软件体系结构分析与评价方法研究

软件体系结构分析与评价的目的是为了识别体系结构设计中的潜在风险,验证系统的质量需求在设计中是否得到了体现,预测系统的质量并帮助开发人员进行设计决策。从软件体系结构的概念出发,介绍并讨论了国内外有代表性的分析评价方法,探讨了软件体系结构分析与评价方法研究中存在的问题和未来的发展方向。     

DRAMA: A framework for domain requirements analysis and modeling architectures in software product lines

One of the benefits of software product line approach is to improve time-to-market. The changes in market needs cause software requirements to be flexible in product lines. Whenever software requirements are changed, software architecture should be evolved to correspond with them. Therefore, domain architecture should be designed based on domain requirements. It is essential that there is traceability between requirements and architecture, and that the structure of architecture is derived from quality requirements. The purpose of this paper is to provide a framework for modeling domain architecture based on domain requirements within product lines. In particular, we focus on the traceable relationship between requirements and architectural structures. Our framework consists of processes, methods, and a supporting tool. It uses four basic concepts, namely, goal based domain requirements analysis, Analytical Hierarchy Process, Matrix technique, and architecture styles. Our approach is illustrated using HIS (Home Integration System) product line. Finally, industrial examples are used to validate DRAMA.     

根据系统需求决策软件产品线体系结构

软件生产线是实现软件复用的有效手段.由于需求的复杂性和软件体系结构风格的多样性以及其他因素的影响,如何由现实的系统需求得到一个合理的软件生产线体系结构已经成为一个亟待解决的问题.提出基于需求建立系统体系结构的框架-FM(Fuzzy method)过程,包括基于目标和场景模型的逻辑组件的识别,应用Fuzzy比较方法计算逻辑组件的重要度,定量的系统特性分析和建立体系结构模型四个主要的步骤.以综合考务系统项目为例说明了这种方法的有效性和实际的可操作性.     

Enhancing mirror adaptive random testing through dynamic partitioning

ContextAdaptive random testing (ART), originally proposed as an enhancement of random testing, is often criticized for the high computation overhead of many ART algorithms. Mirror ART (MART) is a novel approach that can be generally applied to improve the efficiency of various ART algorithms based on the combination of “divide-and-conquer” and “heuristic” strategies.ObjectiveThe computation overhead of the existing MART methods is actually on the same order of magnitude as that of the original ART algorithms. In this paper, we aim to further decrease the order of computation overhead for MART.MethodWe conjecture that the mirroring scheme in MART should be dynamic instead of static to deliver a higher efficiency. We thus propose a new approach, namely dynamic mirror ART (DMART), which incrementally partitions the input domain and adopts new mirror functions.ResultsOur simulations demonstrate that the new DMART approach delivers comparable failure-detection effectiveness as the original MART and ART algorithms while having much lower computation overhead. The experimental studies further show that the new approach also delivers a better and more reliable performance on programs with failure-unrelated parameters.ConclusionIn general, DMART is much more cost-effective than MART. Since its mirroring scheme is independent of concrete ART algorithms, DMART can be generally applied to improve the cost-effectiveness of various ART algorithms.     

An architecture for adaptive fuzzy control in industrial environments

The paper presents an architecture for adaptive fuzzy control of industrial systems. Both conventional and adaptive fuzzy control can be designed. The control methodology can integrate a priori knowledge about the control and/or about the plant, with on-line control adaptation mechanisms to cope with time-varying and/or uncertain plant parameters. The paper presents the fuzzy control software architecture that can be integrated in industrial processing and communication structures. It includes four distinct modules: a mathematical fuzzy library, a graphical user interface (GUI), fuzzy controller, and industrial communication. Three types of adaptive fuzzy control methods have been studied, and compared: (1) direct adaptive, (2) indirect adaptive, and (3) combined direct/indirect adaptive. An experimental benchmark composed of two mechanically coupled electrical DC motors has been employed to study the performance of the presented control architectures. The first motor acts as an actuator, while the second motor is used to generate nonlinearities and/or time-varying load. Results indicate that all tested controllers have good performance in overcoming changes of DC motor load.     

A Quality 4.0 Model for architecting industry 4.0 systems

The increasing importance of automation and smart capabilities for factories and other industrial systems has led to the concept of Industry 4.0 (I4.0). This concept aims at creating systems that improve the vertical and horizontal integration of production through (i) comprehensive and intelligent automation of industrial processes, (ii) informed and decentralized real-time decision making, and (iii) stringent quality requirements that can be monitored at any time. The I4.0 infrastructure, supported in many cases by robots, sensors, and algorithms, demands highly skilled workers able to continuously monitor the quality of both the items to be produced and the underlying production processes.While the first attempts to develop smart factories and enhance the digital transformation of companies are under way, we need adequate methods to support the identification and specification of quality attributes that are relevant to I4.0 systems. Our main contribution is to provide a refined version of the ISO 25010 quality model specifically tailored to those qualities demanded by I4.0 needs. This model aims to provide actionable support for I4.0 software engineers that are concerned with quality issues. We developed our model based on an exhaustive analysis of similar proposals using the design science method as well as expertise from seasoned engineers in the domain. We further evaluate our model by applying it to two important I4.0 reference architectures further clarifying its application.