专业课程小型题库管理系统的研究

通常的题库管理系统都要根据教育测量理论．选择样本组进行测量,然后根据测量统计分析的结果,修改或选择合适的测试题以完成题库建设。大学计算机课程的自身特点。使其在选用通用题库系统时存在局限性。该题库一方面充分发挥教师的主动性．另一方面借鉴经典测量理论增强其规范性。     

基于项目反应理论的自适应考试系统的研究与设计

针对基于经典测量理论的传统考试暴露出越来越多的缺点和不足这一情况,提出基于项目反应理论的计算机自适应考试系统。它能根据被试者的能力水平选择相应难度的题目,实现更快、更准确地估计出被试者的能力值。对自适应考试系统中所涉及的几个关键技术(参数估计、参数等值、题目曝光率控制、题库建设等)进行研究与改进,实现了系统的设计与开发。实验结果表明,该系统可以有效地测试出被试者的能力值,达到了预期目的。     

基于题目反应理论的题库模型的研究与设计

题库必须建立在一定教育测量理论上。题目反应理论是一种现代的题目分析理论,用于测量学生的潜在能力水平。根据ICC三参数模型构建的题库将通过区分度参数、难度参数、拟猜测参数来计算出学生的能力参数水平,并以此构建题库的参数,为构建自适应测验系统打下扎实的数据基础。     

经典测量理论在小型专业题库中的应用研究

学校中生源的稳定性使得经典测量理论在专业题库建设中有其可行性,然而经典测量理论的操作规则要求选取大量样本,进行反复测试,大学教育与计算机课程的自身特点又限制了上述测试的实现.在对经典测量理论改进的基础上,设计了小型计算机专业题库.试卷分析表明,此方法能有效地完成大学专业考试,并能客观评价学生水平.     

网络自适应测评控制系统设计

为了测评不同个人的计算机实际应用能力,以项目反应理论（IRT）为理论基础建立题库和自适应测评系统,根据被试的作答情况选择最适合的试题,从而较精确贴切地测量被试的能力,并通过样本试测机制和难度参数调整机制,实现题库的自我动态维护.该系统的测量精度比传统的测评方式更高,可推广到其他能力的测评.     

自动组卷系统中试题库的研究与设计

试题库是自动组卷系统的基础,合理的试题库结构能提高组卷效率。以经典测量理论为指导,对试题库的建设进行研究,设计了题库结构,分析试题属性,给出了实体关系。     

机助自适应考试(CAT)系统题库的仿真研究

该文用模拟的方法讨论了机助自适应考试系统中题库的容量、知识点分布和题目参数的分布。容量模拟试图在题库的规模和实用性上作一个折中，使得测试能够正确地完成而题库的量尽量的少，因为建立题库的花费非常的大；知识点分布模拟和题目参数的分布模拟，希望找出能够让自适应算法发挥最大优势的知识点分布状况和题目参数分布状况。基于实验结果，对当前的HSK（汉语水平考试）考试系统的题库的扩充方法进行了研究，并且建立信息管理模块对题库参数进行优化。     

最大信息量选题策略的自适应测试系统

随着心理与教育测量理论以及其与计算机技术相结合的不断研究和发展, 基于计算机的自适应测试成为了一种新型的测试形式.在分析、阐述计算机自适应测试理论和最大信息量选题策略的基础之上, 设计与实现了一个基于最大信息量法选题策略的自适应测试系统. 通过实验对被试者估计能力值、总信息量值、最大信息量值、试题参数等的变化进行分析与总结, 进而证明本系统的有效性. 最后对最大信息量选题策略研究做出总结, 针对其存在试题曝光度较高的问题给出了解决思路.     

计算机自适应考试(CAT)系统题库的设计与实现

计算机自适应考试(CAT)系统以其试题的难度、数量自适应考生个性化需求而日益得到教育界的重视。本文基于项目反应理论(IRT),设计了一个适应于CAT系统的题库,该题库采用三参数Logistic模型(3PLM)拟合项目特征曲线,运用联合极大似然估计法(JML)对项目参数进行估计,再通过评价函数对题库参数进行控制和优化,使得题库能够更好地适合不同考生的特点。     

在线测试智能组卷策略研究

本文提出一种新的在线测试智能组卷方法,以学生的预先能力水平为基础,假设学生的能力水平改变量服从标准正态分布,计算出一组学生能力水平的预期改变量,由学生预先能力水平与这组预期改变量的和出发,从题库中抽取出一组题目组成试卷对学生进行测试.通过计算机模拟试验,上述方法对于被试能力水平的估计值达到了较好的精度.     

Fast and precise points-to analysis

Many software engineering applications require points-to analysis. These client applications range from optimizing compilers to integrated program development environments (IDEs) and from testing environments to reverse-engineering tools. Moreover, software engineering applications used in an edit-compile cycle need points-to analysis to be fast and precise.In this article, we present a new context- and flow-sensitive approach to points-to analysis where calling contexts are distinguished by the points-to sets analyzed for their call target expressions. Compared to other well-known context-sensitive techniques it is faster in practice, on average, twice as fast as the call string approach and by an order of magnitude faster than the object-sensitive technique. In fact, it shows to be only marginally slower than a context-insensitive baseline analysis. At the same time, it provides higher precision than the call string technique and is similar in precision to the object-sensitive technique. We confirm these statements with experiments using a number of abstract precision metrics and a concrete client application: escape analysis.     

源代码分析技术的理论与实践发展

源代码分析技术对于软件安全缺陷分析是一项非常重要的手段.分析了软件源代码分析工具的技术手段和发展过程,最后对源代码分析的理论和实践进行了分析总结.     

C语言的别名分析方法研究

别名分析对于数据流分析、程序优化和分析工具的实现非常重要.文章提出了一种需求驱动,流非敏感的分析算法来解决指针别名问题.通过构造程序表达式图(PEG)把指针别名问题转化成判断两个指针节点是否是联通的问题,它不同于传统的别名分析方法,它不需要构造别名集合和对其求交集,所以提高了分析指针别名的效率.     

A system to assist survey analysts

The researcher who knows little about computers but wants to conduct a survey and analyse the results by computer can land himself in some difficulty if he does not appreciate some of the problems of computerization. This paper describes a system which is designed to aid such a person by providing assistance with the design of the questionnaire, the capturing of the data and the final analyses.     

The use of protocol analysis for determining ability requirements for personnel selection on a computer-based task

Abstract

The role of cognitively oriented tasks in the workplace continues to increase as automation of physical task components advances. Difficulties in automating the operator's cognitive processes have placed a renewed emphasis on the human component in advanced manufacturing systems. While traditional task analysis techniques have made significant contributions to improving productivity when important task elements are visually observable, their focus on manual task procedures make them less effective for cognitively oriented activities. This research has made a first attempt at integrating techniques from several disciplines to develop a cognitive task analysis methodology. The utility of this combined approach is examined for a new system being tested in the United States Postal Service. This task requires operators to encode, via a keyboard, addresses presented on a video display terminal. Results support the hypothesis that, for cognitively oriented tasks, a consensus based analysis technique (the Position Analysis Questionnaire) can be significantly improved by including data from task analysis provided the methodology is suitable for identifying non-physical task components.     

A novel analysis space for pointer analysis and its application for bug finding

The size of today’s programs continues to grow, as does the number of bugs they contain. Testing alone is rarely able to flush out all bugs, and many lurk in difficult-to-test corner cases. An important alternative is static analysis, in which correctness properties of a program are checked without running it. While it cannot catch all errors, static analysis can catch many subtle problems that testing would miss.We propose a new space of abstractions for pointer analysis—an important component of static analysis for C and similar languages. We identify two main components of any abstraction—how to model statement order and how to model conditionals, then present a new model of programs that enables us to explore different abstractions in this space. Our assign-fetch graph represents reads and writes to memory instead of traditional points-to relations and leads to concise function summaries that can be used in any context. Its flexibility supports many new analysis techniques with different trade-offs between precision and speed.We present the details of our abstraction space, explain where existing algorithms fit, describe a variety of new analysis algorithms based on our assign-fetch graphs, and finally present experimental results that show our flow-aware abstraction for statement ordering both runs faster and produces more precise results than traditional flow-insensitive analysis.     

基于因子分析法和聚类分析法的副省级城市宜居情况聚类评价

重点选取了15个副省级城市的第一产业比重、人口密度、人均绿地、园林面积、医院数目,市政建设面积、地方财政税收等42个指标,使用SPSS作为计算工具,使用因子分析方法简化评价指标,计算相关系数矩阵,判别因子分析可行性,利用主成分分析法求因子载荷,将因子进行旋转得出更有实际意义的因子解释,并计算因子得分,利用该结果计算Mi...     

Cost analysis of object-oriented bytecode programs

Cost analysis statically approximates the cost of programs in terms of their input data size. This paper presents, to the best of our knowledge, the first approach to the automatic cost analysis of object-oriented bytecode programs. In languages such as Java and C#, analyzing bytecode has a much wider application area than analyzing source code since the latter is often not available. Cost analysis in this context has to consider, among others, dynamic dispatch, jumps, the operand stack, and the heap. Our method takes a bytecode program and a cost model specifying the resource of interest, and generates cost relations which approximate the execution cost of the program with respect to such resource. We report on COSTA, an implementation for Java bytecode which can obtain upper bounds on cost for a large class of programs and complexity classes. Our basic techniques can be directly applied to infer cost relations for other object-oriented imperative languages, not necessarily in bytecode form.     

数据分析需求与实现

数据分析是从海量数据中发现隐含信息或知识的过程。基于一个公安破案辅助数据分析系统,深入研究数据分析任务的需求与实现,提出首先规划分析思路、细化分析功能,然后用多视角数据透视和智能分析两种手段,从微观与宏观、定量与定性等不同角度互为补充地使系统具有完备的分析功能。该研究对如何开发具有实用价值的数据分析系统有普遍的指导意义。