---
_id: '12854'
abstract:
- lang: eng
text: "The main idea behind BUBAAK is to run multiple program analyses in parallel
and use runtime monitoring and enforcement to observe and control their progress
in real time. The analyses send information about (un)explored states of the program
and discovered invariants to a monitor. The monitor processes the received data
and can force an analysis to stop the search of certain program parts (which have
already been analyzed by other analyses), or to make it utilize a program invariant
found by another analysis.\r\nAt SV-COMP 2023, the implementation of data exchange
between the monitor and the analyses was not yet completed, which is why BUBAAK
only ran several analyses in parallel, without any coordination. Still, BUBAAK
won the meta-category FalsificationOverall and placed very well in several other
(sub)-categories of the competition."
acknowledgement: This work was supported by the ERC-2020-AdG 10102009 grant.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Marek
full_name: Chalupa, Marek
id: 87e34708-d6c6-11ec-9f5b-9391e7be2463
last_name: Chalupa
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Chalupa M, Henzinger TA. Bubaak: Runtime monitoring of program verifiers.
In: Tools and Algorithms for the Construction and Analysis of Systems.
Vol 13994. Springer Nature; 2023:535-540. doi:10.1007/978-3-031-30820-8_32'
apa: 'Chalupa, M., & Henzinger, T. A. (2023). Bubaak: Runtime monitoring of
program verifiers. In Tools and Algorithms for the Construction and Analysis
of Systems (Vol. 13994, pp. 535–540). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30820-8_32'
chicago: 'Chalupa, Marek, and Thomas A Henzinger. “Bubaak: Runtime Monitoring of
Program Verifiers.” In Tools and Algorithms for the Construction and Analysis
of Systems, 13994:535–40. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30820-8_32.'
ieee: 'M. Chalupa and T. A. Henzinger, “Bubaak: Runtime monitoring of program verifiers,”
in Tools and Algorithms for the Construction and Analysis of Systems, Paris,
France, 2023, vol. 13994, pp. 535–540.'
ista: 'Chalupa M, Henzinger TA. 2023. Bubaak: Runtime monitoring of program verifiers.
Tools and Algorithms for the Construction and Analysis of Systems. TACAS: Tools
and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13994,
535–540.'
mla: 'Chalupa, Marek, and Thomas A. Henzinger. “Bubaak: Runtime Monitoring of Program
Verifiers.” Tools and Algorithms for the Construction and Analysis of Systems,
vol. 13994, Springer Nature, 2023, pp. 535–40, doi:10.1007/978-3-031-30820-8_32.'
short: M. Chalupa, T.A. Henzinger, in:, Tools and Algorithms for the Construction
and Analysis of Systems, Springer Nature, 2023, pp. 535–540.
conference:
end_date: 2023-04-27
location: Paris, France
name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems'
start_date: 2023-04-22
date_created: 2023-04-20T08:22:53Z
date_published: 2023-04-20T00:00:00Z
date_updated: 2023-04-25T07:02:43Z
day: '20'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1007/978-3-031-30820-8_32
ec_funded: 1
file:
- access_level: open_access
checksum: 120d2c2a38384058ad0630fdf8288312
content_type: application/pdf
creator: dernst
date_created: 2023-04-25T06:58:36Z
date_updated: 2023-04-25T06:58:36Z
file_id: '12864'
file_name: 2023_LNCS_Chalupa.pdf
file_size: 16096413
relation: main_file
success: 1
file_date_updated: 2023-04-25T06:58:36Z
has_accepted_license: '1'
intvolume: ' 13994'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '04'
oa: 1
oa_version: Published Version
page: 535-540
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication: Tools and Algorithms for the Construction and Analysis of Systems
publication_identifier:
eisbn:
- '9783031308208'
eissn:
- 1611-3349
isbn:
- '9783031308192'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
status: public
title: 'Bubaak: Runtime monitoring of program verifiers'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13994
year: '2023'
...
---
_id: '12856'
abstract:
- lang: eng
text: "As the complexity and criticality of software increase every year, so does
the importance of run-time monitoring. Third-party monitoring, with limited knowledge
of the monitored software, and best-effort monitoring, which keeps pace with the
monitored software, are especially valuable, yet underexplored areas of run-time
monitoring. Most existing monitoring frameworks do not support their combination
because they either require access to the monitored code for instrumentation purposes
or the processing of all observed events, or both.\r\n\r\nWe present a middleware
framework, VAMOS, for the run-time monitoring of software which is explicitly
designed to support third-party and best-effort scenarios. The design goals of
VAMOS are (i) efficiency (keeping pace at low overhead), (ii) flexibility (the
ability to monitor black-box code through a variety of different event channels,
and the connectability to monitors written in different specification languages),
and (iii) ease-of-use. To achieve its goals, VAMOS combines aspects of event broker
and event recognition systems with aspects of stream processing systems.\r\nWe
implemented a prototype toolchain for VAMOS and conducted experiments including
a case study of monitoring for data races. The results indicate that VAMOS enables
writing useful yet efficient monitors, is compatible with a variety of event sources
and monitor specifications, and simplifies key aspects of setting up a monitoring
system from scratch."
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093. The
authors would like to thank the anonymous FASE reviewers for their valuable feedback
and suggestions.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Marek
full_name: Chalupa, Marek
id: 87e34708-d6c6-11ec-9f5b-9391e7be2463
last_name: Chalupa
- first_name: Fabian
full_name: Mühlböck, Fabian
id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425
last_name: Mühlböck
orcid: 0000-0003-1548-0177
- first_name: Stefanie
full_name: Muroya Lei, Stefanie
id: a376de31-8972-11ed-ae7b-d0251c13c8ff
last_name: Muroya Lei
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Chalupa M, Mühlböck F, Muroya Lei S, Henzinger TA. Vamos: Middleware for best-effort
third-party monitoring. In: Fundamental Approaches to Software Engineering.
Vol 13991. Springer Nature; 2023:260-281. doi:10.1007/978-3-031-30826-0_15'
apa: 'Chalupa, M., Mühlböck, F., Muroya Lei, S., & Henzinger, T. A. (2023).
Vamos: Middleware for best-effort third-party monitoring. In Fundamental Approaches
to Software Engineering (Vol. 13991, pp. 260–281). Paris, France: Springer
Nature. https://doi.org/10.1007/978-3-031-30826-0_15'
chicago: 'Chalupa, Marek, Fabian Mühlböck, Stefanie Muroya Lei, and Thomas A Henzinger.
“Vamos: Middleware for Best-Effort Third-Party Monitoring.” In Fundamental
Approaches to Software Engineering, 13991:260–81. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30826-0_15.'
ieee: 'M. Chalupa, F. Mühlböck, S. Muroya Lei, and T. A. Henzinger, “Vamos: Middleware
for best-effort third-party monitoring,” in Fundamental Approaches to Software
Engineering, Paris, France, 2023, vol. 13991, pp. 260–281.'
ista: 'Chalupa M, Mühlböck F, Muroya Lei S, Henzinger TA. 2023. Vamos: Middleware
for best-effort third-party monitoring. Fundamental Approaches to Software Engineering.
FASE: Fundamental Approaches to Software Engineering, LNCS, vol. 13991, 260–281.'
mla: 'Chalupa, Marek, et al. “Vamos: Middleware for Best-Effort Third-Party Monitoring.”
Fundamental Approaches to Software Engineering, vol. 13991, Springer Nature,
2023, pp. 260–81, doi:10.1007/978-3-031-30826-0_15.'
short: M. Chalupa, F. Mühlböck, S. Muroya Lei, T.A. Henzinger, in:, Fundamental
Approaches to Software Engineering, Springer Nature, 2023, pp. 260–281.
conference:
end_date: 2023-04-27
location: Paris, France
name: 'FASE: Fundamental Approaches to Software Engineering'
start_date: 2023-04-22
date_created: 2023-04-20T08:29:42Z
date_published: 2023-04-20T00:00:00Z
date_updated: 2023-04-25T07:19:07Z
day: '20'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1007/978-3-031-30826-0_15
ec_funded: 1
file:
- access_level: open_access
checksum: 17a7c8e08be609cf2408d37ea55e322c
content_type: application/pdf
creator: dernst
date_created: 2023-04-25T07:16:36Z
date_updated: 2023-04-25T07:16:36Z
file_id: '12865'
file_name: 2023_LNCS_ChalupaM.pdf
file_size: 580828
relation: main_file
success: 1
file_date_updated: 2023-04-25T07:16:36Z
has_accepted_license: '1'
intvolume: ' 13991'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 260-281
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication: Fundamental Approaches to Software Engineering
publication_identifier:
eisbn:
- '9783031308260'
eissn:
- 1611-3349
isbn:
- '9783031308253'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '12407'
relation: earlier_version
status: public
status: public
title: 'Vamos: Middleware for best-effort third-party monitoring'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13991
year: '2023'
...
---
_id: '12407'
abstract:
- lang: eng
text: "As the complexity and criticality of software increase every year, so does
the importance of run-time monitoring. Third-party monitoring, with limited knowledge
of the monitored software, and best-effort monitoring, which keeps pace with the
monitored software, are especially valuable, yet underexplored areas of run-time
monitoring. Most existing monitoring frameworks do not support their combination
because they either require access to the monitored code for instrumentation purposes
or the processing of all observed events, or both.\r\n\r\nWe present a middleware
framework, VAMOS, for the run-time monitoring of software which is explicitly
designed to support third-party and best-effort scenarios. The design goals of
VAMOS are (i) efficiency (keeping pace at low overhead), (ii) flexibility (the
ability to monitor black-box code through a variety of different event channels,
and the connectability to monitors written in different specification languages),
and (iii) ease-of-use. To achieve its goals, VAMOS combines aspects of event broker
and event recognition systems with aspects of stream processing systems.\r\n\r\nWe
implemented a prototype toolchain for VAMOS and conducted experiments including
a case study of monitoring for data races. The results indicate that VAMOS enables
writing useful yet efficient monitors, is compatible with a variety of event sources
and monitor specifications, and simplifies key aspects of setting up a monitoring
system from scratch."
acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093. \r\nThe
authors would like to thank the anonymous FASE reviewers for their valuable feedback
and suggestions."
alternative_title:
- IST Austria Technical Report
article_processing_charge: No
author:
- first_name: Marek
full_name: Chalupa, Marek
id: 87e34708-d6c6-11ec-9f5b-9391e7be2463
last_name: Chalupa
- first_name: Fabian
full_name: Mühlböck, Fabian
id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425
last_name: Mühlböck
orcid: 0000-0003-1548-0177
- first_name: Stefanie
full_name: Muroya Lei, Stefanie
id: a376de31-8972-11ed-ae7b-d0251c13c8ff
last_name: Muroya Lei
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Chalupa M, Mühlböck F, Muroya Lei S, Henzinger TA. VAMOS: Middleware for
Best-Effort Third-Party Monitoring. Institute of Science and Technology Austria;
2023. doi:10.15479/AT:ISTA:12407'
apa: 'Chalupa, M., Mühlböck, F., Muroya Lei, S., & Henzinger, T. A. (2023).
VAMOS: Middleware for Best-Effort Third-Party Monitoring. Institute of
Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:12407'
chicago: 'Chalupa, Marek, Fabian Mühlböck, Stefanie Muroya Lei, and Thomas A Henzinger.
VAMOS: Middleware for Best-Effort Third-Party Monitoring. Institute of
Science and Technology Austria, 2023. https://doi.org/10.15479/AT:ISTA:12407.'
ieee: 'M. Chalupa, F. Mühlböck, S. Muroya Lei, and T. A. Henzinger, VAMOS: Middleware
for Best-Effort Third-Party Monitoring. Institute of Science and Technology
Austria, 2023.'
ista: 'Chalupa M, Mühlböck F, Muroya Lei S, Henzinger TA. 2023. VAMOS: Middleware
for Best-Effort Third-Party Monitoring, Institute of Science and Technology Austria,
38p.'
mla: 'Chalupa, Marek, et al. VAMOS: Middleware for Best-Effort Third-Party Monitoring.
Institute of Science and Technology Austria, 2023, doi:10.15479/AT:ISTA:12407.'
short: 'M. Chalupa, F. Mühlböck, S. Muroya Lei, T.A. Henzinger, VAMOS: Middleware
for Best-Effort Third-Party Monitoring, Institute of Science and Technology Austria,
2023.'
date_created: 2023-01-27T03:18:08Z
date_published: 2023-01-27T00:00:00Z
date_updated: 2023-04-25T07:19:06Z
day: '27'
ddc:
- '005'
department:
- _id: ToHe
doi: 10.15479/AT:ISTA:12407
ec_funded: 1
file:
- access_level: open_access
checksum: 55426e463fdeafe9777fc3ff635154c7
content_type: application/pdf
creator: fmuehlbo
date_created: 2023-01-27T03:18:34Z
date_updated: 2023-01-27T03:18:34Z
file_id: '12408'
file_name: main.pdf
file_size: 662409
relation: main_file
success: 1
file_date_updated: 2023-01-27T03:18:34Z
has_accepted_license: '1'
keyword:
- runtime monitoring
- best effort
- third party
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: '38'
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication_identifier:
eissn:
- 2664-1690
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '12856'
relation: later_version
status: public
status: public
title: 'VAMOS: Middleware for Best-Effort Third-Party Monitoring'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: technical_report
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '13142'
abstract:
- lang: eng
text: Reinforcement learning has received much attention for learning controllers
of deterministic systems. We consider a learner-verifier framework for stochastic
control systems and survey recent methods that formally guarantee a conjunction
of reachability and safety properties. Given a property and a lower bound on the
probability of the property being satisfied, our framework jointly learns a control
policy and a formal certificate to ensure the satisfaction of the property with
a desired probability threshold. Both the control policy and the formal certificate
are continuous functions from states to reals, which are learned as parameterized
neural networks. While in the deterministic case, the certificates are invariant
and barrier functions for safety, or Lyapunov and ranking functions for liveness,
in the stochastic case the certificates are supermartingales. For certificate
verification, we use interval arithmetic abstract interpretation to bound the
expected values of neural network functions.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
citation:
ama: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. A learner-verifier framework
for neural network controllers and certificates of stochastic systems. In: Tools
and Algorithms for the Construction and Analysis of Systems . Vol 13993. Springer
Nature; 2023:3-25. doi:10.1007/978-3-031-30823-9_1'
apa: 'Chatterjee, K., Henzinger, T. A., Lechner, M., & Zikelic, D. (2023). A
learner-verifier framework for neural network controllers and certificates of
stochastic systems. In Tools and Algorithms for the Construction and Analysis
of Systems (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30823-9_1'
chicago: Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde
Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates
of Stochastic Systems.” In Tools and Algorithms for the Construction and Analysis
of Systems , 13993:3–25. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_1.
ieee: K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier
framework for neural network controllers and certificates of stochastic systems,”
in Tools and Algorithms for the Construction and Analysis of Systems ,
Paris, France, 2023, vol. 13993, pp. 3–25.
ista: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. A learner-verifier
framework for neural network controllers and certificates of stochastic systems.
Tools and Algorithms for the Construction and Analysis of Systems . TACAS: Tools
and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993,
3–25.'
mla: Chatterjee, Krishnendu, et al. “A Learner-Verifier Framework for Neural Network
Controllers and Certificates of Stochastic Systems.” Tools and Algorithms for
the Construction and Analysis of Systems , vol. 13993, Springer Nature, 2023,
pp. 3–25, doi:10.1007/978-3-031-30823-9_1.
short: K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms
for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25.
conference:
end_date: 2023-04-27
location: Paris, France
name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems'
start_date: 2023-04-22
date_created: 2023-06-18T22:00:47Z
date_published: 2023-04-22T00:00:00Z
date_updated: 2023-06-19T08:30:54Z
day: '22'
ddc:
- '000'
department:
- _id: KrCh
- _id: ToHe
doi: 10.1007/978-3-031-30823-9_1
ec_funded: 1
file:
- access_level: open_access
checksum: 3d8a8bb24d211bc83360dfc2fd744307
content_type: application/pdf
creator: dernst
date_created: 2023-06-19T08:29:30Z
date_updated: 2023-06-19T08:29:30Z
file_id: '13150'
file_name: 2023_LNCS_Chatterjee.pdf
file_size: 528455
relation: main_file
success: 1
file_date_updated: 2023-06-19T08:29:30Z
has_accepted_license: '1'
intvolume: ' 13993'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 3-25
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: 'Tools and Algorithms for the Construction and Analysis of Systems '
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031308222'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: A learner-verifier framework for neural network controllers and certificates
of stochastic systems
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13993
year: '2023'
...
---
_id: '13141'
abstract:
- lang: eng
text: "We automatically compute a new class of environment assumptions in two-player
turn-based finite graph games which characterize an “adequate cooperation” needed
from the environment to allow the system player to win. Given an ω-regular winning
condition Φ for the system player, we compute an ω-regular assumption Ψ for the
environment player, such that (i) every environment strategy compliant with Ψ
allows the system to fulfill Φ (sufficiency), (ii) Ψ\r\n can be fulfilled by the
environment for every strategy of the system (implementability), and (iii) Ψ does
not prevent any cooperative strategy choice (permissiveness).\r\nFor parity games,
which are canonical representations of ω-regular games, we present a polynomial-time
algorithm for the symbolic computation of adequately permissive assumptions and
show that our algorithm runs faster and produces better assumptions than existing
approaches—both theoretically and empirically. To the best of our knowledge, for
ω\r\n-regular games, we provide the first algorithm to compute sufficient and
implementable environment assumptions that are also permissive."
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Ashwani
full_name: Anand, Ashwani
last_name: Anand
- first_name: Kaushik
full_name: Mallik, Kaushik
id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598
last_name: Mallik
orcid: 0000-0001-9864-7475
- first_name: Satya Prakash
full_name: Nayak, Satya Prakash
last_name: Nayak
- first_name: Anne Kathrin
full_name: Schmuck, Anne Kathrin
last_name: Schmuck
citation:
ama: 'Anand A, Mallik K, Nayak SP, Schmuck AK. Computing adequately permissive assumptions
for synthesis. In: TACAS 2023: Tools and Algorithms for the Construction and
Analysis of Systems. Vol 13994. Springer Nature; 2023:211-228. doi:10.1007/978-3-031-30820-8_15'
apa: 'Anand, A., Mallik, K., Nayak, S. P., & Schmuck, A. K. (2023). Computing
adequately permissive assumptions for synthesis. In TACAS 2023: Tools and Algorithms
for the Construction and Analysis of Systems (Vol. 13994, pp. 211–228). Paris,
France: Springer Nature. https://doi.org/10.1007/978-3-031-30820-8_15'
chicago: 'Anand, Ashwani, Kaushik Mallik, Satya Prakash Nayak, and Anne Kathrin
Schmuck. “Computing Adequately Permissive Assumptions for Synthesis.” In TACAS
2023: Tools and Algorithms for the Construction and Analysis of Systems, 13994:211–28.
Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30820-8_15.'
ieee: 'A. Anand, K. Mallik, S. P. Nayak, and A. K. Schmuck, “Computing adequately
permissive assumptions for synthesis,” in TACAS 2023: Tools and Algorithms
for the Construction and Analysis of Systems, Paris, France, 2023, vol. 13994,
pp. 211–228.'
ista: 'Anand A, Mallik K, Nayak SP, Schmuck AK. 2023. Computing adequately permissive
assumptions for synthesis. TACAS 2023: Tools and Algorithms for the Construction
and Analysis of Systems. TACAS: Tools and Algorithms for the Construction and
Analysis of Systems, LNCS, vol. 13994, 211–228.'
mla: 'Anand, Ashwani, et al. “Computing Adequately Permissive Assumptions for Synthesis.”
TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems,
vol. 13994, Springer Nature, 2023, pp. 211–28, doi:10.1007/978-3-031-30820-8_15.'
short: 'A. Anand, K. Mallik, S.P. Nayak, A.K. Schmuck, in:, TACAS 2023: Tools and
Algorithms for the Construction and Analysis of Systems, Springer Nature, 2023,
pp. 211–228.'
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