Christopher Nevison

Parallel computing in the undergraduate curriculum

Computer science students need to understand parallel computing, since it may become an integral part of their own careers. The best way to accomplish this is to integrate parallel computing concepts throughout the entire curriculum, from the introductory level up. As parallel computing becomes a part of several courses, it need not displace large segments of material that are currently in these courses; each course can contribute a small amount to the overall objective of understanding parallel computing. The paper presents a sample curriculum.

Dynamic Lot-Sizing When Demand Timing Is Uncertain

We characterize optimal solutions for the dynamic lot-sizing problem when demand quantities are known, but their timing is uncertain. The characterization states that for some possible history of demands following a period of production, there is a period with zero inventory before another period with production. Using this characterization, we outline a dynamic program for the solution of these problems. Some results from sample problems illustrate the variety of optimal solutions that can occur.

Teaching objects early and design patterns in Java using case studies

In order to teach object-oriented design and programming in introductory computer science it is imperative to teach objects from the very beginning of the course. The use of interacting objects is motivated by examples with an inherent complexity. We suggest that a case study approach to teaching object-oriented programming can provide a context with simplicity within complexity, so that simple versions of the case study program or simple pieces of a more complex program can be used to teach concepts at an introductory level. A case study provides a setting where a progression of successively more sophisticated programs can be developed to introduce standard topics of the introductory course within an increasingly familiar context. At the same time, the design of these programs can illustrate some of the fundamental principles of object-oriented design as embodied in basic design patterns.

Java resources for computer science instruction

The goal of this working group was to collect, evaluate, and foster the development of resources to serve as components of both new and revised traditional courses that emphasize object-oriented software development using Java. These courses could, for example, integrate Internet-based distributed programming, concurrency, database programming, graphics and visualization, human interface design and object-oriented development. They could therefore also be suitable as capstone courses in computer science. The focus of the working group was on tools and techniques, including demonstrations, projects, syllabi, and pedagogical patterns. The working group members are coordinating the development of a Web site (sol.pace.edu/iticse98) devoted to sharing such tools and techniques among educators.

A Cost Adjustment Heuristic for Dynamic Lot-Sizing with Uncertain Demand Timing

We define a new heuristic, based on the adjustment of set-up costs, for the dynamic lot-sizing problem when demand timing is uncertain. Using a range of simulated problems, we compare the performance of this cost adjustment heuristic with that of a safety lead time heuristic, Zangwills deterministic algorithm, which ignores uncertainty, and the optimal solution. Results show that the safety lead time heuristic works well for problems with high shortage costs and high probability of early demands, but poorly in other circumstances. The cost adjustment heuristic is quite robust, generally exceeds the performance of the safety lead time approach, and is relatively insensitive to variations in uncertainty.

How to develop and grade an exam for 20,000 students (or maybe just 200 or 20)

Although our students may spend only a class period working one of our exams, as instructors, we invest many more hours crafting the questions and grading their responses. How do we ensure our time is well-spent? What qualities contribute to an effective exam? How can we guarantee a fair evaluation of student performance?With an 18-year track record delivering a nationwide exam, the Advanced Placement Computer Science (AP CS) program has a wealth of experience in the area of exam development and administration. This special session will bring together members of the AP CS Development Committee and the Educational Testing Service to share some of their insights into how the experts do it.AP teachers will learn more about the exam for which they are preparing their students. College faculty will gain a better understanding of the metrics provided by the AP exam. All instructors will come away with practical and transferable ideas for successful exam tactics.

Critical Values For The Wilcoxon Signed-Rank Statistic

This table contains critical values and probabilities for the Wilcoxon Signed-Rank Statistic T+; n is the sample size, c1 and C2 are defined by P(T+ ≤ c1) = α and P(T+ ≥ C2) = α.

An undergraduate parallel processing laboratory

We discuss possibilities for setting up an undergraduate laboratory for parallel processing and how such a laboratory, based on transputers, can be used in a course on parallel processing.

Changes in the advanced placement computer science course: case studies and C++ (panel)

Case studies provide examples of good style, the use of language constructs, fundamental data structures, algorithms and applications. Moreover, case studies provide an economical way to deal with large programs. Large programs give the student practice in the management of complexity and motivate the use of certain programming practices, such as procedural decomposition, intermodule communication through parameter passing, data abstraction, and selection of data structures tailored to the needs of the problem.

From concrete to abstract: the power of generalization

We describe an assignment for students in a software engineering class or advanced programming class with emphasis on design. In the assignment students are given a program that solves a maze, with a display that shows the steps toward the solution. The given program has three variations of an iterative search (implemented using the strategy pattern), depth-first search, breadth-first search, best-first search (the latter using a priority queue). The students are asked to disentangle the problem-specific aspects of this code from the search strategy so as to define an abstract problem solver that can be applied to any problem fitting the model of step-by-step searching of a solution space. This requires three steps: defining appropriate interfaces that specify the information about the problem needed by the abstract solver, defining the abstract solver to find a solution using these interfaces, and defining the maze problem so as to implement these interfaces. With the abstract solver created, students should also be able to implement other problems fitting this model, such as the word-ladder game or a search in a graph for a Hamiltonian circuit, so that the abstract solver can be applied to them. The assignment demonstrates the power of generalization using abstract classes and interfaces as a bridge between concrete problems and the solution algorithm. This assignment is intended for a course in software engineering or an advanced programming course with emphasis on design. Students should already be familiar with object-oriented programming, inheritance, abstract classes and interfaces.