Compositional CLP-based Test Data Generation for Imperative Languages

Albert Albiol, Elvira and Gomez Zamalloa, Miguel and Rojas Siles, Jose Miguel and Puebla Sánchez, Alvaro Germán (2010). Compositional CLP-based Test Data Generation for Imperative Languages. In: "20th international conference on Logic-based program synthesis and transformation LOPSTR'10", 23/07/2010 - 25/07/2010, Hagenberg, Austria. ISBN 978-3-642-20550-7.

Description

Title: Compositional CLP-based Test Data Generation for Imperative Languages
Author/s:
  • Albert Albiol, Elvira
  • Gomez Zamalloa, Miguel
  • Rojas Siles, Jose Miguel
  • Puebla Sánchez, Alvaro Germán
Item Type: Presentation at Congress or Conference (Article)
Event Title: 20th international conference on Logic-based program synthesis and transformation LOPSTR'10
Event Dates: 23/07/2010 - 25/07/2010
Event Location: Hagenberg, Austria
Title of Book: Proceedings of the 20th international conference on Logic-based program synthesis and transformation
Date: 2010
ISBN: 978-3-642-20550-7
Subjects:
Faculty: Facultad de Informática (UPM)
Department: Lenguajes y Sistemas Informáticos e Ingeniería del Software
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Glass-box test data generation (TDG) is the process of automatically generating test input data for a program by considering its internal structure. This is generally accomplished by performing symbolic execution of the program where the contents of variables are expressions rather than concrete values. The main idea in CLP-based TDG is to translate imperative programs into equivalent CLP ones and then rely on the standard evaluation mechanism of CLP to symbolically execute the imperative program. Performing symbolic execution on large programs becomes quickly expensive due to the large number and the size of paths that need to be explored. In this paper, we propose compositional reasoning in CLP-based TDG where large programs can be handled by testing parts (such as components, modules, libraries, methods, etc.) separately and then by composing the test cases obtained for these parts to get the required information on the whole program. Importantly, compositional reasoning also gives us a practical solution to handle native code, which may be unavailable or written in a different programming language. Namely, we can model the behavior of a native method by means of test cases and compositional reasoning is able to use them

More information

Item ID: 9134
DC Identifier: http://oa.upm.es/9134/
OAI Identifier: oai:oa.upm.es:9134
Deposited by: Memoria Investigacion
Deposited on: 15 Nov 2011 09:11
Last Modified: 20 Apr 2016 17:40
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