An adaptive and trustworthy software testing framework on the grid

Grid computing, which is characterized by large-scale sharing and collaboration of dynamic distributed resources has quickly become a mainstream technology in distributed computing and is changing the traditional way of software development. In this article, we present a grid-based software testing framework for unit and integration test, which takes advantage of the large-scale and cost-efficient computational grid resources to establish a testbed for supporting automated software test in complex software applications. Within this software testing framework, a dynamic bag-of-tasks model using swarm intelligence is developed to adaptively schedule unit test cases. Various high-confidence computing mechanisms, such as redundancy, intermediate value checks, verification code injection, and consistency checks are employed to verify the correctness of each test case execution on the grid. Grid workflow is used to coordinate various test units for integration test. Overall, we expect that the grid-based software testing framework can provide efficient and trustworthy services to significantly accelerate the testing process with large-scale software testing.

Verification of evolving software via component substitutability analysis

This paper presents an automated and compositional procedure to solve the substitutability problem in the context of evolving software systems. Our solution contributes two techniques for checking correctness of software upgrades: (1) a technique based on simultaneous use of over-and under-approximations obtained via existential and universal abstractions; (2) a dynamic assume-guarantee reasoning algorithm—previously generated component assumptions are reused and altered on-the-fly to prove or disprove the global safety properties on the updated system. When upgrades are found to be non-substitutable, our solution generates constructive feedback to developers showing how to improve the components. The substitutability approach has been implemented and validated in the ComFoRT reasoning framework, and we report encouraging results on an industrial benchmark. This is an extended version of a paper, Dynamic Component Substitutability Analysis, published in the Proceedings of the Formal Methods 2005 Conference, Lecture Notes in Computer Science, vol. 3582, by the same authors. This research was sponsored by the National Science Foundation under grant nos. CNS-0411152, CCF-0429120, CCR-0121547, and CCR-0098072, the Semiconductor Research Corporation under grant no. TJ-1366, the US Army Research Office under grant no. DAAD19-01-1-0485, the Office of Naval Research under grant no. N00014-01-1-0796, the ICAST project and the Predictable Assembly from Certifiable Components (PACC) initiative at the Software Engineering Institute, Carnegie Mellon University. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of any sponsoring institution, the US government or any other entity.     

Predicting weekly defect inflow in large software projects based on project planning and test status

Defects discovered during the testing phase in software projects need to be removed before the software is shipped to the customers. The removal of defects can constitute a significant amount of effort in a project and project managers are faced with a decision whether to continue development or shift some resources to cope with defect removal. The goal of this research is to improve the practice of project management by providing a method for predicting the number of defects reported into the defect database in the project. In this paper we present a method for predicting the number of defects reported into the defect database in a large software project on a weekly basis. The method is based on using project progress data, in particular the information about the test progress, to predict defect inflow in the next three coming weeks. The results show that the prediction accuracy of our models is up to 72% (mean magnitude of relative error for predictions of 1 week in advance is 28%) when used in ongoing large software projects. The method is intended to support project managers in more accurate adjusting resources in the project, since they are notified in advance about the potentially large effort needed to correct defects.     

Improvement of causal analysis using multivariate statistical process control

Statistical process control (SPC) is a conventional means of monitoring software processes and detecting related problems, where the causes of detected problems can be identified using causal analysis. Determining the actual causes of reported problems requires significant effort due to the large number of possible causes. This study presents an approach to detect problems and identify the causes of problems using multivariate SPC. This proposed method can be applied to monitor multiple measures of software process simultaneously. The measures which are detected as the major impacts to the out-of-control signals can be used to identify the causes where the partial least squares (PLS) and statistical hypothesis testing are utilized to validate the identified causes of problems in this study. The main advantage of the proposed approach is that the correlated indices can be monitored simultaneously to facilitate the causal analysis of a software process.

一种基于C#的通用软件安装程序的架构设计与实现

可以说每个商业化软件都必须具备安装工具,使用系统软件自带的打包程序有时很难满足实际需求,为此提出了一种基于C#的通用软件安装程序的架构,给出了实现这一架构的设计方法和关键代码.通过该架构,可以非常容易地实现安装程序的功能扩展和代码维护.     

家纺产品分销管理系统的设计与实现

根据家纺产品分销的业务范围和操作流程,结合基于组件的多层应用开发技术,提出了适合家纺产品分销管理的系统解决方案,较好地实现了家纺产品分销中的一些业务流程。该文详细阐述了家纺分销管理系统的设计与实现。     

城市轨道交通电力监控系统测试的研究及应用

针对电力监控系统具有实时性、可靠性、硬件依赖等特点,为了保证电力监控系统的可靠、安全和稳定性。提出了适用于该系统的测试方法。根据系统的特点制定了相应的测试策略,并进行了测试的总体设计和测试用例的设计。最后通过对测试环境的分析,开发了相应的模拟器。通过模拟器和测试用例实现了测试的自动化。根据测试的过程和结果表明,采用正确的测试设计方法能够有效的发现系统中存在的问题,保证系统的质量。     

基于Petri网的软件演化过程

随着遗产软件系统的老化,软件演化已成为软件工程的一个新兴领域.对软件演化及过程的特征进行了描述,提出基于Petri网的软件演化过程;最后给出了软件演化过程的活性判断及优化算法.     

二次拟合：一种提高软件可靠性模型精度的新方法

针对软件可靠性模型精度不高的问题,提出了"一次建模 + 二次拟合"的方法,通过误差补偿机制来提高模型精度,并将该方法应用于航天软件失效数据集.实践结果表明,提出的方法对于提高软件可靠性模型精度是有效的.     

基于状态空间的机械臂轨迹规划

提出一种基于状态空间的机械臂轨迹规划方法,定义并构造了机械臂系统的状态空间,根据内在机构约束与外部环境约束描述出系统状态的可达范围,并给出了任务的可实现条件.对于可实现任务,在状态空间能搜索到任务完成的最优解.如果任务无法完成,则修改系统配置或约束,在新的状态空间确定任务实现的转化条件,并对任务的设计与规划给予指导.研究了障碍约束下两连杆机械臂的点到点任务,实验结果验证了该方法的有效性.