Answer-Set Programming as a New Approach to Event-Sequence Testing. Erdem, E., Inoue, K., Oetsch, J., Puehrer, J., Tompits, H., & Yilmaz, C. In Proc. of the 3rd International Conference on Advances in System Testing and Validation Lifecycle (VALID'11), 2011. N abstract bibtex In many applications, faults are triggered by events that occur in a particular order. Based on the assumption that most bugs are caused by the interaction of a low number of events, Kuhn et al. recently introduced sequence covering arrays (SCAs) as suitable designs for event sequence testing. In practice, directly applying SCAs for testing is often impaired by additional constraints, and SCAs have to be adapted to it application-specific needs. Modifying precomputed SCAs to account for problem variations can be problematic, if not impossible, and developing dedicated algorithms is costly. In this paper, we propose answer-set programming (ASP), a well-known knowledge-representation formalism from the area of artificial intelligence based on logic programming, as a declarative paradigm for computing SCAs. Our approach allows to concisely state complex coverage criteria in an elaboration tolerant way, i.e., small variations of a problem specification require only small modifications of the ASP representation.
@inproceedings{valid11,
urln = {valid11.pdf},
author = {Esra Erdem and Katsumi Inoue and Johannes Oetsch and Joerg Puehrer and Hans
Tompits and Cemal Yilmaz},
title = {Answer-Set Programming as a New Approach to Event-Sequence Testing},
booktitle = {Proc. of the 3rd International Conference on Advances in System Testing
and Validation Lifecycle (VALID'11)},
year = {2011},
abstract={In many applications, faults are triggered by events that occur in a particular order. Based on the
assumption that most bugs are caused by the interaction of a low number of events, Kuhn et al. recently introduced
sequence covering arrays (SCAs) as suitable designs for event sequence testing. In practice, directly applying SCAs for
testing is often impaired by additional constraints, and SCAs have to be adapted to it application-specific needs.
Modifying precomputed SCAs to account for problem variations can be problematic, if not impossible, and developing
dedicated algorithms is costly. In this paper, we propose answer-set programming (ASP), a well-known
knowledge-representation formalism from the area of artificial intelligence based on logic programming, as a declarative
paradigm for computing SCAs. Our approach allows to concisely state complex coverage criteria in an elaboration
tolerant way, i.e., small variations of a problem specification require only small modifications of the ASP
representation.}
}
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