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Educational research has established that learning can be defined as an enduring change in behaviour, which results from practice or other forms of experience. In introductory programming courses, proficiency is typically approximated through relatively small but frequent assignments and tests. Scaling these assessments to track significant behavioural change is challenging due to the subtle and complex metrics that must be collected from large student populations. Based on a four-semester study, we present an analysis of learning tool interaction data collected from 514 students and 38,796 solutions to practice programming exercises. We first evaluate the effectiveness of measuring workflow patterns to detect students at-risk of failure within the first three weeks of the semester. Our early predictor analysis accurately detects 81% of the students who struggle throughout the course. However, our early predictor also captures transient struggling, as 43% of the students who ultimately did well in the course were classified as at-risk. In order to better differentiate sustained versus transient struggling, we further propose a trajectory metric which measures changes in programming behaviour. The trajectory metric detects 70% of the students who exhibit sustained struggling, and mis-classifies only 11% of students who go on to succeed in the course. Overall, our results show how detecting changes in programming behaviour can help us differentiate between learning and struggling in CS1.

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Abstract. Real-time systems are notoriously difficult to design and implement, and, as many real-time problems are safety-critical, their solutions must be reliable as well as efficient and correct. While higher-level programming models (such as the Real-Time Specification for Java) permit real-time programmers to use language features that most programmers take for granted (objects, type checking, dynamic dispatch, and memory safety) the compromises required for real-time execution, especially concerning memory allocation, can create as many problems as they solve. This paper presents Scoped Types and Aspects for Real-Time Systems (STARS) a novel programming model for real-time systems. Scoped Types give programmers a clear model of their programs' memory use, and, being statically checkable, prevent the run-time memory errors that bedevil models such as RTSJ. Our Aspects build on Scoped Types guarantees so that Real-Time concerns can be completely separated from applications' base code. Adopting the integrated Scoped Types and Aspects approach can significantly improve both the quality and performance of a real-time Java systems, resulting in simpler systems that are reliable, efficient, and correct.

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Abstract. Real-time systems are notoriously difficult to design and implement, and, as many real-time problems are safety-critical, their solutions must be reliable as well as efficient and correct. While higher-level programming models (such as the Real-Time Specification for Java) permit real-time programmers to use language features that most programmers take for granted (objects, type checking, dynamic dispatch, and memory safety) the compromises required for real-time execution, especially concerning memory allocation, can create as many problems as they solve. This paper presents Scoped Types and Aspects for Real-Time Systems (STARS) a novel programming model for real-time systems. Scoped Types give programmers a clear model of their programs' memory use, and, being statically checkable, prevent the run-time memory errors that bedevil the RTSJ. Adopting the integrated Scoped Types and Aspects approach can significantly improve both the quality and performance of a real-time Java systems, resulting in simpler systems that are reliable, efficient, and correct.

Layered architecture in operating system code is often compromised by execution path-specific customizations such as prefetching, page replacement and scheduling strategies. Pathspecific customizations are difficult to modularize in a layered architecture because they involve dynamic context passing and layer violations. Effectively they are vertically integrated slices through the layers.An initial experiment using an aspect-oriented programming language to refactor prefetching in the FreeBSD operating system kernel shows significant benefits, including easy (un)pluggability of prefetching modes, independent development of prefetching modes, and overall improved comprehensibility.Keywords aspect-oriented programming, software modularity, operating system design Recently, the aspect-oriented programming (AOP) [11] community has focused attention on the concept of crosscutting concerns, which are elements of a system that cut through the primary system modularity. They have proposed linguistic mechanisms intended to allow implementation of crosscutting concerns as first class modules called aspects [8,16,14,1].The goal of our work is to determine if the mechanisms of AOP can be used to improve the modularity of OS code. Specifically, we want to determine whether path-specific customizations can be considered to be crosscutting concerns, and whether they can be modularized using the mechanisms of AOP.Most AOP language research is in Java. To enable a range of experiments for operating systems written in C, we developed a paper design for AspectC. Conceptually and in syntax, AspectC is a simple subset of AspectJ [8,10]. As an initial experiment, we used AspectC to modularize the implementation of prefetching within page fault handling in the FreeBSD OS kernel.