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Test data is data that exists (e.g., in a database) before a test is executed, and that affects or is affected by the component or system under test.


Resources for “Test Data”

Articles

This article is excerpted from Chapter 3 of Rex Black's popular book Managing the Testing Process, 3e.

A number of RBCS clients find that obtaining good test data poses many challenges. For any large-scale system, testers usually cannot create sufficient and sufficiently diverse test data by hand; i.e., one record at a time. While data-generation tools exist and can create almost unlimited amounts of data, the data so generated often do not exhibit the same diversity and distribution of values as production data. For these reasons, many of our clients consider production data ideal for testing, particularly for systems where large sets of records have accumulated over years of use with various revisions of the systems currently in use, and systems previously in use.

However, to use production data, we must preserve privacy. Production data often contains personal data about individuals which must be handled securely. However, requiring secure data handling during testing activities imposes undesirable inefficiencies and constraints. Therefore, many organizations want to anonymize (scramble) the production data prior to using it for testing.

This anonymization process leads to the next set of challenges, though. The anonymization process must occur securely, in the sense that it is not reversible should the data fall into the wrong hands. For example, simply substituting the next digit or the next letter in sequence would be obvious to anyone it doesn’t take long to deduce that “Kpio Cspxo” is actually “John Brown”-which makes the de-anonymization process trivial.

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This article is excerpted from Chapter 3 of Rex Black’s book Managing the Testing Process, 3e.

A number of RBCS clients find that obtaining good test data poses many challenges. For any large-scale system, testers usually cannot create sufficient and sufficiently diverse test data by hand; i.e., one record at a time. While data-generation tools exist and can create almost unlimited amounts of data, the data so generated often do not exhibit the same diversity and distribution of values as production data. For these reasons, many of our clients consider production data ideal for testing, particularly for systems where large sets of records have accumulated over years of use with various revisions of the systems currently in use, and systems previously in use. 

However, to use production data, we must preserve privacy. Production data often contains personal data about individuals which must be handled securely. However, requiring secure data handling during testing activities imposes undesirable inefficiencies and constraints. Therefore, many organizations want to anonymize (scramble) the production data prior to using it for testing.

This anonymization process leads to the next set of challenges, though. The anonymization process must occur securely, in the sense that it is not reversible should the data fall into the wrong hands. For example, simply substituting the next digit or the next letter in sequence would be obvious to anyone­ it doesn’t take long to deduce that "Kpio Cspxo" is actually "John Brown" ­which makes the de-anonymization process trivial. 

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Suppose you went to a restaurant for dinner, sat down, and told the waiter, "Bring me dinner and a drink." You didn't provide any further details, though you had something specific in mind. What are the chances that you'll get the dinner and drink you expected? While no one would ever do this in a restaurant, it happens sometimes on projects that involve third parties.

If we have certain expectations and requirements for an engagement with a third party, those should be defined and clearly communicated between the parties. The best practice is to have that definition and communication before the project starts and to put the agreed-upon terms into the contract. If the third party is delivering software, then these requirements should include quality targets, including measurements of those targets. The measurements should be objective and not subject to distortions.

In addition to defining the requirements, the point at which those requirements must be met should be defined. This can be done by defining entry and exit criteria that establish quality gates for deliverables. Because these quality gates will control the start and end of project phases, they should be synchronized with the phases of the project and aligned with project schedule milestones. 

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"Back in 2010, at the launch of Core Magazine, http://www.coremag.eu/, I wrote a series of columns to welcome people to the magazine. As a sort of Throw-Back-December, here they are, as they appeared in the original magazine issues. I hope you enjoy them."
-Rex Black
 
Greetings, and welcome to my quarterly column on software testing best practices.  When I was asked to write this column, I had to choose the approach, the theme.  The writers' aphorism says, "Write what you know." So, what do I know?
 
Well, if you know me and my consulting company, RBCS, you know that we spend time with clients around the world, in every possible industry, helping people improve their testing with training or consulting services, or doing testing for them with our outsourcing services.  Our work gives me insights into what goes on, the actual day-to-day practice of software testing.
 

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Webinars

Podcast Episodes

Webinar: Enterprise Challenges of Test Data 5/16/17


Length: 0h 53m 46s

If you are testing a simple mobile app, you may find it relatively easy to find representative test data. However, what if you are testing enterprise scale applications? In the enterprise data center, one hundred or more applications of various sizes, complexity, and criticality co-exist, operating on various data repositories, in some cases shared data repositories. In some cases, disparate data repositories hold related data, and the ability to test integration across applications that access these data sets is critical.  In this keynote speech, Rex Black will talk about the challenges facing his clients as they deal with these testing problems. You’ll go away with a better understanding of the nature of the challenges, as well as ideas on how to handle them, grounded in lessons Rex has learned in over 30 years of software engineering and testing.

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Training

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