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Evolutionary Robustness Testing of Data Processing Systems using Models and Data Mutation
Di Nardo, Daniel; Pastore, Fabrizio; Arcuri, Andrea et al.
2015In Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering
Peer reviewed
 

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Abstract :
[en] System level testing of industrial data processing software poses several challenges. Input data can be very large, even in the order of gigabytes, and with complex constraints that define when an input is valid. Generating the right input data to stress the system for robustness properties (e.g. to test how faulty data is handled) is hence very complex, tedious and error prone when done manually. Unfortunately, this is the current practice in industry. In previous work, we defined a methodology to model the structure and the constraints of input data by using UML class diagrams and OCL constraints. Tests were automatically derived to cover predefined fault types in a fault model. In this paper, to obtain more effective system level test cases, we developed a novel search-based test generation tool. Experiments on a real-world, large industrial data processing system show that our automated approach can not only achieve better code coverage, but also accomplishes this using significantly smaller test suites.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab)
Disciplines :
Computer science
Author, co-author :
Di Nardo, Daniel ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Pastore, Fabrizio  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Arcuri, Andrea;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Briand, Lionel ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
no
Language :
English
Title :
Evolutionary Robustness Testing of Data Processing Systems using Models and Data Mutation
Publication date :
November 2015
Event name :
30th IEEE/ACM International Conference on Automated Software Engineering (ASE 2015)
Event place :
Lincoln, Nebraska, United States
Event date :
November 9–13, 2015
Audience :
International
Main work title :
Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering
Pages :
126-137
Peer reviewed :
Peer reviewed
FnR Project :
FNR4082113 - Regression Test Suite Management Strategies For Web Applications, 2012 (01/05/2012-30/04/2016) - Daniel Di Nardo
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since 22 July 2015

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