Developing a Tool to Support Synthetic Test Data Generation for Performance Testing of Application Systems


Application systems represent an important group of software systems in today’s companies. One main characteristic of these systems is their usage of databases to store customer or product information. However, the databases can add additional complexity to the testing activities because different test cases may require the databases to contain specific but different information.

When it comes to performance testing of application systems, huge amounts of realistic test data are required in order to be able to generate the desired load level. Since the manual creation of the test data is tedious, an automatic approach is desirable.

More recently, model-based testing has become a promising approach to not only systemize but also to (partially) automate central testing activities based on information extracted from models such as UML diagrams.

Goals of the Thesis

The goal of this thesis is to develop a concept for the model-based generation of test data which meets the specific requirements of performance testing and to evaluate this concept using a prototypical implementation.

Tasks

  • Requirements Analysis: At the beginning, the specific requirements of test data for performance testing should be collected. In addition, the generation process and information needs of data generation tools such as Databene Benerator should be analyzed according to the test data requirements. In addition, available models and necessary manual steps should be identified.
  • Conceptual Design: Based on this analysis, a concept of the prototype should be designed by relating the identified requirements and by choosing appropriate techniques of model-based testing.
  • Prototypical Implementation: Finally, the concept should be realized by developing a first prototypical implementation and also by evaluating the prototype with test data for real performance tests.

Literature

  • Klaus Haller. 2010. The test data challenge for database-driven applications. In Proceedings of the Third International Workshop on Testing Database Systems (DBTest ’10). ACM, New York, NY, USA, , Article 6 , 6 pages.
  • Utting, Mark, Alexander Pretschner, and Bruno Legeard. A taxonomy of model-based testing approaches. In Software Testing, Verification and Reliability 22.5 (2012): 297-312.
  • Dias Neto, Arilo C., et al. A survey on model-based testing approaches: a systematic review. In Proceedings of the 1st ACM international workshop on Empirical assessment of software engineering languages and technologies: held in conjunction with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE) 2007. ACM, 2007. S. 31-36.
  • Kleuker, Stephan. Applikationen mit Datenbankanbindung. In: Qualitätssicherung durch Softwaretests. Springer Fachmedien Wiesbaden, 2013. S. 215-265.
  • Ayala-Rivera, V., McDonagh, P., Cerqueus, T., & Murphy, L. (2013). Synthetic Data Generation using Benerator Tool.
  • Databene Benerator: http://databene.org/databene-benerator
  • Databene Benerator Manual: http://databene.org/download/databene-benerator-manual-0.7.6.pdf

Info

  • Type: Master Thesis
  • Status: Completed
  • ID: 2016-005
  • Student: Ekaterina Lobanova

  • Language: German, English

Supervisor