基于复杂网络的软件结构复杂性分析与建模
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摘要
随着软件系统的规模和复杂度的不断增长,如何认识、管理、控制和降低软件系统的复杂性就成为软件工程面临的巨大挑战。经过长期的工程实践,软件开发者认识到大规模的复杂软件系统的结构与其功能、质量之间的关系十分密切。如何构建软件良好的结构、系统维护时如何对软件的结构进行优化,一直都是软件工程领域研究的重要问题。
传统的软件工程方法通常关注于软件的局部或者微观层面结构特征,忽略了一些重要的反映全局结构的整体特性。这使得研究人员难以习惯从整体和全局的角度来研究大规模的软件系统,导致长期以来对软件的本质缺乏清晰的认识,也不能了解的软件整体结构的复杂性的演化规律。最近几年,许多研究人员发现抽象为网络模型的软件系统的结构展现出小世界和无标度的复杂网络特性,认为软件系统是一种人工复杂网络,突破了软件的传统思维方式。通过软件工程与复杂系统的学科交叉研究,用网络的观点来重新审视软件,形成软件的网络观,从整体和全局的角度来探索和发现复杂软件系统的结构特性、演化规律和由此产生的行为特征,将有助于正确、全面地认识和理解软件的本质特征,为解决软件的复杂性问题奠定基础。虽然近年来复杂网络与软件工程的交叉研究取得了一些成果,但是由于关于软件结构的研究刚刚起步,也存在下面的一些问题：缺乏针对包括系统演化和实时运行两个动态过程的软件结构动态行为的研究；目前研究人员还普遍存在着单纯采用点和边形式的图来抽象软件的结构是否会能全面或者充分描绘软件系统的困惑；度量软件部件之间相互作用的复杂性是否准确、合理和全面；缺乏针对软件系统的复杂网络模型；如何才能真正建立软件整体结构特性与软件质量之间关系?
针对上述问题,本文以学科交叉融合为背景、以探索软件结构的复杂性为目标,分析其结构的复杂性的演化规律和其动态活动的动力学行为,建立结构复杂性的演化模型,度量软件部件之间相互作用的复杂性,为量化软件的复杂性提供基础,也为提高软件系统的质量提供一种思路与方法。围绕上述研究目标和内容,本文所做工作的主要工作归纳如下：
(1)综合采用复杂网络的理论与方法和软件工程的度量指标从系统的层次上详细分析和研究了软件系统在系统演化和版本升级过程中所表现出来的系统特性和系统结构的变化规律,从系统层次上详细分析了他们源代码的演化过程,从理论上深刻揭示了一类面向对象软件系统的演化动力学特性和规律。这些规律的发现对于从宏观的角度去深刻认识、理解、控制面向对象软件系统的结构和演化特性提供了的理论基础。
(2)根据软件演化的动力学分析所得到的结论,采用复杂网络的相关理论进行了解释,提出了面向对象软件系统的无标度(无向的和有向的)演化模型,深刻解释了作为软件复杂性之一的无标度特性的演化机理。
(3)探索和设计了面向对象软件的动态网络的分析方法,通过实例发现了面向对象的软件系统在实时运行过程中生成的动态网络具有复杂网络所特有的小世界特性和无标度特性。这些特性的发现可以用在系统测试、软件质量的评价、系统资源的回收利用等方面,对于丰富面向对象的程序设计具有重要的意义。
(4)为了能够更加全面的度量软件系统部件间的复杂关系,首先采用复杂网络的方法对软件系统进行了抽象,本文提出了一对能够反映软件质量的耦合因子——影响耦合因子和错误影响耦合因子。
目前,软件工程与复杂系统的学科交叉研究才刚刚起步。用复杂网络的方法来研究和认识软件,形成软件网络观,有助于我们深刻认识软件的本质行为和特征,从而开辟一条软件工程学研究的新途径,为推动软件工程彻底解决软件复杂性问题做出应有的贡献。
As scale and complexity of software increase rapidly, how to understand, mea-sure, manage and control software complexity is a great challenge for software engineering. After many years of software engineering practice, software designers have acknowledged that software structure is closely related to software quality. Good structure is the key to the success of software design. Therefore, how to project well structured software is one of the most researched problems in software engineering.
The traditional research on software structure pay much attention on rather small granularity and the local structural characteristics, while on larger scales average approach is not usually considered. As a result, much information is lost. In the long run, this situation obstructs us from understanding and explaining the evolution of software structure and reusing successful development experiences on the system level.
Recent research achievements in complex networks introduce new mathemat-ical foundations and software engineering methods for software complex systems and find that the structures of these systems share small world and scale free prop-erties of complex networks. These achievements emphasize understanding system as a whole instead of focusing on local structure and behaviors. This new approach helps us to see software system from a different angle. Although the researches on complex network mainly aim at exploring the common characteristics in various complex networks and their formation rules, some problem exist. For example, there is a, lack of analysis of evolution processes from system level; there is a lack of complex software network model for evolution; there is a kind of puzzle whether the approach that is used to abstract software network is reasonable, etc.
To address the above mentioned problems, the objective of this paper is to explore the complex of software structural, to analyze the dynamical evolution processes of software system from system level, to construct models that can pre-dict the emergence of scale-free state of software network, and to measure coupling interactions of software components that induce complexity. In the follows, the primary contributions of this paper will be summarized.
(1) software evolution plays a vital role in software engineering. On the one hand, the continuous evolution and development of software may improve the effi-ciency of development project. On the other hand, software evolution can decrease the system maintenance costs and also enhance the normal development of soft-ware systems. Based on the theories and methods of complex networks, we select three sets of representative object-oriented software complex systems and then fur-ther analyze the dynamical evolution processes of their source codes from system level. It is the first time in literature to report the discovery of the underlying evolution dynamics and rules of a class of object-oriented software systems from theory. All these rules provide a theoretical basis for the recognizing, understand-ing, and control of system structure and evolving characteristic of object-oriented software systems from macroscopic view.
(2) Basing on analyzing evaluative structure of the software networks we con-sider accelerating growth of network as power-law growth, which can be easily generalized to real systems as better than linear growth. For accelerating growth via a power law and scale-free state with preferential linking, we focus on exploring the generic property of complex networks. Generally, two scenarios are possible. In one of them, the links are undirected. In the other scenario, the links are directed. We propose two models that can predict the emergence of power-law growth and scale-free state in good agreement with these two scenarios and can simulate much more real systems than existing scale- free network models. Moreover, we use the obtained predictions to fit accelerating growth and the connectivity distribution of software networks describing scale- free structure. The combined analytical and numerical results indicate the emergence of a novel set of models that consider-ably enhance our ability to understand and characterize complex networks, whose applicability reaches far beyond the quoted examples.
(3) We explore the approach and tool to analyze dynamic software network. By analytical experiment, we conclude that the world of real time software net-works is indeed small world and scale free, just like the Web, the Internet, and many other networks we routinely use in our everyday lives. The unexpected dis-covery bring important meanings for OO program design, debugging costs, and garbage collection, etc.
(4) How to measure and control coupling interactions of software compo-nents is a largely explored research problem in software network. In terms of graph theory and linear algebra, this paper investigates a pair of coupling metrics to evaluate coupling interactions between the classes of object-oriented systems. These metrics differ from the majority of existing metrics in three aspects:taking into account the strength that one class depends on other ones, reflecting indirect coupling, and distinguishing various coupling interaction. An empirical compar-ison of the novel measures with one of the most widely used coupling metrics is described. Specifically, an experiment about the relationships of this pair metrics is conducted. The result shows that software complexity derived from coupling interaction could not be accurately reflected by one dimension of coupling metric for negative correlation.
This conception will help deepen our understanding of the essential of software complexity. At present the interdisciplinary research between complex networks and software engineering just grow. The approach that adopt complex network will help deepen our understanding of the essential of software complexity and provide a new insight into software engineering and raise the profile for dealing with software crisis.
传统的软件工程方法通常关注于软件的局部或者微观层面结构特征,忽略了一些重要的反映全局结构的整体特性。这使得研究人员难以习惯从整体和全局的角度来研究大规模的软件系统,导致长期以来对软件的本质缺乏清晰的认识,也不能了解的软件整体结构的复杂性的演化规律。最近几年,许多研究人员发现抽象为网络模型的软件系统的结构展现出小世界和无标度的复杂网络特性,认为软件系统是一种人工复杂网络,突破了软件的传统思维方式。通过软件工程与复杂系统的学科交叉研究,用网络的观点来重新审视软件,形成软件的网络观,从整体和全局的角度来探索和发现复杂软件系统的结构特性、演化规律和由此产生的行为特征,将有助于正确、全面地认识和理解软件的本质特征,为解决软件的复杂性问题奠定基础。虽然近年来复杂网络与软件工程的交叉研究取得了一些成果,但是由于关于软件结构的研究刚刚起步,也存在下面的一些问题：缺乏针对包括系统演化和实时运行两个动态过程的软件结构动态行为的研究；目前研究人员还普遍存在着单纯采用点和边形式的图来抽象软件的结构是否会能全面或者充分描绘软件系统的困惑；度量软件部件之间相互作用的复杂性是否准确、合理和全面；缺乏针对软件系统的复杂网络模型；如何才能真正建立软件整体结构特性与软件质量之间关系?
针对上述问题,本文以学科交叉融合为背景、以探索软件结构的复杂性为目标,分析其结构的复杂性的演化规律和其动态活动的动力学行为,建立结构复杂性的演化模型,度量软件部件之间相互作用的复杂性,为量化软件的复杂性提供基础,也为提高软件系统的质量提供一种思路与方法。围绕上述研究目标和内容,本文所做工作的主要工作归纳如下：
(1)综合采用复杂网络的理论与方法和软件工程的度量指标从系统的层次上详细分析和研究了软件系统在系统演化和版本升级过程中所表现出来的系统特性和系统结构的变化规律,从系统层次上详细分析了他们源代码的演化过程,从理论上深刻揭示了一类面向对象软件系统的演化动力学特性和规律。这些规律的发现对于从宏观的角度去深刻认识、理解、控制面向对象软件系统的结构和演化特性提供了的理论基础。
(2)根据软件演化的动力学分析所得到的结论,采用复杂网络的相关理论进行了解释,提出了面向对象软件系统的无标度(无向的和有向的)演化模型,深刻解释了作为软件复杂性之一的无标度特性的演化机理。
(3)探索和设计了面向对象软件的动态网络的分析方法,通过实例发现了面向对象的软件系统在实时运行过程中生成的动态网络具有复杂网络所特有的小世界特性和无标度特性。这些特性的发现可以用在系统测试、软件质量的评价、系统资源的回收利用等方面,对于丰富面向对象的程序设计具有重要的意义。
(4)为了能够更加全面的度量软件系统部件间的复杂关系,首先采用复杂网络的方法对软件系统进行了抽象,本文提出了一对能够反映软件质量的耦合因子——影响耦合因子和错误影响耦合因子。
目前,软件工程与复杂系统的学科交叉研究才刚刚起步。用复杂网络的方法来研究和认识软件,形成软件网络观,有助于我们深刻认识软件的本质行为和特征,从而开辟一条软件工程学研究的新途径,为推动软件工程彻底解决软件复杂性问题做出应有的贡献。
As scale and complexity of software increase rapidly, how to understand, mea-sure, manage and control software complexity is a great challenge for software engineering. After many years of software engineering practice, software designers have acknowledged that software structure is closely related to software quality. Good structure is the key to the success of software design. Therefore, how to project well structured software is one of the most researched problems in software engineering.
The traditional research on software structure pay much attention on rather small granularity and the local structural characteristics, while on larger scales average approach is not usually considered. As a result, much information is lost. In the long run, this situation obstructs us from understanding and explaining the evolution of software structure and reusing successful development experiences on the system level.
Recent research achievements in complex networks introduce new mathemat-ical foundations and software engineering methods for software complex systems and find that the structures of these systems share small world and scale free prop-erties of complex networks. These achievements emphasize understanding system as a whole instead of focusing on local structure and behaviors. This new approach helps us to see software system from a different angle. Although the researches on complex network mainly aim at exploring the common characteristics in various complex networks and their formation rules, some problem exist. For example, there is a, lack of analysis of evolution processes from system level; there is a lack of complex software network model for evolution; there is a kind of puzzle whether the approach that is used to abstract software network is reasonable, etc.
To address the above mentioned problems, the objective of this paper is to explore the complex of software structural, to analyze the dynamical evolution processes of software system from system level, to construct models that can pre-dict the emergence of scale-free state of software network, and to measure coupling interactions of software components that induce complexity. In the follows, the primary contributions of this paper will be summarized.
(1) software evolution plays a vital role in software engineering. On the one hand, the continuous evolution and development of software may improve the effi-ciency of development project. On the other hand, software evolution can decrease the system maintenance costs and also enhance the normal development of soft-ware systems. Based on the theories and methods of complex networks, we select three sets of representative object-oriented software complex systems and then fur-ther analyze the dynamical evolution processes of their source codes from system level. It is the first time in literature to report the discovery of the underlying evolution dynamics and rules of a class of object-oriented software systems from theory. All these rules provide a theoretical basis for the recognizing, understand-ing, and control of system structure and evolving characteristic of object-oriented software systems from macroscopic view.
(2) Basing on analyzing evaluative structure of the software networks we con-sider accelerating growth of network as power-law growth, which can be easily generalized to real systems as better than linear growth. For accelerating growth via a power law and scale-free state with preferential linking, we focus on exploring the generic property of complex networks. Generally, two scenarios are possible. In one of them, the links are undirected. In the other scenario, the links are directed. We propose two models that can predict the emergence of power-law growth and scale-free state in good agreement with these two scenarios and can simulate much more real systems than existing scale- free network models. Moreover, we use the obtained predictions to fit accelerating growth and the connectivity distribution of software networks describing scale- free structure. The combined analytical and numerical results indicate the emergence of a novel set of models that consider-ably enhance our ability to understand and characterize complex networks, whose applicability reaches far beyond the quoted examples.
(3) We explore the approach and tool to analyze dynamic software network. By analytical experiment, we conclude that the world of real time software net-works is indeed small world and scale free, just like the Web, the Internet, and many other networks we routinely use in our everyday lives. The unexpected dis-covery bring important meanings for OO program design, debugging costs, and garbage collection, etc.
(4) How to measure and control coupling interactions of software compo-nents is a largely explored research problem in software network. In terms of graph theory and linear algebra, this paper investigates a pair of coupling metrics to evaluate coupling interactions between the classes of object-oriented systems. These metrics differ from the majority of existing metrics in three aspects:taking into account the strength that one class depends on other ones, reflecting indirect coupling, and distinguishing various coupling interaction. An empirical compar-ison of the novel measures with one of the most widely used coupling metrics is described. Specifically, an experiment about the relationships of this pair metrics is conducted. The result shows that software complexity derived from coupling interaction could not be accurately reflected by one dimension of coupling metric for negative correlation.
This conception will help deepen our understanding of the essential of software complexity. At present the interdisciplinary research between complex networks and software engineering just grow. The approach that adopt complex network will help deepen our understanding of the essential of software complexity and provide a new insight into software engineering and raise the profile for dealing with software crisis.
引文
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