程序理解中一种基于特征符号的粗匹配方法

所有基于Plan的自动程序理解工具都采用把源码段跟标准Plan库中标准Plan相比较的方法来得到源码语义信息,从而达到程序理解的目标.以程序段的特征信息为索引项,对标准Plan库进行穷尽式快速粗匹配,以克服自下而上程序理解模式搜索强度大,实际应用性不强的弱点,达到快速粗粒度匹配的目标.方法的局限是匹配过程中存在信息遗漏,需要进一步采用模糊推理机制对潜在Plan进行相似性度量.     

一种基于模糊推理的细匹配方法

所有基于Plan的自动程序理解工具都采用把源码段跟标准Plan相比较的方法来得到源码语义信息。采用程序段的特征信息作为匹配索引项进行粗匹配可以大大加快匹配效率,但完全依赖特征信息作为匹配代理造成了信息流失。该文提出了一种基于模糊推理的细匹配方法来进行相似度分析,目的是对粗匹配得到的潜在Plan集进行相似度分析以得到最终候选Plan集。     

自动搜索库调用系统的设计与实现

本文介绍了库调用自动搜索系统的设计与实现,可以在指定的目录下搜索系统源码从而导出系统各模块的依赖关系,对于系统分析、系统集成以及集成测试都能起到良好的参考作用。     

应用特征整合理论优化基于图像符号的信息可视化设计

特征整合理论是视觉注意方面最有影响力的重要理论之一,为优化视觉沟通提供了理论基础.文中提出应用玫瑰曲线设计花形图像符号的方法,利用用户在前注意阶段的自动的、无意识的加工过程,引导用户觉察到目标信息,从而优化用户对信息可视化设计的视觉搜索过程.文中提出的图像符号在信息可视化的应用中能够映射6个变量,变量特征容易识别,并且便于表现2个变量间的比例关系.通过对2008年美国教育经费投入的案例研究,实践了基于明确信息搜索目标的信息可视化设计和探索性的信息可视化设计;通过眼动实验测试用户的首次注视时间和5 s的注视时间,探索了用户优先处理的视觉对象,提出了运用花形图像符号控制符号视觉特征相似性以优化用户视觉体验的方法.     

一种经验库制导的浮点程序优化加速策略

为了保障数值程序的准确与高效,浮点程序自动优化成为了近年来学术界关注的一项新兴技术.该技术的核心思想是将经典的数值分析理论总结成程序转换规则,并利用规则将浮点程序以计算过程更为稳定的算法进行自动重写,从而使数值程序稳定高效且易于维护.然而,现有浮点程序自动优化方法的优化效率是其主要瓶颈.随着越来越多的数值程序转换规则被发现与总结,自动优化框架的规则库会越来越大,传统优化方法在规则库中遍历所有优化规则的过程也变得越来越困难.本文提出了一种经验库制导的浮点程序优化加速策略,该策略基于浮点误差成因的相似性原理,将已成功优化浮点程序对应的符号与结构特征抽取出来,并以散列的方式将优化该程序涉及到的规则序列保存在一个优化经验库中.当新的浮点数值程序需要进行自动优化时,本文算法首先计算其符号结构特征与经验库中各记录的相似度.符号结构相似度较高的记录所对应的规则序列会被优先用于浮点程序重写,从而得到优化程序.随着优化程序的增多,经验库的规模会逐渐增大,经验库的散列化分区存储设计保证了其检索与匹配效率.在浮点程序优化基准用例集FPBench和开源物理引擎OpenRelativity上的实验表明,在优化后...     

基于语义网络的海量源码搜索引擎

提出一种通过类自然语言输入在海量源码库中进行代码搜索的方法,旨在提高开源代码在方法层面的重用性。相比于传统的关键字匹配的海量源码搜索方案与基于自然语言的上下文相关的项目内定位方法,本文的程序分析结合语义网络的算法既可解决前者由于源码中缩写与近义词问题带来的目标无法匹配的问题,同时也可解决基于自然语言的源码定位受限于指定项目无法在应用于海量源码搜索的限制。最后通过实验验证引擎的可靠性与可用性。     

一种基于程序理解的N-S图生成算法

程序理解是计算机自动实现程序源码分析、获得程序结构相关知识的技术,在程序理解信息提取的基础上,针对程序函数级以下结构的源码分析,运用计算机可视化技术,提出一种N-S图表示程序函数的算法,运用该算法可解决图元设计、图元缩放与定位、图元嵌套等问题。算法运行结果表明,该算法能够快速有效地生成N-S图,提高程序理解的效率。     

JUTA: 一个Java自动化单元测试工具

描述了一个Java自动化的单元测试工具JUTA.JUTA首先调用工具Soot解析单个Java方法的源码,并将源码解析成一个控制流图.在此基础上,采用符号执行的方法分析控制流图上的路径.工具能够自动地产生满足覆盖率标准的程序的测试用例.这种方法产生的所有测试用例都是可执行的,并且一般来说具有较小的测试用例数.如果用户能够合理地给出描述程序错误的断言,框架JUTA能够自动地检查源码中部分特定类型的错误.实验结果表明工具对Java单元代码的动态测试和静态测试均能在可接受的时间内给出有效的结果.     

微装配中零部件搜索方法

针对如何快速且准确地在微装配的显微视野中寻找到目标零部件,并获取目标零部件的全局视觉信息的问题,提出了一种基于显微视觉倍率切换的微装配零部件搜索机制.详细分析了如何确定自动搜索步长;论述了自动搜索策略的原理与过程:通过自动扫描目标平面,以准确识别出目标平面内的微零部件,有效地克服了大范围微装配中显微视觉范围远小于操作域的局限性,保证了微装配零部件目标始终呈现在不同显微倍率视野中,为微装配机器人的进一步操作奠定了视觉基础.实验结果表明:提出的搜索方法搜索成功率达到了95％,平均搜索时间为28 s.     

基于回溯树的Web服务自动组合

在服务规则库的基础上,介绍了回溯树与完备回溯树的概念,并证明了其重要性质.提出了基于回溯树的Web服务自动组合方法.该方法采用分步分治的思想进行服务的自动组合:1) 针对用户请求的输出对象生成完备回溯树;2) 在完备回溯树中选取最佳生成源(生成路径);3) 将生成路径合成为可执行的流程服务.与已有的基于图搜索的自动Web服务组合方法相比,该方法极大地减小了搜索空间,避免了循环搜索,能够满足单目标和多目标的用户请求.仿真实验结果表明,该方法能够在大规模的服务规则库中进行快速的服务组合,从而满足用户请求.     

Applying Plan Recognition Algorithms To Program Understanding

Program understanding is often viewed as the task of extracting plans and design goals from program source. As such, it is natural to try to apply standard AI plan recognition techniques to the program understanding problem. Yet program understanding researchers have quietly, but consistently, avoided the use of these plan recognition algorithms. This paper shows that treating program understanding as plan recognition is too simplistic and that traditional AI search algorithms for plan recognition are not suitable, as is, for program understanding. In particular, we show (1) that the program understanding task differs significantly from the typical general plan recognition task along several key dimensions, (2) that the program understanding task has particular properties that make it particularly amenable to constraint satisfaction techniques, and (3) that augmenting AI plan recognition algorithms with these techniques can lead to effective solutions for the program understanding problem.     

Program Understanding as Constraint Satisfaction: Representation and Reasoning Techniques

The process of understanding a source code in a high-level programming language involves complex computation. Given a piece of legacy code and a library of program plan templates, understanding the code corresponds to building mappings from parts of the source code to particular program plans. These mappings could be used to assist an expert in reverse engineering legacy code, to facilitate software reuse, or to assist in the translation of the source into another programming language. In this paper we present a model of program understanding using constraint satisfaction. Within this model we intelligently compose a partial global picture of the source program code by transforming knowledge about the problem domain and the program itself into sets of constraints. We then systematically study different search algorithms and empirically evaluate their performance. One advantage of the constraint satisfaction model is its generality; many previous attempts in program understanding could now be cast under the same spectrum of heuristics, and thus be readily compared. Another advantage is the improvement in search efficiency using various heuristic techniques in constraint satisfaction.     

Hierarchical planning involving deadlines, travel time, and resources

This paper describes a planning architecture that supports a form of hierarchical planning well suited to applications involving deadlines, travel time, and resource considerations. The architecture is based upon a temporal database, a heuristic evaluator, and a decision procedure for refining partial plans. A partial plan consists of a set of tasks and constraints on their order, duration, and potential resource requirements. The temporal database records the partial plan that the planner is currently working on and computes certain consequences of that information to be used in proposing methods to further refine the plan. The heuristic evaluator examines the space of linearized extensions of a given partial plan in order to reject plans that fail to satisfy basic requirements (e.g., hard deadlines and resource limitations) and to estimate the utility of plans that meet these requirements. The information provided by the temporal database and the heuristic evaluator is combined using a decision procedure that determines how best to refine the current partial plan. Neither the temporal database nor the heuristic evaluator is complete and, without reasonably accurate information concerning the possible resource requirements of the tasks in a partial plan, there is a significant risk of missing solutions. A specification language that serves to encode expectations concerning the duration and resource requirements of tasks greatly reduces this risk, enabling useful evaluations of partial plans. Details of the specification language and examples illustrating how such expectations are exploited in decision making are provided.     

并行查询下查询执行计划的选择

查询是数据库系统的主要负载,其效率决定了数据库性能的好坏。一个查询存在多种执行计划,当前,查询优化器只能按照数据库系统的配置参数,静态地为查询选择一个较优的执行计划。并行查询间存在复杂多变的资源争用,很难通过配置参数准确反映,而且同一执行计划在不同情景下的效率并不一致。并行查询下执行计划的选择需考虑查询间的相互影响——查询交互。基于此,提出了一种在并行查询下度量查询受查询交互影响大小的标准QIs。针对并行查询下查询执行计划的选择,还提出了一种动态地为查询选择执行计划的方法TRating,该方法通过比较查询组合中按不同执行计划执行的查询受查询交互影响的大小,选择受查询交互影响较小的执行计划作为该查询的较优执行计划。实验结果表明,TRating方法为查询选择较优执行计划的准确率达61%,相比查询优化器提高了25%;而且在为查询选择次优执行计划时,其准确率也高达69%。     

Acceptance sampling design by computer — Optimality concerns

There is a great deal of literature dealing with the use of the computer in designing acceptance sampling plans. The general approach is to use some approximation technique to generate minimum sample size plans whose OC curves will approximate the desired Producer's Risk and Consumer's Risk levels. Since only rarely will a single such approximation satisfy both (1-) and β requirements some means, either averaging or selection, is used to select a plan. Plans so determined are acceptable but often not optimal, and planes with significantly smaller sample size may exist which are very close to optimal.

This paper reports the development and use of a computer program which may be used to design single sampling plans using either the binomial or Poisson distribution. The program also finds alternate plans with smaller sample size, and gives a measure of the proximity of such alternate plan to optimality. Some rudimentary artificial intelligence techniques are employed in the search and selection of optimal plans and the near-optimal alternative plans.

An extended version of the program also supports experimentation with a variety of criteria of optimality for the selection of candidate plans from those generated.

The main program is written for use under MS/PC-DOS in both Turbo Pascal and Turbo C. The extended version uses only Pascal.     

An Introduction to Interactive Discourse Processing from the Perspective of Plan Recognition and Text Planning

People engage in task-oriented dialogues to carry out or plan a task. Each participant in such an interaction must be capable of processing plans in two ways. First, each participant must be capable of understanding the plans that the other participant is using. Researchers have developed theories and models about how computational systems should go about recognizing the plans and goals of another participant, both at the subject-matter level and at the level of the communication. This area of research is called plan recognition. Secondly, each participant must be able to make their owns plans to communicate. This area of natural language research is called text planning.Interactive systems -- systems that understand natural language and that can produce natural language to engage in a task-related interaction -- must address the issue of how understanding plans (the process of plan recognition) relates to making plans for the interaction (the process of text planning). We provide an introduction to these two research areas in natural language processing. Those who need to be familiar with both areas -- to conduct research at their intersection -- will find this introduction useful for building systems that both understand what people are trying to do when they speak and that can actively participate in the interaction.     

Development of validation rules to support digital lodgement of 3D cadastral plans

Validation is a familiar topic in computing, generally as a mechanism to protect a database from the effects of inappropriate data with the side effect of detecting some errors. As such, the validation rules are determined from the database schema using well understood methodologies. This paper takes a different view by examining digital validation as one of a set of processes that are designed to ensure that the incoming data (in this case, a plan of cadastral survey) is unambiguous and contains sufficient detail to define the legal spatial extents of a property. This is a complex question, especially since the rules and the decisions based on these processes must be defensible (therefore cannot contain arbitrary requirements imposed by a specific database model). Using the jurisdiction of Queensland, Australia, as a case study, this paper discusses the manual submission and lodgement of cadastral survey plans and the current 2D digital process as precursors to the automatic lodgement of all plans of survey. A set of validation rules is proposed for application to single geometric objects, to the relationship of objects on a single survey plan, and to objects that are independently defined on separate plans. It is asserted that, by the nature of the problem, this set is incomplete and will remain so. However, this research has identified a “checklist” of issues to be addressed by jurisdictions hoping to implement digital cadastral survey plan lodgement. The implications of this work in the context of the broader challenges in land administration and within the topic of 3D cadastral data are discussed.