Investigating dependencies in software requirements for change propagation analysis

ContextThe dependencies between individual requirements have an important influence on software engineering activities e.g., project planning, architecture design, and change impact analysis. Although dozens of requirement dependency types were suggested in the literature from different points of interest, there still lacks an evaluation of the applicability of these dependency types in requirements engineering.ObjectiveUnderstanding the effect of these requirement dependencies to software engineering activities is useful but not trivial. In this study, we aimed to first investigate whether the existing dependency types are useful in practise, in particular for change propagation analysis, and then suggest improvements for dependency classification and definition.MethodWe conducted a case study that evaluated the usefulness and applicability of two well-known generic dependency models covering 25 dependency types. The case study was conducted in a real-world industry project with three participants who offered different perspectives.ResultsOur initial evaluation found that there exist a number of overlapping and/or ambiguous dependency types among the current models; five dependency types are particularly useful in change propagation analysis; and practitioners with different backgrounds possess various viewpoints on change propagation. To improve the state-of-the-art, a new dependency model is proposed to tackle the problems identified from the case study and the related literature. The new model classifies dependencies into intrinsic and additional dependencies on the top level, and suggests nine dependency types with precise definitions as its initial set.ConclusionsOur case study provides insights into requirement dependencies and their effects on change propagation analysis for both research and practise. The resulting new dependency model needs further evaluation and improvement.     

Paving the way for CRM success: The mediating role of knowledge management and organizational commitment

Customer relationship management (CRM) has become one of the most influential technologies in the world, and companies are increasingly implementing it to create value. However, despite significant investment in CRM technology infrastructure, empirical research offers inconsistent support for its positive impact on performance. This study develops and tests a research model analyzing the process through which CRM technology infrastructure translates into organizational performance, drawing on the resource-based view (RBV) and the knowledge-based view (KBV) of the firm. Based on an international sample of 125 hotels, the results suggest that organizational commitment and knowledge management fully mediate this process.     

Effect of introduction of structural defects on protective ability of polyesters

Permeability of a polymer plays an important role in conferring the protective ability of organic coating to the steel surface against atmospheric corrosion. Although the relationship between structure of polymers and their permeability has been extensively studied in various applications like membranes, packaging, etc., such detailed study is lacking in the area of coatings. The systematic study of structure–permeability relationship of polymers in clear coatings can give guidelines in selecting the binder for the required application. This article deals with the effect of introduction of structural defects into a straight chain aliphatic polyesters on the protective ability of their clear coatings against corrosion. The mild steel panels coated with clear coatings based on the polyesters were exposed to humidity in humidity chamber. A novel technique of detecting the onset of corrosion was used instead of conventional methods that detect the failure of the coating due to corrosion. It was observed that even at 1–10% mole defect introduced by replacement of straight chain diols with branched diols, the protective ability of clear coatings was affected drastically.     

一种应用于人脸识别的超分辨率方法

为提高局部保持投影(LPP)在人脸图像超分辨率中的适用性,在LPP中引入典型相关分析(CCA),提出一种相关性增强的局部保持投影方法(CELPP)。CELPP用于提取高分辨率图像与低分辨率图像特征,根据关系学习建立低分辨率图像特征与高分辨率图像特征之间的映射变换,输入低分辨率图像,通过CELPP特征提取和关系映射,得到高分辨率图像,并将其用于人脸识别。对人脸库ORL和Yale进行的实验结果表明,该方法同时考虑了高分辨率图像与低分辨率图像的相似性及同类图像的局部结构性,在基于人脸识别的超分辨率应用中优于LPP和CCA。     

基于NoSQL数据库的大数据存储技术的研究与应用

实际工程中采集和处理的数据量特别大,这对传统数据库技术提出巨大挑战。针对传统关系型数据库存储速度慢、对硬件要求高的缺点,提出一种以NoSQL数据库为基础的大数据处理方法,打破了传统数据库的关系模型,数据以一种自由的方式存储,而不依赖固定的表结构。该方法主要是将经验模态分解并与NoSQL数据库技术相结合,应用于大型结构件的变形监测中,构建出一个基于NoSQL数据库系统的大型结构件变形监测系统。仿真结果表明,该方法可以实现大型结构件变形监测数据的实时处理,在计算收敛性、算法稳定性和处理速度上都优于传统数据库技术。     

一种基于移动用户位置的网络服务推荐方法

伴随着无线通信技术和智能移动终端的快速发展,基于位置的服务(location-based services,简称LBS)以其移动性、实用性、随时性和个性化的特点,在军事、交通、物流等诸多领域得到了广泛的应用,成为最具发展潜力的移动增值业务之一。在一个基于位置的网络服务推荐框架的基础上,给出了一种基于位置的移动用户偏好相似度计算方法,同时证明了其满足近邻相似测度的一般性质;然后,提出一种符合社会学概念的信任值计算方法。把它们应用于基于移动用户位置的网络服务推荐过程中,从而形成了一种基于移动用户位置的网络服务推荐方法。该方法有效地提高了网络服务推荐的准确性和可靠性,同时缓解了推荐过程中可能存在的数据稀疏性以及冷启动问题。最后,通过公开的MIT数据集验证了该推荐方法的准确度和可行性。     

工作流系统性能分析与优化方案

随着企业业务流程信息化建设的推进,对核心业务领域的流程化管理已成为实现信息化水平进一步提升的重要基础,工作流系统作为基础设施,其性能在一定程度上决定了业务流程流转的效率.本文通过对工作流系统性能的量化分析,得出其性能指标与数据库规模的量化关系,从而为性能优化工作提出关键因素和技术切入点,在此基础上,本文结合数据库机制对工作流性能优化方案进行了研究和实现,提出了一种有效的算法,实现了归档机制,从而达到提升工作流系统性能优化的最终目的.     

基于开发者协作关系和信息检索的需求跟踪系统

目前自动化需求跟踪的研究广泛使用文本信息检索技术。然而信息检索会遗漏一些文本不相似但是实际相关的软件制品,导致自动化跟踪的精度不高。针对上述问题,提出利用开发者协作关系来进行优化,研发了基于开发者协作关系和信息检索的需求跟踪系统。该系统在进行需求跟踪时,首先用信息检索推荐与需求文本上相似的代码,然后从代码提交日志中挖掘开发者协作关系,根据开发者协作关系再推荐相关代码,用户根据两次推荐的结果确定正确的需求代码跟踪关系。试验结果表明该系统能够找到信息检索遗漏的需求跟踪关系,能够提高自动化跟踪的准确性,节省跟踪时间。     

多特征文本蕴涵识别研究

文本蕴涵识别是解决自然语言中存在的同义异形问题的有效途径。虽然国内外学者已经提出了很多文本蕴涵识别模型,但影响文本蕴涵识别的因素错综复杂,识别准确率普遍不高。该文把文本蕴涵识别看作二元分类问题,抽取词汇特征、句法依存关系特征及FrameNet语义知识库特征的多种特征构造特征矩阵,训练SVM分类器,实现文本蕴涵识别。该方法在国际文本蕴涵识别技术评测RTE3的测试集上进行测试,蕴涵正例识别准确率达到了78.1%,高于RTE3评测2-ways的最高结果。