学生项目团队对课程教学效果支撑的实践研究

以学生项目团队为教学组织单位,以"程序设计基础"这门课程为实验点,探讨大众普及式的项目团队对计算机类课程教学效果的影响和作用,阐述如何以学生项目团队为依托,使课上与课下有机结合的教学模式,即通过优化教学内容、改变授课方式、创新实践方法等一系列举措,使学生变被动为主动地接收学科知识,在潜移默化中培养学生的专业技能和职业素养。     

Using a formal specification contractually

A commonly made criticism of formal methods is that they increase costs. Selective use of formal methods to define critical requirements can, however, lead to a significant decrease in lifecycle costs. In particular the economic and technical benefits of outsourcing the development of software can be fully realized and the cost of outsourcing slightly reduced by use of a formal specification. In this paper we describe a development in which a formal specification prepared by the customer formed part of the contract with the supplier. We conclude that this use of a formal specification can reduce risks and costs for all concerned and can help foster fruitful and co-operative relations in situations which are often fraught with confrontation.Published with the permission of the controller of Her Britannic Majesty's Stationery Office.     

WEB编程中脚本漏洞的分析与防范

网络安全是每一个计算机用户和WEB程序员必须面对的问题,本文针对WEB编程中存在的几个典型脚本漏洞进行了实例分析,并给出适当的防范措施,期望引起WEB程序员对网络安全的重视。     

Applying fuzzy multi-objective linear programming to project management decisions with the interactive two-phase method

The aim of this paper is to develop an interactive two-phase method that can help the Project Manager (PM) with solving the fuzzy multi-objective decision problems. Therefore, in this paper, we first revisit the related papers and focus on how to develop an interactive two-phase method. Next, we establish to consider the imprecise nature of the data by fulfilling the possibilistic programming model, and we also assume that each objective work has a fuzzy goal. Finally, for reaching our objective, the detailed numerical example is presented to illustrate the feasibility of applying the proposed approach to PM decision problems at the end of this paper. Results show that our model can be applied as an effective tool. Furthermore, we believe that this approach can be applied to solve other multi-objective decision making problems.     

An approach to literate and structured formal developments

We present an approach to the literate and structured presentation of formal developments. We discuss the presentation of formal developments in a logical framework and distinguish three aspects: language-related aspects, structural aspects of proofs, and presentational aspects. We illustrate the approach by two examples: a simple mathematical proof of the Knaster-Tarski fixpoint theorem, and a formalization of the VDM development of a revision management system.     

Multiple robot programming using a concurrent logic language

Advances in robotics has led to the cooperation of multiple robots among themselves and with their industrial automation environment. Efficient interaction with industrial robots thus becomes one of the key factors in the successful utilization of this modern equipment. When multiple manipulators have to be coordinated, there is a need for a new programming approach that facilitates and encompasses the needs of concurrency, synchronization, timing, and communication. Most robot languages have been developed with little attention being given to the integration of the robot with its environment. Currently, there is a gap between the robot capabilities, the task definition environment, and language facilities supplied to use robots.This paper analyzes the needs and then establishes that a concurrent logic programming approach is a step towards achieving a multi-robot knowledgeable task programming. In particular, the FCP dialect of concurrent Prolog is demonstrated, and analyzed.This research is partially supported by the Paul Ivanier Center for research in robots and production management.     

Pair dynamics in team collaboration

From a recent field survey with a group of professional pair programmers, it was revealed that the programmers perceive a partner’s personality, cognitive style and communication skills as the top three factors that lead to prudent pair programming. Based on this finding, the factors personality and communication skills, along with gender were selected for an experiment to analyze if a partner’s human, intrinsic values influence the pair programming experience, specifically in the levels of satisfaction, compatibility, communication, and confidence. A total of 128 students majoring in Management Information Systems, Information Systems, and Information Technology participated in the experiment. Of the 68 undergraduates, 40 were first-year students and 28 were juniors; the remaining 60 were Master’s degree graduate students. The students were formed into a total of 64 pairs based on their personality, level of communication skills, and gender. A total of three visits were made. During the first two visits, a set of four programming problems was used in four programming sessions lasting 45 min each; two were individual programming sessions and two were pair programming sessions. At the end of each visit, a questionnaire was administered and collected. The questionnaire results revealed that the various Myers–Briggs Type Indicator (MBTI) personality combinations did not significantly influence the levels of communication, satisfaction, confidence, and compatibility. The pairs that exhibited a high level of communication between partners did not necessarily experience a high level of satisfaction or exhibit compatibility between partners, nor did they have a high level of confidence regarding the finished product. The communication skill level seemed to have an impact on communication only. Similar to many previous gender-focused literatures, the same gender pairs did exhibit significantly higher levels of communication, satisfaction and compatibility than the mixed gender pairs. Within the same gender pairs, the female–female pairs showed a much higher level than the male–male pairs in those categories. Contrariwise, the same gender pairs did not show a significantly higher confidence level than the mixed gender pairs about their finished product.     

Direct off-line robot programming via a common CAD package

This paper focuses on intuitive and direct off-line robot programming from a CAD drawing running on a common 3-D CAD package. It explores the most suitable way to represent robot motion in a CAD drawing, how to automatically extract such motion data from the drawing, make the mapping of data from the virtual (CAD model) to the real environment and the process of automatic generation of robot paths/programs. In summary, this study aims to present a novel CAD-based robot programming system accessible to anyone with basic knowledge of CAD and robotics. Experiments on different manipulation tasks show the effectiveness and versatility of the proposed approach.     

LMNtal as a hierarchical logic programming language

LMNtal (pronounced “elemental”) is a simple language model based on hierarchical graph rewriting that uses logical variables to represent connectivity and membranes to represent hierarchy. LMNtal is an outcome of the attempt to unify constraint-based concurrency and Constraint Handling Rules (CHR), the two notable extensions to concurrent logic programming. LMNtal is intended to be a substrate language of various computational models, especially those addressing concurrency, mobility and multiset rewriting. Although the principal objective of LMNtal was to provide a unifying computational model, it is of interest to equip the formalism with a precise logical interpretation. In this paper, we show that it is possible to give LMNtal a simple logical interpretation based on intuitionistic linear logic and a flattening technique. This enables us to call LMNtal a hierarchical, concurrent linear logic language.     

利用结对编程技术改进程序设计实践教学

介绍了结对编程的概念,阐述了其作为学习编程技能的一种过程改进策略在国外计算机专业教学中的实验效果,并论述了相关影响因素。     

Multi-coefficients goal programming

In today’s increasingly competitive business environment, maintaining profit margins or quantities of goods sold is an important issue for businesses. Accordingly, more and more industries use group pricing discrimination strategy to attract potential customers in order to increase competitive advantage. Hence, to find ways maximize profit and to minimize total cost, group pricing discrimination strategy has become an important issue for decision makers. Unfortunately, these types of problems cannot be solved by any current goal programming models. The objective of this study is to deduce a new method, which we call the multi-coefficients goal programming, for group pricing discrimination problems. In addition, an example is given to illustrate the correctness and usefulness of the proposed model.     

Using the analytic hierarchy process and goal programming for information system project selection

One of the basic information system (IS) management activities is the planning of IS projects. Specifically, such planning requires the selection of IS projects and allocation of resources to complete them. This paper presents an improved IS project selection methodology that combines the recently applied IS project selection methodologies of the analytic hierarchy process (AHP) within a goal programming (GP) model framework. This new combination of the AHP and GP methodologies helps to overcome the weaknesses observed when either methodology is used separately. The combined AHP and GP methodology is illustrated through an example.     

Scalability of hybrid programming for a CFD code on the Earth Simulator

The Earth Simulator (ES) is an SMP cluster system. There are two types of parallel programming models available on the ES. One is a flat programming model, in which a parallel program is implemented by MPI interfaces only, both within an SMP node and among nodes. The other is a hybrid programming model, in which a parallel program is written by using thread programming within an SMP node and MPI programming among nodes simultaneously. It is generally known that it is difficult to obtain the same high level of performance using the hybrid programming model as can be achieved with the flat programming model.

In this paper, we have evaluated scalability of the code for direct numerical simulation of the Navier–Stokes equations on the ES. The hybrid programming model achieves the sustained performance of 346.9 Gflop/s, while the flat programming model achieves 296.4 Gflop/s with 16 PNs of the ES for a DNS problem size of 256³. For small scale problems, however, the hybrid programming model is not as efficient because of microtasking overhead. It is shown that there is an advantage for the hybrid programming model on the ES for the larger size problems.     

An integer programming formulation for the project scheduling problem with irregular time-cost tradeoffs

Four integer programming formulations are studied for the irregular costs project scheduling problem with time/cost trade-offs (PSIC). Three formulations using standard assignment type variables are tested against a more novel integer programming formulation. Empirical tests show that in many instances the new formulation performs best and can solve problems with up to 90 activities in a reasonable amount of time. This is explained by a reduced number of binary variables, a tighter linear programming (LP) relaxation, and the sparsity and embedded network structure of the constraint matrix of the new formulation.     

A two-stage stochastic programming approach for project planning with uncertain activity durations

This paper investigates the problem of setting target finish times (due dates) for project activities with random durations. Using two-stage integer linear stochastic programming, target times are determined in the first stage followed by the development of a detailed project schedule in the second stage. The objective is to balance (1) the cost of project completion as a function of activity target times with (2) the expected penalty incurred by deviating from the specified values. It is shown that the results may be significantly different when deviations are considered, compared to when activities are scheduled as early as possible in the traditional way. For example, the optimal target completion time for a project may be greater than the makespan of the early-start schedules under any scenario. To find solutions, an exact algorithm is developed for the case without a budget constraint and is used as a part of a heuristic when crashing is permitted. All computational procedures are demonstrated on a set of 150 benchmark problems consisting of 90 activities each.     

Concurrent programming in VISO

Concurrent programming is more difficult to use and understand than sequential programming. In order to simplify this type of programming a number of approaches have been developed such as visual programming. Visual Occam (VISO) is a visual programming language for concurrent programming. It has a graphical syntax based on the language Occam and its semantics is represented both in petri net and process calculus. This paper presents a modular visual approach to write concurrent programs using the VISO language. Concurrent programs in VISO are specified graphically at different levels of abstraction. This paper describes this modular visual approach by constructing two examples in VISO. The first example is a simple concurrent program and it is mainly used to show the details of constructing a concurrent program in VISO. The second example is a larger concurrent program with more levels of abstraction. Copyright © 2000 John Wiley & Sons, Ltd.     

The progressive party problem: Integer linear programming and constraint programming compared

Many discrete optimization problems can be formulated as either integer linear programming problems or constraint satisfaction problems. Although ILP methods appear to be more powerful, sometimes constraint programming can solve these problems more quickly. This paper describes a problem in which the difference in performance between the two approaches was particularly marked, since a solution could not be found using ILP.The problem arose in the context of organizing a progressive party at a yachting rally. Some yachts were to be designated hosts; the crews of the remaining yachts would then visit the hosts for six successive half-hour periods. A guest crew could not revisit the same host, and two guest crews could not meet more than once. Additional constraints were imposed by the capacities of the host yachts and the crew sizes of the guests.Integer linear programming formulations which included all the constraints resulted in very large models, and despite trying several different strategies, all attempts to find a solution failed. Constraint programming was tried instead and solved the problem very quickly, with a little manual assistance. Reasons for the success of constraint programming in this problem are identified and discussed.     

Immune programming

This paper describes ‘Immune Programming’, a paradigm in the field of evolutionary computing taking its inspiration from principles of the vertebrate immune system. These principles are used to derive stack-based computer programs to solve a wide range of problems.An antigen is used to represent the programming problem to be addressed and may be provided in closed form or as an input/output mapping. An antibody set (a repertoire), wherein each member represents a candidate solution, is generated at random from a gene library representing computer instructions. Affinity, the fit of an antibody (a solution candidate) to the antigen (the problem), is analogous to shape-complementarity evident in biological systems. This measure is used to determine both the fate of individual antibodies, and whether or not the algorithm has successfully completed.When a repertoire has not yielded affinity relating algorithm completion, individual antibodies are replaced, cloned, or hypermutated. Replacement occurs according to a replacement probability and yields an entirely new randomly-generated solution candidate when invoked. This randomness (and that of the initial repertoire) provides diversity sufficient to address a wide range of problems. The chance of antibody cloning, wherein a verbatim copy is placed in the new repertoire, occurs proportionally to its affinity and according to a cloning probability. The chances of an effective (high-affinity) antibody being cloned is high, analogous to replication of effective pathogen-fighting antibodies in biological systems. Hypermutation, wherein probability-based replacement of the gene components within an antibody occurs, is also performed on high-affinity entities. However, the extent of mutation is inversely proportional to the antigenic affinity. The effectiveness of this process lies in the supposition that a candidate showing promise is likely similar to the ideal solution.This paper describes the paradigm in detail along with the underlying immune theories and their computational models. A set of sample problems are defined and solved using the algorithm, demonstrating its effectiveness and excellent convergent qualities. Further, the speed of convergence with respect to repertoire size limitations and probability parameters is explored and compared to stack-based genetic programming algorithms.     

Parallel programming for a chess endgame database

This paper presents a parallel implementation in APL of an algorithm to set up a database for the KRK -endgame in chess. It shows clearly the techniques necessary to achieve the parallelism and thereby proves that APL can be a valuable productivity increasing aid in this kind of Artificial Intelligence (AI)-research. The complete APL-functions are given in the Appendix. Both reversed pigeon hole and bit map techniques are used. Move generation is table driven with a new technique to cater for the blockage of sliding pieces like a rook. In order to maintain parallelism ‘if’ statements are avoided and extensive use is made of compression and identity elements.