We posit that functional programmers employ a notion called expression integrity to understand programs. We attempt to study the extent to which both novices and experts use this notion as they program, discuss the difficulties that arise in measuring this, and offer some observational findings.

Good error messages are critical for novice programmers. Re-cognizing this, the DrRacket programming environment provides a series of pedagogically-inspired language subsets with error messages customized to each subset. We apply human-factors research methods to explore the effectiveness of these messages. Unlike existing work in this area, we study messages at a fine-grained level by analyzing the edits students make in response to various classes of errors. We present a rubric (which is not language specific) to evaluate student responses, apply it to a course-worth of student lab work, and describe what we have learned about using the rubric effectively. We also discuss some concrete observations on the effectiveness of these messages.

Static analysis has gained much attention over the past few years in applications such as bug finding and program verification. As software becomes more complex and componentized, it is common for software systems and applications to be implemented in multiple languages. There is thus a strong need for developing analysis tools for multi-language software. We introduce a technique called Analysis Preserving Language Transformation (aplt) that enables the analysis of multi-language software, and also allows analysis tools for one language to be applied to programs written in another. aplt preserves data and control flow information needed to perform static analyses, but allows the translation to deviate from the original program's semantics in ways that are not pertinent to the particular analysis. We discuss major technical difficulties in building such a translator, using a C-to-Java translator as an example. We demonstrate the feasibility and effectiveness of aplt using two usage cases: analysis of the Java runtime native methods and reuse of Java analysis tools for C. Our preliminary results show that a control- and data-flow equivalent model for native methods can eliminate unsoundness and produce reliable results, and that aplt enables seamless reuse of analysis tools for checking high-level program properties.

IEEE 802.11b wireless Ethernet is rapidly becoming the standard for in-building and short-range wireless communication. Many mobile devices such as mobile robots, laptops and PDAs already use this protocol for wireless communication. Many wireless Ethernet cards measure the signal strength of incoming packets. This paper investigates the feasibility of implementing a localization system using this sensor. Using a Bayesian localization framework, we show experiments demonstrating that off-the-shelf wireless hardware can accurately be used for location sensing and tracking with about one meter precision in a wireless-enabled office building.

A key subproblem in the construction of location-aware systems is the determination of the position of a mobile device. This paper describes the design, implementation and analysis of a system for determining position inside a building from measured RF signal strengths of packets on an IEEE 802.11b wireless Ethernet network. Previous approaches to location awareness with RF signals have been severely hampered by non-linearity, noise and complex correlations due to multi-path effects, interference and absorption. The design of our system begins with the observation that determining position from complex, noisy and non-linear signals is a well-studied problem in the field of robotics. Using only off-the-shelf hardware, we achieve robust position estimation to within a meter in our experimental context and after adequate training of our system. We can also coarsely determine our orientation and can track our position as we move. By applying recent advances in probabilistic inference of position and sensor fusion from noisy signals, we show that the RF emissions from base stations as measured by off-the-shelf wireless Ethernet cards are sufficiently rich in information to permit a mobile device to reliably track its location.