Layered JavaScript engines, in which the JavaScript runtime is built on top another managed runtime, provide better extensibility and portability compared to traditional monolithic engines. In this paper, we revisit the design of layered JavaScript engines and propose a layered architecture, called MuscalietJS2, that splits the responsibilities of a JavaScript engine between a high-level, JavaScript-specific component and a low-level, language-agnostic .NET VM. To make up for the performance loss due to layering, we propose a two pronged approach: high-level JavaScript optimizations and exploitation of low-level VM features that produce very efficient code for hot functions. We demonstrate the validity of the MuscalietJS design through a comprehensive evaluation using both the Sunspider benchmarks and a set of web workloads. We demonstrate that our approach outperforms other layered engines such as IronJS and Rhino engines while providing extensibility, adaptability and portability.

We explore the challenges in expressing and managing concurrency in browsers on mobile devices. Browsers are complex applications that implement multiple standards, need to support legacy behavior, and are highly dynamic and interactive. We present ZOOMM, a highly concurrent web browser engine prototype and show how concurrency is effectively exploited at different levels: speed up computation performance, preload network resources, and preprocess resources outside the critical path of page loading. On a dual-core Android mobile device we demonstrate that ZOOMM is two times faster than the native WebKit based browser when loading the set of pages defined in the Vellamo benchmark.

We study distributed state-space generation on a cluster of workstations. It is explained why state-space partitioning by a global hash function is problematic when states contain variables from unbounded domains, such as lists or other recursive data types. Our solution is to introduce a database which maintains a global numbering of state values. We also describe tree compression, a technique of recursive state folding, and show that it is superior to manipulating plain state vectors. This solution is implemented and linked to the µCRL toolset, where state values are implemented as maximally shared terms (ATerms). However, it is applicable to other models as well, e.g. PROMELA or LOTOS models. Our experiments show the trade-offs between keeping the database global, replicated or local, depending on the available network bandwidth and latency.