by Ivo Krka, Yuriy Brun, Daniel Popescu, Joshua Garcia, Nenad Medvidovic
Abstract:
Software behavioral models have proven useful for design, validation, verification, and maintenance. However, existing approaches for deriving such models sometimes overgeneralize what behavior is legal. We outline a novel approach that utilizes inferred program invariants and method invocation sequences to obtain an object-level model to describe legal execution sequences. The key insight is using program invariants to identify similar states in the sequences. We exemplify how our approach improves upon certain aspects of the state-of-the-art FSA-inference techniques.
Citation:
Ivo Krka, Yuriy Brun, Daniel Popescu, Joshua Garcia, and Nenad Medvidovic, Using dynamic execution traces and program invariants to enhance behavioral model inference, in Proceedings of the New Ideas and Emerging Results Track at the 32nd International Conference on Software Engineering (ICSE), 2010, pp. 179–182.
Bibtex:
@inproceedings{Krka10icse-nier,
author = {Ivo Krka and Yuriy Brun and Daniel Popescu and Joshua Garcia and
Nenad Medvidovic},
title =
{\href{http://people.cs.umass.edu/brun/pubs/pubs/Krka10icse-nier.pdf}{Using
dynamic execution traces and program invariants to enhance behavioral model
inference}},
booktitle = {Proceedings of the New Ideas and Emerging Results Track at the
32nd International Conference on Software Engineering (ICSE)},
venue = {ICSE NIER},
address = {Cape Town, South Africa},
month = {May},
date = {2--8},
year = {2010},
pages = {179--182},
doi = {10.1145/1810295.1810324},
accept = {$\frac{19}{76} \approx 25\%$},
note = {\href{https://doi.org/10.1145/1810295.1810324}{DOI:
10.1145/1810295.1810324}},
abstract = {Software behavioral models have proven useful for design,
validation, verification, and maintenance. However, existing approaches for
deriving such models sometimes overgeneralize what behavior is legal. We
outline a novel approach that utilizes inferred program invariants and
method invocation sequences to obtain an object-level model to describe
legal execution sequences. The key insight is using program invariants to
identify similar states in the sequences. We exemplify how our approach
improves upon certain aspects of the state-of-the-art FSA-inference
techniques.},
fundedBy = {NSF CSR-0720612, NSF 0820170,
NSF CNS-0937060 to the CRA for the CIFellows Project},
}