Execution patterns for visualizing web services

Web Services are well on their way to becoming the Lingua Franca for distributed computing. Although tools for building and monitoring web services applications are more powerful and easier to use than ever, they do not yet fully address the horizontal complexity of mature applications built as large nets of interconnected web services. We present a pattern-based visualization that enables business owners, application designers, programmers, and operations staff to quickly understand the behavior of complex web services applications. We describe a novel pattern extraction algorithm that captures important trends from web services execution traces. We demonstrate a new way to visualize these patterns that shows the behavior of web services applications at different levels of abstraction. Finally, we explain how this can help developers with performance analysis by showing both the averages and variations in the data contained in each pattern.

[1]  Wil M. P. van der Aalst,et al.  Mining Social Networks: Uncovering Interaction Patterns in Business Processes , 2004, Business Process Management.

[2]  Randy Goebel,et al.  Visualizing and discovering web navigational patterns , 2004, WebDB '04.

[3]  John T. Stasko,et al.  PVaniM: a tool for visualization in network computing environments , 1998, Concurr. Pract. Exp..

[4]  John T. Stasko,et al.  Visualizing Interactions in Program Executions , 1997, Proceedings of the (19th) International Conference on Software Engineering.

[5]  Gary Sevitsky,et al.  Visualizing reference patterns for solving memory leaks in Java , 1999, Concurr. Pract. Exp..

[6]  Gary Sevitsky,et al.  Visualizing reference patterns for solving memory leaks in Java , 1999, Concurr. Pract. Exp..

[7]  Xiang Fu,et al.  Analysis of interacting BPEL web services , 2004, WWW '04.

[8]  Mark W. Johnson.  Monitoring and Diagnosing Applications with ARM 4.0 , 2004, Int. CMG Conference.

[9]  Mark N. Wegman,et al.  Execution Patterns in Object-Oriented Visualization , 1998, COOTS.

[10]  Linton C. Freeman,et al.  Carnegie Mellon: Journal of Social Structure: Visualizing Social Networks Visualizing Social Networks , 2022 .

[11]  Yan Zhao,et al.  Visualization of Communication Patterns in Collaborative Innovation Networks - Analysis of Some W3C Working Groups , 2003, CIKM '03.

[12]  Steven P. Reiss.  Dynamic detection and visualization of software phases , 2005, WODA '05.

[13]  Michael T. Heath,et al.  Visualizing the performance of parallel programs , 1991, IEEE Software.

[14]  Jock D. Mackinlay,et al.  Visualizing the evolution of Web ecologies , 1998, CHI.

[15]  Marcos K. Aguilera,et al.  Performance debugging for distributed systems of black boxes , 2003, SOSP '03.

[16]  D.A. Reed,et al.  Scalable performance analysis: the Pablo performance analysis environment , 1993, Proceedings of Scalable Parallel Libraries Conference.

[17]  W. De Pauw,et al.  Web Services Navigator: Visualizing the execution of Web Services , 2005, IBM Syst. J..

[18]  Eric. Newcomer,et al.  Understanding SOA with Web Services , 2004 .

[19]  John T. Stasko,et al.  The information mural: a technique for displaying and navigating large information spaces , 1995, Proceedings of Visualization 1995 Conference.

[20]  Joseph L. Hellerstein,et al.  ETE: a customizable approach to measuring end-to-end response times and their components in distributed systems , 1999, Proceedings. 19th IEEE International Conference on Distributed Computing Systems (Cat. No.99CB37003).

[21]  Hui Wang,et al.  Pattern extraction method for text classification , 2000 .

[22]  Johan Moe,et al.  Understanding distributed systems via execution trace data , 2001, Proceedings 9th International Workshop on Program Comprehension. IWPC 2001.

[23]  Frank Leymann,et al.  Web Services Platform Architecture: SOAP, WSDL, WS-Policy, WS-Addressing, WS-BPEL, WS-Reliable Messaging, and More , 2005 .

[24]  Steven P. Reiss,et al.  Jove: java as it happens , 2005, SoftVis '05.