SUMMARY Transactional memory is a promising technique for enforcing disciplined access to shared data in a multiprocessor system. Transactional memory simplifies the implementation of a variety of concurrent data structures. In this paper, we study the benefits of a modest, real‐time aware, hardware implementation of transactional memory that we callmicro‐transactions. In particular, we argue that hardware support for micro‐transactions allows us to efficiently implement certain data structures. Those data structures are difficult to realize with the atomic operations provided by stock hardware and provide real‐time guarantees for those operations. Our main implementation platform is the Java Optimized Processor system, a field‐programmable gate array (FPGA) implementation of the Java virtual machine, optimized for real‐time Java. We report on the performance of data structures implemented with locks, atomic instructions, and micro‐transactions. Our results suggest that transactional memory is an interesting alternative to traditional concurrency control mechanisms. Copyright © 2012 John Wiley & Sons, Ltd.

Eval endows JavaScript developers with great power. It allows developers and end-users, by turning text into executable code, to seamlessly extend and customize the behavior of deployed applications as they are running. With great power comes great responsibility, though not in our experience. In previous work we demonstrated through a large corpus study that programmers wield that power in rather irresponsible and arbitrary ways. We showed that most calls to eval fall into a small number of very predictable patterns. We argued that those patterns could easily be recognized by an automated algorithm and that they could almost always be replaced with safer JavaScript idioms. In this paper we set out to validate our claim by designing and implementing a tool, which we call Evalorizer, that can assist programmers in getting rid of their unneeded evals. We use the tool to remove eval from a real-world website and validated our approach over logs taken from the top 100 websites with a success rate over 97% under an open world assumption.