Donna S. Reese

Increased Retention of Early Computer Science and Software Engineering Students Using Pair Programming

An important problem faced by many Computer Science and Software Engineering programs is declining enrollment. In an effort to reverse that trend at Mississippi State University, we have instituted pair programming for the laboratory exercises in the introductory programming course. This paper describes a study performed to analyze whether using pair programming would increase retention. An important goal of this study was not only to measure increased retention, but to provide insight into why retention increased or decreased. The results of the study showed that retention significantly increased for those students already majoring in Computer Science, Software Engineering, or Computer Engineering. In addition, survey results indicated that the students viewed many aspects of pair programming to be very beneficial to their learning experience.

An artificial immune system model for intelligent agents

Abstract This paper describes the human immune system and its functionalities from a computational viewpoint. The objective of this paper is to provide the biological basis for an artificial immune system. This paper will also serve to illustrate how a biological system can be studied and how inferences can be drawn from its operation that can be exploited in intelligent agents. Functionalities of the biological immune system (e.g., content addressable memory, adaptation, etc.) are identified for use in intelligent agents. Specifically, in this paper, an intelligent agent will be described for task allocation in a heterogeneous computing environment. Initial implementation of the agents will be described along with preliminary results. This research is not intended to develop an explicit model of the human immune system, but to exploit some of its functionalities in designing agent-based parallel and distributed control systems.

Using multiplayer games to teach interprocess communication mechanisms

An advanced operating system (OS) course teaches students how the OS mechanisms that they have learned in OS I are implemented. Solaris and Windows NT are used to illustrate these implementations. This course covers the major aspects of OS functionality and addresses both OS design issues and user level programming issues. The area of inter-process communication is not conceptually difficult for students to grasp, but the actual implementation and use of these concepts requires some practice. For the past three years, the author has experimented with the use of multi-player games as a mechanism for teaching students these programming constructs. This paper reports on these experiences.

The Biological Basis of the Immune System as a Model for Intelligent Agents

This paper describes the human immune system and its functionalities from a computational viewpoint. The objective of this paper is to provide the biological basis for an artificial immune system. This paper will also serve to illustrate how a biological system can be studied and how inferences can be drawn from its operation that can be exploited in intelligent agents. Functionalities of the biological immune system (e.g., content addressable memory, adaptation, etc.) are identified for use in intelligent agents. Specifically, in this paper, an intelligent agent will be described for task allocation in a heterogeneous computing environment. This research is not intended to develop an explicit model of the human immune system, but to exploit some of its functionalities in designing agent-based parallel and distributed control systems.

Near-critical path analysis of program activity graphs

Program activity graphs can be constructed from time-stamped traces of appropriate execution events. Information about the activities on the k longest execution paths is useful in the analysis of parallel program performance. In this paper, four algorithms for finding the near-critical paths of program activity graphs are presented and compared, including an efficient new algorithm that utilizes slack values calculated by the critical path method to perform a best-first search in linear space. The worst-case time and memory requirements of the new algorithm are in O(ke) and O(k+e), where e is the number of edges in the graph. Results confirming the efficiency of the algorithm are presented for five application programs. A framework for utilizing the near-critical path information is also described. The framework includes both statistical summaries and visualization capabilities.<<ETX>>

Object oriented Fortran for development of portable parallel programs

Parallel programming has to date remained inaccessible to the average scientific programmer. Parallel programming languages are generally foreign to most scientific applications programmers who only speak Fortran. Automatic parallelization techniques have so far proved unsuccessful in extracting large amounts of parallelism from sequential codes and do not encourage development of new, inherently parallel algorithms. In addition, there is a lack of consistency of programmer interface across architectures which requires programmers to invest a lot of effort in porting code from one parallel machine to another. This paper discusses the object oriented Fortran language and support routines developed at Mississippi State in support of parallelizing complex field simulations. This interface is based on Fortran to ease its acceptance by scientific programmers and is implemented on top of the Unix operating system for portability.<<ETX>>

Dynamic view-dependent partitioning for structured grids with complex boundaries for object-order rendering techniques

Object-order rendering techniques present an attractive approach to run-time visualization of structured grid data, particularly when combined with a parallel rendering paradigm such as image composition. The ability of this combination to exploit hardware exceeds that of parallel image order methods. However, certain configurations of grid boundaries prevent composition from being performed correctly. In particular when the boundary between two partitions contains concave sections, the partitions may no longer be depth sorted correctly, a requirement for some visualization techniques such as direct volume rendering. This occurs because the concave boundary prevents even the simple ordering of two adjacent partitions. If the data may be repartitioned such that it can be depth sorted correctly then an image composition approach is a viable option. To facilitate such an operation, we present an algorithm to analyze the geometric structure of a grid boundary and extract knowledge about how the boundary impacts depth sorting and therefore image composition. We then show through examples how this knowledge may be applied to create a set of partitions that may be properly depth sorted.

A placement examination for computer science II

Students enrolling in Computer Science II at Mississippi State University (MSU) have widely varying backgrounds. Some have taken the prerequisite course at MSU, some have transferred from community colleges offering the prerequisite, and some are new graduate students with undergraduate deficiencies. Proper placement of students in the introductory courses is necessary to give those students with little background in object-oriented software development an opportunity for success, while challenging students who may have had substantial programming experience elsewhere. The Department has developed and tested a placement examination. The examination helps students decide if they should enroll in an introductory course that assumes some previous programming experience without object-oriented software development, or if they should begin in Computer Science II that assumes knowledge of C++ with object-oriented design. The score on the placement exam demonstrated predictive power when trying to distinguish, coarsely, between those students who will probably pass the Computer Science II course and those students who are at risk of failing the course.

Structured Forensics Examination Planning with Domain Modeling: A Report of Three Experiment Trials

In any forensic investigation, planning and analysis activities are required in order to determine what digital media will be seized, what types of information will be sought in the examination, and how the examination will be conducted. Existing literature and suggested practices indicate that such planning should occur, but few tools provide support for such activities. Planning an examination may be an essential activity when investigators and technicians are faced with unfamiliar case types or unusually complex, large-scale cases. This article reports the results of empirical studies that evaluate two planning methods for planning computer forensics examinations: an experimental methodology that includes domain modeling and a typical planning method that does not include domain modeling. These studies were conducted to evaluate two research questions: Will the domain modeling of a computer forensics case during the planning phase result in an increased amount of evidence found in a digital forensics examination? Will an experimental “case domain modeling” methodology require a significant amount of additional effort when compared to a typical approach? Three experiment trials were conducted to evaluate the effectiveness of case domain modeling on simulated case scenarios. Analysis of the experiments indicates that case domain modeling in forensics planning requires an additional time investment and it can result in more evidence found during an examination and more effective keyword searches. Additionally, experimental data indicates that case domain modeling is most useful when the evidence disk has a relatively high occurrence of text-based documents and when vivid case background details are available.

Efficient rendering of multiblock curvilinear grids with complex boundaries

Domain decomposition is a popular technique for solving large computational problems that require data to be divided into smaller sub‐domains. The exact manner of decomposition depends on the computational needs of the algorithm and often introduces irregular boundaries. Each subdomain forms a block of a larger grid and can be solved or rendered separately by different processing nodes. Rendering of each sub‐domain can result in images which are then composited in a back‐to‐front or front‐to‐back manner. This scenario is useful when visualization is used concurrently with the simulation. However, the irregularity of boundaries may prohibit the correct image composition due to a visibility anomaly between the sub‐domains. In this paper, we present an algorithm based on object‐space partitioning to resolve this problem. To accelerate the partitioning process, two techniques are introduced. First, an image‐space partition representation is employed for fast assignment of data points to correct partitions. Secondly, a k‐d tree is used to subdivide the view‐space adaptively according to the complexity of the surface. This view‐space partition provides a trade‐off between performance and accuracy of the rendered image. Large gains in performance can be achieved with only small losses of accuracy. Two examples of curvilinear grids of different complexity are used to demonstrate the effectiveness of this scheme. Copyright