电子商务系统业务流程逆向恢复及可变性分析
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摘要
在现代商业社会活动中,各大公司或者组织机构每天都会用一些自动化处理软件来处理他们在工作中所遇到的各种复杂的业务处理流程。在一个业务流程的过程中,例如我们在电子商务系统上订货时,要执行相应的流程顺序(例如,选购商品,网上付款,接受商品等)。这些电子商务供应商每天都执行着这些业务流程处理程序。但是在各种新型业务流程层出不穷的今天,每天都有新的业务需求被提出,每天都要对旧流程进行修改,所以各大电子商务软件提供商会不断地修改自己的业务应用,以适应社会业务流程的变化。然而,当业务流程设计被修改和实施时,相应的文档修改往往没有跟上,导致后来系统的开发或者维护人员不能从系统文档上获得最新的业务流程信息,导致软件开发或者维护人员必须得花更多的时间到代码中理解现有的业务流程并修改相应的流程模块,这是一个耗时的也很容易出错的工作。所以要正确的修改与开发相应的流程模块,开发人员需要对应用软件在业务上要有深入理解,一致快速的开发出符合业务需求的应用软件。除此之外,由于缺乏对遗留软件系统资源的统一管理,软件开发人员常常做着一些重复的开发,这极大的降低了对软件系统的利用率,也增大了软件开发成本。
对于以上的问题,本文中我们提出了面向电子商务应用软件系统的相关流程恢复方法。本文主要针对三大电子商务应用软件的电子商务页而的之间的跳转关系以及页面之间控制关系来恢复相应的流程。我们将这些流程恢复成一个流程图,在本文中用状态机模型来表示软件系统的流程,除此之外我们还设计了流程差异比较算法,对三大业务相似的电子商务应用软件进行了业务流程对比分析。在流程差异比较算法设计中本文根据代数背景知识,在不同的流程图中提出了用同态图、同构图来表示不同业务流程图之间相似的业务流程,用异构图表示不同的业务流程图之间的业务流程差异。最后通过案例进行举例分析。
最后本文讨论了对业务相似的遗留系统,我们可以通过流程差异比较算法提取出遗留软件系统的共性与可变性。通过提取遗留软件系统在业务流程上的共性,我们可以开发出相应业务流程软件核心资产包括软件设计、代码模块,供以后的开发人员使用。对与提取的可变性功能,我们可以对比相似业务系统的之间的流程差异,帮助需求设计人员与软件开发人员快速了解不同系统之间的业务特点,以致开发出更符合用户需求的软件产品。
In the modern business today, companies or organizations with some automation software to handle their work encountered in a variety of complex business processes every day. In a business process, such as e-commerce which contain ordering, to execute the corresponding process sequence (for example, buy goods, online payment, accept the merchandise, etc.). But in the endless variety of new business processes of today, some new business always needs to be made every day to modify the old process every day, so the major e-commerce software provider will continue to modify their business applications to meet the business processes of social change. However, when the business process design and implementation has been modified, the corresponding documentation changes are often not kept pace, resulting in later system development or maintenance personnel can not be obtained from the document on the latest business process information, resulting in software development or maintenance personnel must spend more and more time to understand the existing code and modify the business process flow module, which is a very time-consuming and error-prone task. So to the right to modify and develop the corresponding process module, application software developers need to have in-depth understanding of business, consistent with rapid development of applications that meet business needs. In addition, legacy software systems due to lack of unified management of resources, software developers often doing some of the repeated development, which greatly reduces the utilization of the software system but also increases software development costs.
For solving the above problems, we proposed a e-business application software system for the relevant process recovery method in the paper. In this paper, with the relationship of the three e-commerce applications, and the relationship between jump one page to another page and then restore the appropriate relationship between the control processes. We will resume these processes as a flow chart, using state machine model in this paper to represent the software process. In addition, we also designed a process diff algorithm, similar to the three business application software business process comparative analysis, in the algorithm Based on the algebra background, presenting with the same state diagram in a different flow chart, with the composition of different business process diagrams to represent the similarity between business process, with heterogeneous flow chart diagram that the different business differences between the business processes. In the case study, we adopted the precision and recall rates to evaluate our algorithms.
Finally, we extract the in commonality and variability with the difference compare algorithm between processes from the business legacy systems with similar businesses. We can develop appropriate business process software with core assets, including software design, code modules, in order to developers use the resources through extracting the commonality in business processes from the Legacy software system. And extraction of the variability of software, we can compare similar services in the difference business systems, assist to requirement designers and software developers to understand the operational characteristics of the different systems quickly in order to meet user needs and develop more adjusted to software products.
对于以上的问题,本文中我们提出了面向电子商务应用软件系统的相关流程恢复方法。本文主要针对三大电子商务应用软件的电子商务页而的之间的跳转关系以及页面之间控制关系来恢复相应的流程。我们将这些流程恢复成一个流程图,在本文中用状态机模型来表示软件系统的流程,除此之外我们还设计了流程差异比较算法,对三大业务相似的电子商务应用软件进行了业务流程对比分析。在流程差异比较算法设计中本文根据代数背景知识,在不同的流程图中提出了用同态图、同构图来表示不同业务流程图之间相似的业务流程,用异构图表示不同的业务流程图之间的业务流程差异。最后通过案例进行举例分析。
最后本文讨论了对业务相似的遗留系统,我们可以通过流程差异比较算法提取出遗留软件系统的共性与可变性。通过提取遗留软件系统在业务流程上的共性,我们可以开发出相应业务流程软件核心资产包括软件设计、代码模块,供以后的开发人员使用。对与提取的可变性功能,我们可以对比相似业务系统的之间的流程差异,帮助需求设计人员与软件开发人员快速了解不同系统之间的业务特点,以致开发出更符合用户需求的软件产品。
In the modern business today, companies or organizations with some automation software to handle their work encountered in a variety of complex business processes every day. In a business process, such as e-commerce which contain ordering, to execute the corresponding process sequence (for example, buy goods, online payment, accept the merchandise, etc.). But in the endless variety of new business processes of today, some new business always needs to be made every day to modify the old process every day, so the major e-commerce software provider will continue to modify their business applications to meet the business processes of social change. However, when the business process design and implementation has been modified, the corresponding documentation changes are often not kept pace, resulting in later system development or maintenance personnel can not be obtained from the document on the latest business process information, resulting in software development or maintenance personnel must spend more and more time to understand the existing code and modify the business process flow module, which is a very time-consuming and error-prone task. So to the right to modify and develop the corresponding process module, application software developers need to have in-depth understanding of business, consistent with rapid development of applications that meet business needs. In addition, legacy software systems due to lack of unified management of resources, software developers often doing some of the repeated development, which greatly reduces the utilization of the software system but also increases software development costs.
For solving the above problems, we proposed a e-business application software system for the relevant process recovery method in the paper. In this paper, with the relationship of the three e-commerce applications, and the relationship between jump one page to another page and then restore the appropriate relationship between the control processes. We will resume these processes as a flow chart, using state machine model in this paper to represent the software process. In addition, we also designed a process diff algorithm, similar to the three business application software business process comparative analysis, in the algorithm Based on the algebra background, presenting with the same state diagram in a different flow chart, with the composition of different business process diagrams to represent the similarity between business process, with heterogeneous flow chart diagram that the different business differences between the business processes. In the case study, we adopted the precision and recall rates to evaluate our algorithms.
Finally, we extract the in commonality and variability with the difference compare algorithm between processes from the business legacy systems with similar businesses. We can develop appropriate business process software with core assets, including software design, code modules, in order to developers use the resources through extracting the commonality in business processes from the Legacy software system. And extraction of the variability of software, we can compare similar services in the difference business systems, assist to requirement designers and software developers to understand the operational characteristics of the different systems quickly in order to meet user needs and develop more adjusted to software products.
引文
[1]Lehman MM. Laws of Software Evolution Revisited. Proceedings of the 5th European Workshop,1996; Springer Verlag; 108-124.
[2]Ying Zoul, Jin Guo King,Chun Fool. Maokeng Hung.Recovering Business Processes from Business Applications.
[3]Jin Guo, Ying Zou. Detecting Clones in Business Applications.
[4]Earls AB, Embury SM, Turner NH. A Method for the Manual Extraction of Business logics from Legacy Source Code. BT Technology Journal,2002; Springer; 20(4):127-145.
[5]Huang H. Business Rule Extraction from Legacy Code. Proceedings of the 20th Conference on Computer Software and Applications,1996; IEEE Computer Society; 162.
[6]Poo DCC. Explicit Representation of Business Policies. Proceedings of Asia Pacific Software Engineering Conference,1998; IEEE Computer Society; 136-143.
[7]Shao J, Pound CJ. Extracting Business Rules from Information Systems, BT Technology Journal.1999; Kluwer Academic Publishers:Hingham,17(4): 179-186.
[8]Sneed HM, Erdos K. Extracting Business Rules from Source Code. Proceedings of 4th International Workshop on Program Comprehension,1996; IEEE Computer Society; 240.
[9]Sneed HM. Extracting Business Logic from Existing COBOL Programs as a Basis for Redevelopment. Proceedings of 9th International Workshop on Program Comprehension,2001. IEEE Computer Society; 167.
[10]COPL IE J O. Multi2paradigm design [D]. Brussels:Vrije Universiteit,2000.
[11]Hung M, Zou Y. A Framework for Exacting Workflows from E-Commerce Systems, Proceedings of Software Technology and Engineering Practice,2005; IEEE Computer Society; 43-46.
[12]Zou Y, Lau TC, Kontogiannis K, Tong T, McKegney R. Model-Driven Business Process Recovery. Proceedings of the 11th Working Conference on Reverse Engineering,2004. IEEE Computer Society; 224-233.
[13]Xing Z, Stroulia E. Understanding the Evolution and Co-Evolution of Classes in Object-Oriented Systems. Journal of Software Engineering and Knowledge Engineering,2006; 16(1):23-52.
[14]U. Manber, "Finding similar files in a large file system," presented at Usenix Winter 1994 Technical Conference, San Francisco,1994.
[15]N. Shivakumar and H. Garca-Molina, "Finding near-replicas of documents on the电子商务,”presented at Proceedings of Workshop on电子商务Databases (电子商务DB’98),Mar,1998.
[16]http://j-spider.sourceforge.net/
[17]Vander Aalst WMP, Reijers HA, Weijters AJMM, van Dongen BF, de Medeiros AKA, Song M, Verbeek HMW.Business Process Mining:An Industrial Application. Information Systems; 32(1):713-732.
[18]Antoniol G, Gueheneuc Y. Feature Identification:A Novel Approach and a Case Study, Proceedings of IEEE International Conference on Software Maintenance,2005; IEEE Computer Society; 357-366.
[19]Briand LC, Labiche Y, Leduc J. Towards the Reverse Engineering of UML Sequence Diagrams for Distributed Java Software. IEEE Transactions on Software Engineering,2006; 32(9):642-663.
[20]Chen K, Rajlich V. Case Study of Feature Location Using Dependence Graph. Proceedings of the 8th International Workshop on Program Comprehension. 2000; IEEE Computer Society; 241-247.
[21]Xulin Zhao, Ying Zou A Business Process Driven Approach for Generating Software Architecture.10th International Conference on Quality Software,2010
[22]G Salton Automatic text processing:the transformation Analysis and Retrieval of Information by Computer,1989.
[23]R. Rivest The MD5 Message-Digest Algorithm. MIT Laboratory for Computer Science and RSA Data Security, Inc.
[24]M Steinbach, G Karypis, V Kumar-A comparison of document clustering techniques KDD workshop on text mining,2000-Citeseer.
[25]A. K. Jain, M. N. Murty, P. J. Flynn Data clustering:a review. Journal ACM Computing Surveys (CSUR) Surveys Homepage archive Volume 31 Issue 3, Sept.1999.
[26]Stephen C. Johnson. Hierarchical clustering schemes Psychometrika Volume 32, Number 3,241-254.
[27]Daniel Boley, Maria Gini, Robert Gross, Eui-Hong (Sam) Han.Decision Support Systems.Volume 27, Issue 3, December 1999, Pages 329-341.
[28]Jorg Sander, Martin Ester, Hans-Peter Kriegel and Xiaowei Xu.Density-Based Clustering in Spatial Databases:The Algorithm GDBSCAN and ItsApplications.Data Mining and Knowledge Discovery Volume 2, Number 2, 169-194.
[29]Donald E. Gustafson,William C. Kessel. Fuzzy clustering with a fuzzy covariance matrix. Decision and Control including the 17th Symposium on Adaptive Processes,1978 IEEE Conference on Issue Date:Jan.1978 On page(s):761-766.
[30]韩士安,林磊。近世代数(第二版)。科学出版社,第30-50页。
[31]冯克勤,李尚志,章璞.近世代数引论(第3版).中国科学技术大学出版社,第10-30页。
[32]谢正茂,,“电子商务数据模型以及获取、存储方法研究“北京大学,硕士论文,2003。
[33]冯是聪, 张志刚,and李晓明,”一种中文网页自动分类方法的实现及其应用“计算机工程,2003。
[34]何清。“模糊聚类分析理论与应用研究进展”.模糊系统与数学。1998年,第二期,89-94页。
[35]Yinxing Xue, Zhenchang Xing and Stan Jarzabek. Understanding Feature Evolution in a Family of Product Variants. Reverse Engineering (WCRE), 2010 17th Working Conference on Issue Date:13-16 Oct.2010.
[36]Yijian Wu, Yiming Yang, Xin Peng. Recovering Object-Oriented Framework for SoftwareProduct Line Reengineering. ICSR 2012.
[37]Yiming Yang, Xin Peng, Wenyun Zhao. Domain Feature Model Recovery from Multiple Applications using Data Access Semantics and Formal Concept Anal. The 16th Working Conference on Reverse Engineering, WCRE 2009
[38]李晓明,“搜索引擎：原理、技术与系统”。科学出版社,2005-4,50-200
[2]Ying Zoul, Jin Guo King,Chun Fool. Maokeng Hung.Recovering Business Processes from Business Applications.
[3]Jin Guo, Ying Zou. Detecting Clones in Business Applications.
[4]Earls AB, Embury SM, Turner NH. A Method for the Manual Extraction of Business logics from Legacy Source Code. BT Technology Journal,2002; Springer; 20(4):127-145.
[5]Huang H. Business Rule Extraction from Legacy Code. Proceedings of the 20th Conference on Computer Software and Applications,1996; IEEE Computer Society; 162.
[6]Poo DCC. Explicit Representation of Business Policies. Proceedings of Asia Pacific Software Engineering Conference,1998; IEEE Computer Society; 136-143.
[7]Shao J, Pound CJ. Extracting Business Rules from Information Systems, BT Technology Journal.1999; Kluwer Academic Publishers:Hingham,17(4): 179-186.
[8]Sneed HM, Erdos K. Extracting Business Rules from Source Code. Proceedings of 4th International Workshop on Program Comprehension,1996; IEEE Computer Society; 240.
[9]Sneed HM. Extracting Business Logic from Existing COBOL Programs as a Basis for Redevelopment. Proceedings of 9th International Workshop on Program Comprehension,2001. IEEE Computer Society; 167.
[10]COPL IE J O. Multi2paradigm design [D]. Brussels:Vrije Universiteit,2000.
[11]Hung M, Zou Y. A Framework for Exacting Workflows from E-Commerce Systems, Proceedings of Software Technology and Engineering Practice,2005; IEEE Computer Society; 43-46.
[12]Zou Y, Lau TC, Kontogiannis K, Tong T, McKegney R. Model-Driven Business Process Recovery. Proceedings of the 11th Working Conference on Reverse Engineering,2004. IEEE Computer Society; 224-233.
[13]Xing Z, Stroulia E. Understanding the Evolution and Co-Evolution of Classes in Object-Oriented Systems. Journal of Software Engineering and Knowledge Engineering,2006; 16(1):23-52.
[14]U. Manber, "Finding similar files in a large file system," presented at Usenix Winter 1994 Technical Conference, San Francisco,1994.
[15]N. Shivakumar and H. Garca-Molina, "Finding near-replicas of documents on the电子商务,”presented at Proceedings of Workshop on电子商务Databases (电子商务DB’98),Mar,1998.
[16]http://j-spider.sourceforge.net/
[17]Vander Aalst WMP, Reijers HA, Weijters AJMM, van Dongen BF, de Medeiros AKA, Song M, Verbeek HMW.Business Process Mining:An Industrial Application. Information Systems; 32(1):713-732.
[18]Antoniol G, Gueheneuc Y. Feature Identification:A Novel Approach and a Case Study, Proceedings of IEEE International Conference on Software Maintenance,2005; IEEE Computer Society; 357-366.
[19]Briand LC, Labiche Y, Leduc J. Towards the Reverse Engineering of UML Sequence Diagrams for Distributed Java Software. IEEE Transactions on Software Engineering,2006; 32(9):642-663.
[20]Chen K, Rajlich V. Case Study of Feature Location Using Dependence Graph. Proceedings of the 8th International Workshop on Program Comprehension. 2000; IEEE Computer Society; 241-247.
[21]Xulin Zhao, Ying Zou A Business Process Driven Approach for Generating Software Architecture.10th International Conference on Quality Software,2010
[22]G Salton Automatic text processing:the transformation Analysis and Retrieval of Information by Computer,1989.
[23]R. Rivest The MD5 Message-Digest Algorithm. MIT Laboratory for Computer Science and RSA Data Security, Inc.
[24]M Steinbach, G Karypis, V Kumar-A comparison of document clustering techniques KDD workshop on text mining,2000-Citeseer.
[25]A. K. Jain, M. N. Murty, P. J. Flynn Data clustering:a review. Journal ACM Computing Surveys (CSUR) Surveys Homepage archive Volume 31 Issue 3, Sept.1999.
[26]Stephen C. Johnson. Hierarchical clustering schemes Psychometrika Volume 32, Number 3,241-254.
[27]Daniel Boley, Maria Gini, Robert Gross, Eui-Hong (Sam) Han.Decision Support Systems.Volume 27, Issue 3, December 1999, Pages 329-341.
[28]Jorg Sander, Martin Ester, Hans-Peter Kriegel and Xiaowei Xu.Density-Based Clustering in Spatial Databases:The Algorithm GDBSCAN and ItsApplications.Data Mining and Knowledge Discovery Volume 2, Number 2, 169-194.
[29]Donald E. Gustafson,William C. Kessel. Fuzzy clustering with a fuzzy covariance matrix. Decision and Control including the 17th Symposium on Adaptive Processes,1978 IEEE Conference on Issue Date:Jan.1978 On page(s):761-766.
[30]韩士安,林磊。近世代数(第二版)。科学出版社,第30-50页。
[31]冯克勤,李尚志,章璞.近世代数引论(第3版).中国科学技术大学出版社,第10-30页。
[32]谢正茂,,“电子商务数据模型以及获取、存储方法研究“北京大学,硕士论文,2003。
[33]冯是聪, 张志刚,and李晓明,”一种中文网页自动分类方法的实现及其应用“计算机工程,2003。
[34]何清。“模糊聚类分析理论与应用研究进展”.模糊系统与数学。1998年,第二期,89-94页。
[35]Yinxing Xue, Zhenchang Xing and Stan Jarzabek. Understanding Feature Evolution in a Family of Product Variants. Reverse Engineering (WCRE), 2010 17th Working Conference on Issue Date:13-16 Oct.2010.
[36]Yijian Wu, Yiming Yang, Xin Peng. Recovering Object-Oriented Framework for SoftwareProduct Line Reengineering. ICSR 2012.
[37]Yiming Yang, Xin Peng, Wenyun Zhao. Domain Feature Model Recovery from Multiple Applications using Data Access Semantics and Formal Concept Anal. The 16th Working Conference on Reverse Engineering, WCRE 2009
[38]李晓明,“搜索引擎：原理、技术与系统”。科学出版社,2005-4,50-200