Developing a knowledge-based perspective on coordination: The case of global software projects

We have attempted to bring together two areas which are challenging for both IS research and practice: forms of coordination and management of knowledge in the context of global, virtual software development projects. We developed a more comprehensive, knowledge-based model of how coordination can be achieved, and\illustrated the heuristic and explanatory power of the model when applied to global software projects experiencing different degrees of success. We first reviewed the literature on coordination and determined what is known about coordination of knowledge in global software projects. From this we developed a new, distinctive knowledge-based model of coordination, which was then employed to analyze two case studies of global software projects, at SAP and Baan, to illustrate the utility of the model.     

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.     

Imputation techniques for multivariate missingness in software measurement data

The problem of missing values in software measurement data used in empirical analysis has led to the proposal of numerous potential solutions. Imputation procedures, for example, have been proposed to ‘fill-in’ the missing values with plausible alternatives. We present a comprehensive study of imputation techniques using real-world software measurement datasets. Two different datasets with dramatically different properties were utilized in this study, with the injection of missing values according to three different missingness mechanisms (MCAR, MAR, and NI). We consider the occurrence of missing values in multiple attributes, and compare three procedures, Bayesian multiple imputation, k Nearest Neighbor imputation, and Mean imputation. We also examine the relationship between noise in the dataset and the performance of the imputation techniques, which has not been addressed previously. Our comprehensive experiments demonstrate conclusively that Bayesian multiple imputation is an extremely effective imputation technique.

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.

测试用例的设计和复用技术

软件测试是企业保证软件产品质量的一个重要手段,其中测试用例的设计是软件测试的关键,它一般包括功能测试用例的设计,结构测试用例设计以及系统方面的测试用例设计等.结合实际经验,系统地阐述了如何有效地进行测试用例的设计以及复用.并给出两个案例进行分析,探讨测试用例设计中的一些注意事项.     

仿真软件测试研究

对于大型复杂仿真系统,它能否正常运行,软件的质量起着决定性的作用.软件测试是软件质量的根本保证.首先回顾了仿真软件测试的发展过程;其次,以应用于HLA仿真系统中的RTI软件测试为例,采用黑盒测试方法对国防科技大学仿真实验室开发的KD-RTI、瑞典的pRTI和DMSO的RTI1.3NG-V6进行功能和性能方面的测试,测试结果表明三个RTI软件都能满足要求;最后提出仿真软件测试的发展趋势.     

基于软件配置模型的构件化领域框架研究

以软件复用研究为背景,对面向软件定制的构件化领域框架进行了研究,提出了一种基于软件配置模型的构件化领域框架,并着重分析了利用框架进行软件定制的配置机制以及框架运行原理,最后以灾害快速反应系统为例,对模型和框架进行了实现.     

实例化过程模型的时间自动机描述方法研究

语法结构正确的过程模型并不能保证过程运作的实际执行,因为没有考虑实例化阶段的时间资源安排.传统的过程自动机描述法不足以分析实例化过程模型.针对这种情况,提出用时间自动机描述过程模型语义的方法,设计了生成时间自动机的算法,分析了这种描述方法在模型检验中的应用.