In this paper, we propose a new technique that can identify transaction-local memory (i.e. captured memory), in managed environments, while having a low runtime overhead. We implemented our proposal in a well known STM framework (Deuce) and we tested it in STMBench7 with two different STMs: TL2 and LSA. In both STMs the performance improved significantly (4 times and 2.6 times, respectively). Moreover, running the STAMP benchmarks with our approach shows improvements of 7 times in the best case for the Vacation application.

Software Transactional Memory (STM) was initially proposed as a lock-free mechanism for concurrency control. Early implementations had efficiency limitations, and soon obstruction-free proposals appeared, to tackle this problem, often simplifying STM implementation. Today, most of the modern and top-performing STMs use blocking designs, relying on locks to ensure an atomic commit operation. This approach has revealed better in practice, in part due to its simplicity. Yet, it may have scalability problems when we move into many-core computers, requiring fine-tuning and careful programming to avoid contention. In this paper we present and discuss the modifications we made to a lock-based multi-version STM in Java, to turn it into a lock-free implementation that we have tested to scale at least up to 192 cores, and which provides results that compete with, and sometimes exceed, some of today's top-performing lock-based implementations. The new lock-free commit algorithm allows write transactions to proceed in parallel, by allowing them to run their validation phase independently of each other, and by resorting to helping from threads that would otherwise be waiting to commit, during the write-back phase. We also present a new garbage collection algorithm to dispose of old unused object versions that allows for asynchronous identification of unnecessary versions, which minimizes its interference with the rest of the transactional system.

This work aims to create an innovative system for analyzing and predicting the behaviour of object-oriented applications, with respect to the domain objects they manipulate, based on Markov Chains. The results are validated by the execution of the TPC-W and oo7 benchmarks. The oo7 benchmark has been modelled as a stochastic process through Monte Carlo simulations. The system is sufficiently flexible to be applied to a broad spectrum of object-oriented applications. The results are precise, regarding the observed behaviour, and the overheads introduced by the data acquisition are low.

Current best practices on web application development build on a plethora of design patterns, frameworks, and tools to support commontasks such as handling requests from the user and persisting domain entities: Even the simplest web applications need suchthings. Thus, web application developers are forced to learn anenormous amount of technology before they can start being productivein the development process.This paper proposes a simpler approach to the development of web applications, based on the combination of two elements. First, the use of Software Transactional Memory to bring the transactionsemantics into the programming language level. Second, we propose an object-oriented Domain Modeling Language to specify the domain model.This domain model is transformed into classes that haveinterfaces that an object-oriented programmer would expect, but the objects of these classes are transparently transactional andpersistent.This approach significantly reduces both the effort and the errorsmade during the development of new applications. Rather thandealing with multiple configuration files and tools, which have norelation to the domain problem, programmers can concentrate exclusively on an object-oriented model of the problem they want to solve. By using this approach, we can delay, or completely avoid,the commitment to a particular technology.