Computer programming is a process. Successful programming involves incrementally building and testing a solution. Students' ability to program is typically determined by an assessment of the end-product of a programming session rather than an examination of the actual process students are engaged in. A prerequisite to assessing a student's programming process is having access to that process. While direct one-on-one observation of students while they code has the potential to yield high-quality data, it does not scale well to large classes. One scalable approach is to automatically capture edit events through IDE instrumentation, and programmatically assess the resulting data. In this poster we report on our work to date in developing and deploying a plug-in for Eclipse's Java Development Tools (JDT), explore the data we have collected to date, compare our results with those reported in previous work, and discuss possible directions for future work in using this data for assessment of students' programming process.

This paper details our experiences with design and implementation of data science curriculum at University at Buffalo (UB). We discuss (i) briefly the history of project, (ii) a certificate program that we created, (iii) a data-intensive computing course that forms the core of the curriculum and (iv) some of the challenges we faced and how we addressed them. Major goal of the project was to improve the preparedness of our workforce for the emerging data-intensive computing area. We measured this through assessment of student learning on various concepts and topics related to data-intensive computing. We also discuss the best practices in building a data science program. We highlight the importance of external funding support and multi-disciplinary collaborations in the success of the project. The pedagogical resources created for the project are freely available to help educators and other learners navigate the path to learning data science. We expect this paper about our experience will provide a road map for educators who desire to introduce data science in their curriculum.

An enormous challenge when the Internet matured into a mainstream technology was meeting the information technology workforce needs in a competitive business environment. In anticipation of a similar scenario for upcoming Grid technology we are in the process of implementing a comprehensive multi-tier NSF-supported adaptation of Grid technology in education. The project addresses the abovementioned challenge at three important levels of our educational system: the undergraduate, the graduate and the industrial training. Our Grid technology-based curriculum has been developed for a sequence of two new courses for senior level undergraduates. Some courses would be taught at the graduate level with emphasis on research. Additionally, seminars are planned for spreading Grid awareness to the local businesses and industries by using domain-dependent Grid applications. This work presents the details of the model we call GridForce (Grid For Research Collaboration and Education) and our experiences with its implementation, with the objective of improving the technical preparedness of the workforce for the Grid.

This paper reports research on the effect of prior programming experience on success in an objects-first CS1. In an objects-first, approach students are taught from the very beginning to think in terms of objects and the fundamentals of object-oriented programming, encapsulation, inheritance, and polymorphism. These concepts are introduced before traditional selection and iterative constructs. The finding that students with prior programming experience do not do better than those without such experience flies in the face of conventional wisdom.

An integrated checkpointing and recovery scheme which exploits the low latency and high coverage characteristics of a concurrent error detection scheme is presented. Message dependency, which is the main source of multistep rollback in distributed systems, is minimized by using a new message validation technique derived from the notion of concurrent error detection. The concept of a new global state matrix is introduced to track error checking and message dependency in a distributed system and assist in the recovery. The analytical model, algorithms and data structures to support an easy implementation of the new scheme are presented. The completeness and correctness of the algorithms are proved. A number of scenarios and illustrations that give the details of the analytical model are presented. The benefits of the integrated checkpointing scheme are quantified by means of simulation using an object-oriented test framework.

A checkpointing and recovery scheme which exploits the low latency and high coverage characteristics of a hardware error detection scheme is presented. Message dependency which is the main source of multi-step rollback in distributed systems is minimized by using a new message validation technique derived from hardware-assisted error detection. The main contribution of this paper is the development of an analytical model to establish the completeness and correctness of the new scheme. A novel concept of global state matrix is defined to keep track of the global state in a distributed system and assist in recovery. An illustration is given to show the distinction between conventional and the new recovery schemes.

A simple, inexpensive and time/space efficient signature technique for process monitoring is presented. In this technique, a known signature function is applied to the instruction stream at compilation phase and when the accumulated signature forms an m-out-of-n code, the corresponding instructions are tagged. Error checking is done at run-time by monitoring the signatures accumulated at the tagged locations to determine whether they form m-out-of-n codes. This approach of signature checking does not require the embedding of reference signatures at compilation, thereby leading to savings in memory as well as in execution time. The m-out-of-n code approach offers high error coverage and controllable latency. The results of the experiments conducted to verify the controllability of the latency are discussed. One of the distinguishing features of the proposed scheme is the elimination of reference signatures, which are the main source of memory and time overhead in the existing techniques.>

A solution is obtained to the problem of defining a software measure or a family of measures which simultaneously detect those aspects of software complexity that are detected by the software science measures and the cyclomatic number. The authors present a family of measures, called weighted measures that is built on the software science measures by adding weights to certain operators and operands; the size of the weights is determined by a theorem which relates nesting levels and the cyclomatic number. Thus, by construction the weighted measures synthesize the software science measures and the cyclomatic number. Further, by applying the weighted measures, the software science measures, and the cyclomatic number to sample programs, it is shown that the weighted measures also synthesize in practice the software science measures and the cyclomatic number.>