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.

/pdf/x10-an-object-oriented-approach-to-non-uniform-cluster-4dbvtkahpt.pdf

X10: an object-oriented approach to non-uniform cluster computing

Recent studies in the literature have shown that syntax remains a significant barrier to novice computer science students in the field. While this syntax barrier is known to exist, whether and how it varies across programming languages has not been carefully investigated. For this article, we conducted four empirical studies on programming language syntax as part of a larger analysis into the, so called, programming language wars. We first present two surveys conducted with students on the intuitiveness of syntax, which we used to garner formative clues on what words and symbols might be easy for novices to understand. We followed up with two studies on the accuracy rates of novices using a total of six programming languages: Ruby, Java, Perl, Python, Randomo, and Quorum. Randomo was designed by randomly choosing some keywords from the ASCII table (a metaphorical placebo). To our surprise, we found that languages using a more traditional C-style syntax (both Perl and Java) did not afford accuracy rates significantly higher than a language with randomly generated keywords, but that languages which deviate (Quorum, Python, and Ruby) did. These results, including the specifics of syntax that are particularly problematic for novices, may help teachers of introductory programming courses in choosing appropriate first languages and in helping students to overcome the challenges they face with syntax.

An Empirical Investigation into Programming Language Syntax

Empirical studies, often in the form of controlled experiments, have been widely adopted in software engineering research as a way to evaluate the merits of new software engineering tools. However, controlled experiments involving human participants actually using new tools are still rare, and when they are conducted, some have serious validity concerns. Recent research has also shown that many software engineering researchers view this form of tool evaluation as too risky and too difficult to conduct, as they might ultimately lead to inconclusive or negative results. In this paper, we aim both to help researchers minimize the risks of this form of tool evaluation, and to increase their quality, by offering practical methodological guidance on designing and running controlled experiments with developers. Our guidance fills gaps in the empirical literature by explaining, from a practical perspective, options in the recruitment and selection of human participants, informed consent, experimental procedures, demographic measurements, group assignment, training, the selecting and design of tasks, the measurement of common outcome variables such as success and time on task, and study debriefing. Throughout, we situate this guidance in the results of a new systematic review of the tool evaluations that were published in over 1,700 software engineering papers published from 2001 to 2011.

/pdf/a-practical-guide-to-controlled-experiments-of-software-3tpfti39xw.pdf

A practical guide to controlled experiments of software engineering tools with human participants

This paper introduces the Checker Framework, which supports adding pluggable type systems to the Java language in a backward-compatible way. A type system designer defines type qualifiers and their semantics, and a compiler plug-in enforces the semantics. Programmers can write the type qualifiers in their programs and use the plug-in to detect or prevent errors. The Checker Framework is useful both to programmers who wish to write error-free code, and to type system designers who wish to evaluate and deploy their type systems.The Checker Framework includes new Java syntax for expressing type qualifiers; declarative and procedural mechanisms for writing type-checking rules; and support for flow-sensitive local type qualifier inference and for polymorphism over types and qualifiers. The Checker Framework is well-integrated with the Java language and toolset.We have evaluated the Checker Framework by writing 5 checkers and running them on over 600K lines of existing code. The checkers found real errors, then confirmed the absence of further errors in the fixed code. The case studies also shed light on the type systems themselves.

/pdf/practical-pluggable-types-for-java-1pb7tz0ey4.pdf

Practical pluggable types for java

Source code querying tools allow programmers to explore relations between different parts of the code base. This paper describes such a tool, named CodeQuest. It combines two previous proposals, namely the use of logic programming and database systems. As the query language we use safe Datalog, which was originally introduced in the theory of databases. That provides just the right level of expressiveness; in particular recursion is indispensable for source code queries. Safe Datalog is like Prolog, but all queries are guaranteed to terminate, and there is no need for extra-logical annotations. Our implementation of Datalog maps queries to a relational database system. We are thus able to capitalise on the query optimiser provided by such a system. For recursive queries we implement our own optimisations in the translation from Datalog to SQL. Experiments confirm that this strategy yields an efficient, scalable code querying system.

Code Quest : Scalable Source Code Queries with Datalog

While still a relatively young field, computer science has a vast body of knowledge in the domain of programming languages. When a new language is introduced, its designers make claims which distinguish their language from previous languages. However, it often feels like language designers do not feel a pressing need to back these claims with evidence beyond personal anecdotes. Peer reviewers are likely to agree.In this paper, we present preliminary work which revisits the history of such claims by examining a number of language design papers which span the history of programming language development. We focus on the issue of claim-evidence correspondence, or determining how often claims are or are not backed by evidence. These preliminary results confirm that unsupported claims have been around since the inception of higher level programming in the 1950s. We stake a position that this behavior is unacceptable for the health of the research community. We should be more aware of valiant and effective efforts for supplying evidence to support language design claims.

Staking claims: a history of programming language design claims and evidence: a positional work in progress

In previous work, we described a new approach to supporting user-defined type qualifiers, which augment existing types to specify and check additional properties of interest. For each qualifier, users define a set of rules that are enforced during static typechecking of programs. Separately, these rules are automatically validated with respect to a user-defined predicate that formalizes the qualifier's intended run-time invariant. We instantiated this approach as a framework for user-defined type qualifiers in C programs, called CLARITY. In this paper, we extend our earlier approach by resolving two usability issues. First, we show how to perform qualifier inference in the presence of user-defined rules by generating and solving a system of conditional set constraints, thereby relieving users of the burden of explicitly annotating programs. Second, we show how to automatically infer rules that respect a given user-defined invariant, thereby relieving qualifier designers of the burden of manually producing such rules. We have formalized both qualifier and rule inference and proven their correctness. We have also extended CLARITY to support qualifier and rule inference, and we illustrate their utility in practice through experiments with several type qualifiers and open-source C programs.

Inference of user-defined type qualifiers and qualifier rules

In previous work, we described a new approach to supporting user-defined type qualifiers, which augment existing types to specify and check additional properties of interest. For each qualifier, users define a set of rules that are enforced during static typechecking of programs. Separately, these rules are automatically validated with respect to a user-defined predicate that formalizes the qualifier's intended run-time invariant. We instantiated this approach as a framework for user-defined type qualifiers in C programs, called Clarity.

In this paper, we extend our earlier approach by resolving two usability issues. First, we show how to perform qualifier inference in the presence of user-defined rules by generating and solving a system of conditional set constraints, thereby relieving users of the burden of explicitly annotating programs. Second, we show how to automatically infer rules that respect a given user-defined invariant, thereby relieving qualifier designers of the burden of manually producing such rules. We have formalized both qualifier and rule inference and proven their correctness. We have also extended Clarity to support qualifier and rule inference, and we illustrate their utility in practice through experiments with several type qualifiers and open-source C programs.

/pdf/inference-of-user-defined-type-qualifiers-and-qualifier-2wkju261cs.pdf

In this poster, we present our vision of refactoring support for languages with a partitioned global address space memory model as embodied in the X10 programming language. We examine a novel refactoring, extract concurrent, that introduces additional concurrency within a loop by arranging for some user-selected code in the loop body to run in parallel with other iterations of the loop. We discuss the mechanisms and challenges for implementing this refactoring and how development of this refactoring provides insight for designing future refactorings.

Towards concurrency refactoring for x10

For worms with known signatures, properly configured firewalls can prevent infection of a network from the outside. However, as several recent worms have shown, portable computers provide worms with an entry point into such networks, since these computers are connected behind the firewall. Once inside, the firewall provides no protection against the worm's further spread. Wireless networks are particularly dangerous in this regard, as the act of connection is often invisible, and improperly configured wireless networks will allow anyone within radio range to connect. In this paper, we use real data on a large-scale wireless deployment to analyze the speed with which a worm could spread if it used only this propagation vector. We discuss several possible solutions and provide analysis on how much protection those solutions would provide.

/pdf/mobile-contagion-simulation-of-infection-and-defense-1y8rmcq4pt.pdf

Mobile Contagion: Simulation of Infection and Defense

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Staking claims: a history of programming language design claims and evidence: a positional work in progress

Inference of user-defined type qualifiers and qualifier rules

Inference of user-defined type qualifiers and qualifier rules

Towards concurrency refactoring for x10

Mobile Contagion: Simulation of Infection and Defense