TY - GEN
T1 - Scalable timing analysis with refinement
AU - Guan, Nan
AU - Tang, Yue
AU - Abdullah, Jakaria
AU - Stigge, Martin
AU - Yi, Wang
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2015
Y1 - 2015
N2 - Traditional timing analysis techniques rely on composing system-level worst-case behavior with local worst-case behaviors of individual components. In many complex real-time systems, no single local worst-case behavior exists for each component and it generally requires to enumerate all the combinations of individual local behaviors to find the global worst case. This paper presents a scalable timing analysis technique based on abstraction refinement, which provides effective guidance to significantly prune away state space and quickly verify the desired timing properties. We first establish the general framework of the method, and then apply it to solve the analysis problem for several different realtime task models.
AB - Traditional timing analysis techniques rely on composing system-level worst-case behavior with local worst-case behaviors of individual components. In many complex real-time systems, no single local worst-case behavior exists for each component and it generally requires to enumerate all the combinations of individual local behaviors to find the global worst case. This paper presents a scalable timing analysis technique based on abstraction refinement, which provides effective guidance to significantly prune away state space and quickly verify the desired timing properties. We first establish the general framework of the method, and then apply it to solve the analysis problem for several different realtime task models.
KW - Digraph realtime task model
KW - Real-time systems
KW - Scalability
KW - Timing analysis
UR - https://www.scopus.com/pages/publications/84926658169
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84926658169&origin=recordpage
U2 - 10.1007/978-3-662-46681-0_1
DO - 10.1007/978-3-662-46681-0_1
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9783662466803
VL - 9035
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 3
EP - 18
BT - Tools and Algorithms for the Construction and Analysis of Systems - 21st International Conference, TACAS 2015 held as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2015, Proceedings
PB - Springer Verlag
T2 - 21st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2015 held as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2015
Y2 - 11 April 2015 through 18 April 2015
ER -