Full-featured integrated development environments have become critical to the adoption of new programming languages. Key to the success of these IDEs is the provision of services tailored to the languages. However, modern IDEs are large and complex, and the cost of constructing one from scratch can be prohibitive. Generators that work from language specifications reduce costs but produce environments that do not fully reflect distinctive language characteristics.

Programming language design remains a vital field, with interest in languages targeting concurrency, scripting, and aspects, as well as in domain-specific languages. Full-featured integrated development environments (IDEs) have become critical to the adoption of new languages. A key factor in the success of these IDEs is the provision of services specifically tailored to the language. However, modern IDE frameworks are large and complex, and the cost of constructing a language-specific IDE from scratch remains prohibitive

It is now well established that the device scaling predicted by Moore's Law is no longer a viable option for increasing the clock frequency of future uniprocessor systems at the rate that had been sustained during the last two decades. As a result, future systems are rapidly moving from uniprocessor to multiprocessor configurations, so as to use parallelism instead of frequency scaling as the foundation for increased compute capacity. The dominant emerging multiprocessor structure for the future is a Non-Uniform Cluster Computing (NUCC) system with nodes that are built out of multi-core SMP chips with non-uniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as blade servers. Unlike previous generations of hardware evolution, this shift will have a major impact on existing software. Current OO language facilities for concurrent and distributed programming are inadequate for addressing the needs of NUCC systems because they do not support the notions of non-uniform data access within a node, or of tight coupling of distributed nodes.We have designed a modern object-oriented programming language, X10, for high performance, high productivity programming of NUCC systems. A member of the partitioned global address space family of languages, X10 highlights the explicit reification of locality in the form of places}; lightweight activities embodied in async, future, foreach, and ateach constructs; a construct for termination detection (finish); the use of lock-free synchronization (atomic blocks); and the manipulation of cluster-wide global data structures. We present an overview of the X10 programming model and language, experience with our reference implementation, and results from some initial productivity comparisons between the X10 and Java™ languages.

We present a framework and tool for porting assessment and code remediation in commercial porting projects, primarily targeting interplatform C/C++ porting. Our framework has a modular architecture for handling real-world code bases, a key part of which is an extensible knowledge base of porting issue types. Porting issue detection and remediation are achieved through dynamically-linked detector and remediation "plug-ins" which can be augmented over time. Analysis and remediation can be performed over multiple intermediate forms, such as the AST or error logs. Analysis and remediation results can be presented as a single assessment report, or the changes can be incorporated into the original code base. Furthermore our framework has been integrated into Eclipse, providing a user interface and allowing further capability for integration with other Eclipse extensions. A subset of our tool has been prototyped and benchmarked against real-world customer code.

We present a streaming algorithm for evaluating XPath expressions that use backward axes (parent and ancestor) and forward axes in a single document-order traversal of an XML document. Other streaming XPath processors handle only forward axes. We show through experiments that our algorithm significantly outperforms (by more than a factor of two) a traditional nonstreaming XPath engine. Furthermore, our algorithm scales better because it retains only the relevant portions of the input document in memory. Our engine successfully processes documents over 1GB in size, whereas the traditional XPath engine degrades considerably in performance for documents over 100 MB in size and fails to complete for documents of size over 200 MB.