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A Variability-based Testing Approach for Synthesizing Video Sequences

by José Angel Galindo Duarte, Mauricio Alférez, Mathieu Acher, Benoit Baudry, David Benavides
Abstract:
A key problem when developing video processing software is the difficulty to test different input combinations. In this paper, we present VANE, a variability-based testing approach to derive video sequence variants. The ideas of VANE are i) to encode in a variability model what can vary within a video sequence; ii) to exploit the variability model to generate testable configurations; iii) to synthesize variants of video sequences corresponding to configurations. VANE computes T-wise covering sets while optimizing a function over attributes. Also, we present a preliminary validation of the scalability and practicality of VANE in the context of an industrial project involving the test of video processing algorithms.VANE computes T-wise covering sets while optimizing a function over attributes. Also, we present a preliminary validation of the scalability and practicality of VANE in the context of an industrial project involving the test of video processing algorithms.
Reference:
A Variability-based Testing Approach for Synthesizing Video Sequences (José Angel Galindo Duarte, Mauricio Alférez, Mathieu Acher, Benoit Baudry, David Benavides), In Proc. of the Int. Symp. on Software Testing and Analysis (ISSTA), 2014.
Bibtex Entry:
@inproceedings{galindo14,
    keywords = {test, SPL},
    title = {{A Variability-based Testing Approach for Synthesizing Video Sequences}},
    author = {Galindo Duarte, Jos{'e} Angel and Alf{'e}rez, Mauricio and Acher, Mathieu and Baudry, Benoit and Benavides, David},
    abstract = {{A key problem when developing video processing software is the difficulty to test different input combinations. In this paper, we present VANE, a variability-based testing approach to derive video sequence variants. The ideas of VANE are i) to encode in a variability model what can vary within a video sequence; ii) to exploit the variability model to generate testable configurations; iii) to synthesize variants of video sequences corresponding to configurations. VANE computes T-wise covering sets while optimizing a function over attributes. Also, we present a preliminary validation of the scalability and practicality of VANE in the context of an industrial project involving the test of video processing algorithms.VANE computes T-wise covering sets while optimizing a function over attributes. Also, we present a preliminary validation of the scalability and practicality of VANE in the context of an industrial project involving the test of video processing algorithms.}},
    booktitle = {{Proc. of the Int. Symp. on Software Testing and Analysis (ISSTA)}},
    pages = {},
    address = {CA, USA},
  	X-International-Audience = {yes},
  	X-Language = {EN},
  	x-abbrv = {ISSTA},
    year = {2014},
    url = {http://hal.inria.fr/docs/01/00/56/12/PDF/paper.pdf}
}