infinitely many possible relaxations of several traditional data structures and objects: queues, stacks, multisets and registers, and examine their relative computational power.

First-in-first-out (FIFO) queues are among the most fundamental and highly studied concurrent data structures. The most effective and practical dynamic-memory concurrent queue implementation in the literature is the lock-free FIFO queue algorithm of Michael and Scott, included in the standard Java TM Concurrency Package. This work presents a new dynamic-memory concurrent lock-free FIFO queue algorithm that in a variety of circumstances performs better than the Michael and Scott queue. The key idea behind our new algorithm is a novel way of replacing the singly-linked list of Michael and Scott, whose pointers are inserted using a costly compare-and-swap (CAS) operation, by an “optimistic” doubly - linked list whose pointers are updated using a simple store, yet can be “fixed” if a bad ordering of events causes them to be inconsistent. We believe it is the first example of such an “optimistic” approach being applied to a real world data structure.

Assuming the existence of garbage collection makes it easier to design implementations of concurrent data structures. However, this assumption limits their applicability. We present a methodology that, for a significant class of data structures, allows designers to first tackle the easier problem of designing a garbage-collection-dependent implementation, and then apply our methodology to achieve a garbage-collection-independent one. Our methodology is based on the well-known reference counting technique, and employs the double compare-and-swap operation.