菜单自动生成工具MTOOL

本文较详细地介绍了应用软件中菜单系统的自动生成 工具ＭＴＯＯＬ。该工具将一定语法规则编制成的菜单描述文件转换成标准的菜单方式驱动的程序，提高了引用软件的编程效率。     

基于知识的应用软件生成系统KBSG

1.前言KBSG是我们在微机上开发的一个面向工程应用领域的基于知识的应用软件生成系 统原型,该系统吸收并运用了软件工程 与人工智能的最新成果,采用知识库、软 件库、设计库以及用户数据库的四库思 想,来对工程软件的设计、开发、调试、运 行及其管理进行统一的处理,基本上实 现工程应用软件设计开发的工程化与自 动化。     

一个交互式框图生成工具

目前在国内没有出售工作站级的,用来作框图、流程图目的的软件。基于此目的,本人在Openlook环境下,用SunView的图形软件包,通过自己设计窗口界面,实现了交互式图形编辑的目的。可广泛地用     

现代应用软件的测试策略与工具

现代应用软件有许多新的特性，这样注对软件测试提出了新的要求，如要求测试工作更有效、进行面向用户的测试等，这些要求是传统的测试策略所不能解决的，本文提出了一种基于应用操作覆盖的测试方法来解决这些问题，这种方法的基本分析工具是导航图和事件记录序列，本文最后还给出了相应的自动测试工具。     

4“阶与5”阶强魔性幻方自动生成的程序

４”阶与５”阶强魔性幻方自动生成的程序杭州大学冯恭己浙江省软件中心辛柱鼎，童子容美国加州大学ＨｎｇｏＨｓｕｎ博士等于１９８９年在四川大学学报上刊登了一篇论文：幻群ＭＧ和它在４阶幻方上的作用［４］．文中第一次对“强魔性”概念作了定义，但由于此类幻方内部...     

一种基于Velocity的代码自动生成技术研究

通过代码自动、快速地生成应用系统是软件开发的捷径。基于Velocity的代码生成技术是目前常用的方法。通过分析已有代码自动生成技术解决方案存在的问题,结合快速生成信息管理系统的业务需求,提出并实现了一个基于DOM4J解析框架以及Velocity模板技术的代码自动生成的平台框架。通过一个实例,给出该平台的实现过程。目前该自动生成技术已应用于实际软件开发中,初步达到了快速生成代码的研究目标。     

基于UML的软件测试用例自动生成技术研究

测试用例自动生成是软件自动化测试的基础与关键。随着UML的广泛应用,基于UML模型的测试用例自动生成技术日益受到关注。本文提出了通过对UML Sequence Diagram进行形式化分析产生测试场景的技术,定义了相应的测试覆盖准则,分析了测试数据的生成。并探讨了将测试工具和建模工具相结合的具体实现方法。     

功能规约自动生成

ＮＤＲＡＳＳ系统是南京大学计算机软件研究所新近研制成的一个由软件需求定义到软件功能规约的转换系统。功能规约自动生成是该系统的主体部分。它涉及状态空间的生成，操作定义的生成和系统总控流程的生成等。本文简要阐述了这些问题，特别讨论了ＮＤＲＡＳＳ系统中控制流图的规范化与结构化分解，全文包括研究动因、ＮＤＲＡＳＳ系统、功能规约自动生成架构、控制流图的规范化和结构化、代码生成、示例以及结语七个部分。     

An object-oriented approach to application generation

The TUBA system consists of a set of integrated tools for the generation of business-oriented applications. Tools and applications have a modular structure, represented by class objects. The article describes the architecture of the environments for file processing, screen handling and report writing.     

N因素S水平的配对测试集生成算法研究

在分析配对测试及其有效性的基础上,给出了一种新的关于n因素s(s≥2)水平的配对测试集生成算法。实验表明该算法与以往一些算法相比具有一定的优越性,最后将该算法运用于一个具体实例,并较详细地介绍了该实例的测试集生成过程。     

物资采购计划自动生成系统

本文论述物资采购计划自动生成的系统结构，以及在ＰＣ机上用ＦＯＸＢＡＳＥ开发工具编程实现原理与算法。系统实现了数据维护、物资采购计划生成及报表输出功能，为实现物资采购的现代化科学管理提供了一些参考。     

On the possibilities of (pseudo-) software cloning from external interactions

This paper discusses some initial investigations into the application of genetic programming technology as a vehicle for re-examining some existing approaches within the software life-cycle. Specifically, it outlines a new direction in production techniques—software cloning from executable specifications or source code. It explores the possibility and advantages of producing a system from its external interactions. To allow this production to be automatic, the system assumes that it can view (and potentially manipulate) these external interactions of the original system; and hence it assumes the existence of either an executable specification or the source code—an object to assist in the generation of the external interactions; i.e. the system is treated as a black-box. Although the generation and application of software clones is relatively unexplored, it is believed that this is a fundamental technology that can have many different applications within a software engineering environment. For example, software clones could be used in: complexity measurement, software testing and software fault tolerance. Clearly, for these clones to be usable, their production needs to be automated. An interesting approach to this automatic production or generation problem is the application of evolutionary-based Genetic Programming (GP). Using the paradigms of best fit, selection, crossover and mutation, a number of clones, satisfying specific requirements, can be automatically generated. In general, GP is a flexible and powerful algorithm suitable for solving a variety of different problems. This paper presents the results of studies that have been conducted in order to answer questions related to feasibility of using GP for clone generation: what features of GP are important? What works and what does not? How can the GP be “tuned” for the problem? The results have been used to draw a set of suggestions and conclusions that indicate possible usability of GP-based approach to automatic generation of clones.     

Automatic, evolutionary test data generation for dynamic software testing

This paper proposes a dynamic test data generation framework based on genetic algorithms. The framework houses a Program Analyser and a Test Case Generator, which intercommunicate to automatically generate test cases. The Program Analyser extracts statements and variables, isolates code paths and creates control flow graphs. The Test Case Generator utilises two optimisation algorithms, the Batch-Optimistic (BO) and the Close-Up (CU), and produces a near to optimum set of test cases with respect to the edge/condition coverage criterion. The efficacy of the proposed approach is assessed on a number of programs and the empirical results indicate that its performance is significantly better compared to existing dynamic test data generation methods.     

二维模块生成器中的布局算法研究及实现

本文讨论了ＣＭＯＳ集成电路模块生成器中的布局算法，尤其是在门阵列（门海）布图模式下的各种布局算法及其对布图结果的影响，并对已实现的三种布局算法给出了实例测试结果。     

A tabu search algorithm for structural software testing

This paper presents a tabu search metaheuristic algorithm for the automatic generation of structural software tests. It is a novel work since tabu search is applied to the automation of the test generation task, whereas previous works have used other techniques such as genetic algorithms. The developed test generator has a cost function for intensifying the search and another for diversifying the search that is used when the intensification is not successful. It also combines the use of memory with a backtracking process to avoid getting stuck in local minima. Evaluation of the generator was performed using complex programs under test and large ranges for input variables. Results show that the developed generator is both effective and efficient.