Service virtualization

In software engineering, service virtualization is a method to emulate the behavior of specific components in heterogeneous component-based applications such as API-driven applications, cloud-based applications and service-oriented architectures. It is used to provide software development and QA/testing teams access to dependent system components that are needed to exercise an application under test (AUT), but are unavailable or difficult-to-access for development and testing purposes. With the behavior of the dependent components "virtualized," testing and development can proceed without accessing the actual live components. Service virtualization is recognized by vendors, industry analysts, and industry publications as being different than mocking.[1][2]

Service virtualization overview

Service virtualization emulates the behavior of software components to remove dependency constraints on development and testing teams. Such constraints occur in complex, interdependent environments when a component connected to the application under test is:

Although the term "service virtualization" reflects the technique's initial focus on virtualizing web services, service virtualization extends across all aspects of composite applications: services, databases, mainframes, ESBs, and other components that communicate using common messaging protocols.[4][5][6]

Service virtualization emulates only the behavior of the specific dependent components that developers or testers need to exercise in order to complete their end-to-end transactions. Rather than virtualizing entire systems, it virtualizes only specific slices of dependent behavior critical to the execution of development and testing tasks. This provides just enough application logic so that the developers or testers get what they need without having to wait for the actual service to be completed and readily available. For instance, instead of virtualizing an entire database (and performing all associated test data management as well as setting up the database for every test session), you monitor how the application interacts with the database, then you emulate the related database behavior (the SQL queries that are passed to the database, the corresponding result sets that are returned, and so forth).[7] [8]

Applying service virtualization

Service virtualization involves creating and deploying a "virtual asset" that simulates the behavior of a real component which is required to exercise the application under test, but is difficult or impossible to access for development and testing purposes.

A virtual asset stands in for a dependent component by listening for requests and returning an appropriate response—with the appropriate performance. For a database, this might involve listening for a SQL statement, then returning data source rows. For a web service, this might involve listening for an XML message over HTTP, JMS, or MQ, then returning another XML message. The virtual asset's functionality and performance might reflect the actual functionality/performance of the dependent component, or it might simulate exceptional conditions (such as extreme loads or error conditions) to determine how the application under test responds under those circumstances.

Virtual assets are typically created by:

They are then further configured to represent specific data, functionality, and response times.

Virtual assets are deployed locally or in the cloud (public or private). With development/test environments configured to use the virtual assets in place of dependent components, developers or testers can then exercise the application they are working on without having to wait for the dependent components to be completed or readily accessible.[4][5][8]

Industry analysts report that service virtualization is best suited for "IT shops with significant experience with 'skipping' integration testing due to 'dependent software', and with a reasonably sophisticated test harness.[9]

How service virtualization relates to stubbing and mocking

An alternative approach to working around the test environment access constraints outlined in this article's introduction is for team members to develop method stubs or mock objects that substitute for dependent resources. The shortcoming of this approach became apparent in the early 2000s with the rise of Service-oriented architecture.[10] The proliferation of Composite applications that rely on numerous dependent services, plus the rise of Agile software development following the 2001 publication of the Agile Manifesto, made it increasingly difficult for developers or testers to manually develop the number, scope, and complexity of stubs or mocks required to complete development and testing tasks for modern enterprise application development [11]

The first step in the evolution from stubbing to service virtualization was the technology packaged in SOA testing tools since 2002.[12] The earliest implementations of service virtualization were designed to automate the process of developing simple stub-like emulations so that composite applications could be tested more efficiently.[13] As enterprise systems continued to grow increasingly complex and distributed, software tool vendors shifted focus from stubbing to the more environment-focused service virtualization.[3] While stubbing can still be completed through manual development and management of stubs, what has become known as "service virtualization" is completed by using one of the available commercial off the shelf (COTS) service virtualization technologies as a platform for the development and deployment of their "service virtualization assets." [11]

Tools available in the market

Open source stubbing/mocking or service virtualization tools:

Other mocking tools:

Commercial service virtualization tools:

References

  1. Service Virtualization as an Alternative to Mocking, by Jonathan Allen, eBizQ April 22, 2013
  2. 1 2 3 4 5 Service virtualization arises to meet services testing obstacles, by George Lawton, SearchSOA May 15, 2012
  3. 1 2 Service Virtualization for Modern Applications by Gaurish Hattangadi, Virtual Strategy Magazine, November 28, 2010
  4. 1 2 Managing Test Environments by Liz McMillan, Cloud Computing Journal, December 2011
  5. 1 2 Application Behavior Virtualization by Elizabeth White, Cloud Computing Journal, December 2011
  6. Database Virtualization For Development and Test by Wayne Ariola, ST & QA Magazine, March 2012
  7. An Intro to SOA and Virtualization by John Michelsen, WebServices.org, August 2007
  8. 1 2 The Next Generation of Test Environment Management by Wayne Ariola, Virtualization Journal, July 12, 2011
  9. Parasoft and "Service Virtualization" Testing: A Good Idea by Wayne Kernochan, Thoughts From a Software IT Analyst, February 22, 2013
  10. Testing in Service-Oriented Environments by Ed Morris et al, Software Engineering Institute, March 2010
  11. 1 2 Service virtualization is helping organizations realize business value from testing by Chandranshu Singh, ovum, March 31, 2014
  12. Parasoft's Web Service Testing Tool Should Aid Development by Theresa Lanowitz Gartner, May 1, 2002
  13. SOA virtualization gets real by Rich Seeley, SearchSOA, November 28, 2007
  14. SoapUI SOAP Virtualization
  15. SoapUI REST Virtualization
  16. betamax homepage
  17. betamax source code
  18. https://github.com/rest-driver/rest-driver/wiki rest-driver homepage
  19. http://mock-server.com MockServer homepage
  20. VCR docs
  21. WireMock Homepage
  22. Web Service Mocker on sourceforge
  23. mountebank home page
  24. Hoverfly open source service virtualization
  25. Mirage open source service virtualization
  26. Service Virtualization with Wilma - Documentation
  27. Service Virtualization with Wilma - Source code
  28. Sandbox Homepage
  29. 1 2 3 4 The Forrester Wave™: Service Virtualization And Testing Solutions, Q1 2014 by Diego Lo Giudice with Mike Gualtieri, Jeffrey S. Hammond, Rowan Curran, Forrester Research 2014
  30. 1 2 3 4 voke Market Snapshot Service Virtualization by Theresa Lanowitz, voke Research
  31. 1 2 3 4 Extreme automation, meet the pre-production life cycle, by Alexandra Weber Morales, SD Times, January 15, 2014
This article is issued from Wikipedia - version of the Tuesday, January 26, 2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.