--- _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.' 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: 2023-04-20T00:00:00Z date_updated: 2023-06-19T08:49:46Z day: '20' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-031-30820-8_15 file: - access_level: open_access checksum: 60dcafc1b4f6f070be43bad3fe877974 content_type: application/pdf creator: dernst date_created: 2023-06-19T08:43:21Z date_updated: 2023-06-19T08:43:21Z file_id: '13151' file_name: 2023_LNCS_Anand.pdf file_size: 521425 relation: main_file success: 1 file_date_updated: 2023-06-19T08:43:21Z has_accepted_license: '1' intvolume: ' 13994' language: - iso: eng month: '04' oa: 1 oa_version: Published Version page: 211-228 publication: 'TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems' publication_identifier: eissn: - 1611-3349 isbn: - '9783031308192' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Computing adequately permissive assumptions for synthesis 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' ...