Building scalable software systems in the multicore era

Software systems must face two challenges today: growing complexity and increasing parallelism in the underlying computational models. The problem of increased complexity is often solved by dividing systems into modules in a way that permits analysis of these modules in isolation. The problem of lack of concurrency is often tackled by dividing system execution into tasks that permits execution of these tasks in isolation. The key challenge in software design is to manage the explicit and implicit dependence between modules that decreases modularity. The key challenge for concurrency is to manage the explicit and implicit dependence between tasks that decreases parallelism. Even though these challenges appear to be strikingly similar, current software design practices and languages do not take advantage of this similarity. The net effect is that the modularity and concurrency goals are often tackled mutually exclusively. Making progress towards one goal does not naturally contribute towards the other. My position is that for programmers that are not formally and rigorously trained in the concurrency discipline the safest and most productive way to get scalability in their software is by improving modularity of their software using programming language features and design practices that reconcile modularity and concurrency goals. I briefly discuss preliminary efforts of my group, but we have only touched the tip of the iceberg

Duck Futures: A Generative Approach to Transparent Futures

Futures offer a convenient abstraction for encapsulating delayed computation. It is a mechanism to introduce concurrency through a rewrite of the sequential program. However, managing futures is tedious and requires knowledge of concurrency and its concerns. The notion of transparent futures is used to hide the complexity of futures from developers. A number of techniques based on transparency have been proposed to create and manage futures. Previous techniques make use of reflection. In this paper, we propose duck futures that use a generative approach. We show that duck futures are much more efficient compared to previous notions of transparent futures. We also present the first large scale study of the applicability and utility of duck futures in practice using the Boa infrastructure for mining large scale open source repositories. Our study finds that transparent futures, despite their limitations, can be very useful in practice

A decision tree-based approach to dynamic pointcut evaluation

Constructs of dynamic nature, e.g., history-based pointcuts and control-flow based pointcuts, have received significant attention in recent aspect-oriented literature. A variety of compelling use cases are presented that motivate the need for efficiently supporting such constructs in language implementations. The key challenge in implementing dynamic constructs is to efficiently support runtime adaptation of the set of intercepted join points at a fine-grained level. This translates to two high-level requirements. First, since the set of intercepted join points may change, such implementations must provide an efficient method to determine this set membership, i.e., whether the currently executing join point needs to be intercepted. Second, the frequency with which such set membership needs to be determined must be minimized. In previous work, Dyer and Rajan proposed a dedicated caching mechanism to address the second requirement. In this work, we propose a mechanism to address the first requirement. This requirement translates to efficiently evaluating whether a join point is intercepted by a set of pointcut expressions. In the worst case, at every join point there may be the need to determine whether it is intercepted. Therefore, even modest savings in such mechanisms is likely to translate to significant savings in the long run