--- _id: '10416' abstract: - lang: eng text: 'A fundamental algorithmic problem at the heart of static analysis is Dyck reachability. The input is a graph where the edges are labeled with different types of opening and closing parentheses, and the reachability information is computed via paths whose parentheses are properly matched. We present new results for Dyck reachability problems with applications to alias analysis and data-dependence analysis. Our main contributions, that include improved upper bounds as well as lower bounds that establish optimality guarantees, are as follows: First, we consider Dyck reachability on bidirected graphs, which is the standard way of performing field-sensitive points-to analysis. Given a bidirected graph with n nodes and m edges, we present: (i) an algorithm with worst-case running time O(m + n · α(n)), where α(n) is the inverse Ackermann function, improving the previously known O(n2) time bound; (ii) a matching lower bound that shows that our algorithm is optimal wrt to worst-case complexity; and (iii) an optimal average-case upper bound of O(m) time, improving the previously known O(m · logn) bound. Second, we consider the problem of context-sensitive data-dependence analysis, where the task is to obtain analysis summaries of library code in the presence of callbacks. Our algorithm preprocesses libraries in almost linear time, after which the contribution of the library in the complexity of the client analysis is only linear, and only wrt the number of call sites. Third, we prove that combinatorial algorithms for Dyck reachability on general graphs with truly sub-cubic bounds cannot be obtained without obtaining sub-cubic combinatorial algorithms for Boolean Matrix Multiplication, which is a long-standing open problem. Thus we establish that the existing combinatorial algorithms for Dyck reachability are (conditionally) optimal for general graphs. We also show that the same hardness holds for graphs of constant treewidth. Finally, we provide a prototype implementation of our algorithms for both alias analysis and data-dependence analysis. Our experimental evaluation demonstrates that the new algorithms significantly outperform all existing methods on the two problems, over real-world benchmarks.' acknowledgement: "The research was partly supported by Austrian Science Fund (FWF) Grant No P23499-N23, FWF NFN Grant No S11407-N23 (RiSE/SHiNE), and ERC Start grant (279307: Graph Games).\r\n" article_number: '30' article_processing_charge: No article_type: original author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Bhavya full_name: Choudhary, Bhavya last_name: Choudhary - first_name: Andreas full_name: Pavlogiannis, Andreas id: 49704004-F248-11E8-B48F-1D18A9856A87 last_name: Pavlogiannis orcid: 0000-0002-8943-0722 citation: ama: Chatterjee K, Choudhary B, Pavlogiannis A. Optimal Dyck reachability for data-dependence and Alias analysis. Proceedings of the ACM on Programming Languages. 2017;2(POPL). doi:10.1145/3158118 apa: 'Chatterjee, K., Choudhary, B., & Pavlogiannis, A. (2017). Optimal Dyck reachability for data-dependence and Alias analysis. Proceedings of the ACM on Programming Languages. Los Angeles, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3158118' chicago: Chatterjee, Krishnendu, Bhavya Choudhary, and Andreas Pavlogiannis. “Optimal Dyck Reachability for Data-Dependence and Alias Analysis.” Proceedings of the ACM on Programming Languages. Association for Computing Machinery, 2017. https://doi.org/10.1145/3158118. ieee: K. Chatterjee, B. Choudhary, and A. Pavlogiannis, “Optimal Dyck reachability for data-dependence and Alias analysis,” Proceedings of the ACM on Programming Languages, vol. 2, no. POPL. Association for Computing Machinery, 2017. ista: Chatterjee K, Choudhary B, Pavlogiannis A. 2017. Optimal Dyck reachability for data-dependence and Alias analysis. Proceedings of the ACM on Programming Languages. 2(POPL), 30. mla: Chatterjee, Krishnendu, et al. “Optimal Dyck Reachability for Data-Dependence and Alias Analysis.” Proceedings of the ACM on Programming Languages, vol. 2, no. POPL, 30, Association for Computing Machinery, 2017, doi:10.1145/3158118. short: K. Chatterjee, B. Choudhary, A. Pavlogiannis, Proceedings of the ACM on Programming Languages 2 (2017). conference: end_date: 2018-01-13 location: Los Angeles, CA, United States name: 'POPL: Programming Languages' start_date: 2018-01-07 date_created: 2021-12-05T23:01:48Z date_published: 2017-12-27T00:00:00Z date_updated: 2023-02-23T12:27:13Z day: '27' ddc: - '000' department: - _id: KrCh doi: 10.1145/3158118 ec_funded: 1 external_id: arxiv: - '1910.00241' file: - access_level: open_access checksum: faa3f7b3fe8aab84b50ed805c26a0ee5 content_type: application/pdf creator: cchlebak date_created: 2021-12-07T08:06:28Z date_updated: 2021-12-07T08:06:28Z file_id: '10421' file_name: 2017_ACMProgLang_Chatterjee.pdf file_size: 460188 relation: main_file success: 1 file_date_updated: 2021-12-07T08:06:28Z has_accepted_license: '1' intvolume: ' 2' issue: POPL language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 2581B60A-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '279307' name: 'Quantitative Graph Games: Theory and Applications' - _id: 2584A770-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 23499-N23 name: Modern Graph Algorithmic Techniques in Formal Verification - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering publication: Proceedings of the ACM on Programming Languages publication_identifier: eissn: - 2475-1421 publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' related_material: record: - id: '5455' relation: earlier_version status: public scopus_import: '1' status: public title: Optimal Dyck reachability for data-dependence and Alias analysis 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: journal_article user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 2 year: '2017' ... --- _id: '5455' abstract: - lang: eng text: 'A fundamental algorithmic problem at the heart of static analysis is Dyck reachability. The input is a graphwhere the edges are labeled with different types of opening and closing parentheses, and the reachabilityinformation is computed via paths whose parentheses are properly matched. We present new results for Dyckreachability problems with applications to alias analysis and data-dependence analysis. Our main contributions,that include improved upper bounds as well as lower bounds that establish optimality guarantees, are asfollows:First, we consider Dyck reachability on bidirected graphs, which is the standard way of performing field-sensitive points-to analysis. Given a bidirected graph withnnodes andmedges, we present: (i) an algorithmwith worst-case running timeO(m+n·α(n)), whereα(n)is the inverse Ackermann function, improving thepreviously knownO(n2)time bound; (ii) a matching lower bound that shows that our algorithm is optimalwrt to worst-case complexity; and (iii) an optimal average-case upper bound ofO(m)time, improving thepreviously knownO(m·logn)bound.Second, we consider the problem of context-sensitive data-dependence analysis, where the task is to obtainanalysis summaries of library code in the presence of callbacks. Our algorithm preprocesses libraries in almostlinear time, after which the contribution of the library in the complexity of the client analysis is only linear,and only wrt the number of call sites.Third, we prove that combinatorial algorithms for Dyck reachability on general graphs with truly sub-cubic bounds cannot be obtained without obtaining sub-cubic combinatorial algorithms for Boolean MatrixMultiplication, which is a long-standing open problem. Thus we establish that the existing combinatorialalgorithms for Dyck reachability are (conditionally) optimal for general graphs. We also show that the samehardness holds for graphs of constant treewidth.Finally, we provide a prototype implementation of our algorithms for both alias analysis and data-dependenceanalysis. Our experimental evaluation demonstrates that the new algorithms significantly outperform allexisting methods on the two problems, over real-world benchmarks.' alternative_title: - IST Austria Technical Report 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: Bhavya full_name: Choudhary, Bhavya last_name: Choudhary - first_name: Andreas full_name: Pavlogiannis, Andreas id: 49704004-F248-11E8-B48F-1D18A9856A87 last_name: Pavlogiannis orcid: 0000-0002-8943-0722 citation: ama: Chatterjee K, Choudhary B, Pavlogiannis A. Optimal Dyck Reachability for Data-Dependence and Alias Analysis. IST Austria; 2017. doi:10.15479/AT:IST-2017-870-v1-1 apa: Chatterjee, K., Choudhary, B., & Pavlogiannis, A. (2017). Optimal Dyck reachability for data-dependence and alias analysis. IST Austria. https://doi.org/10.15479/AT:IST-2017-870-v1-1 chicago: Chatterjee, Krishnendu, Bhavya Choudhary, and Andreas Pavlogiannis. Optimal Dyck Reachability for Data-Dependence and Alias Analysis. IST Austria, 2017. https://doi.org/10.15479/AT:IST-2017-870-v1-1. ieee: K. Chatterjee, B. Choudhary, and A. Pavlogiannis, Optimal Dyck reachability for data-dependence and alias analysis. IST Austria, 2017. ista: Chatterjee K, Choudhary B, Pavlogiannis A. 2017. Optimal Dyck reachability for data-dependence and alias analysis, IST Austria, 37p. mla: Chatterjee, Krishnendu, et al. Optimal Dyck Reachability for Data-Dependence and Alias Analysis. IST Austria, 2017, doi:10.15479/AT:IST-2017-870-v1-1. short: K. Chatterjee, B. Choudhary, A. Pavlogiannis, Optimal Dyck Reachability for Data-Dependence and Alias Analysis, IST Austria, 2017. date_created: 2018-12-12T11:39:26Z date_published: 2017-10-23T00:00:00Z date_updated: 2023-02-21T15:54:10Z day: '23' ddc: - '000' department: - _id: KrCh doi: 10.15479/AT:IST-2017-870-v1-1 file: - access_level: open_access checksum: 177a84a46e3ac17e87b31534ad16a4c9 content_type: application/pdf creator: system date_created: 2018-12-12T11:54:02Z date_updated: 2020-07-14T12:46:59Z file_id: '5524' file_name: IST-2017-870-v1+1_main.pdf file_size: 960491 relation: main_file file_date_updated: 2020-07-14T12:46:59Z has_accepted_license: '1' language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: '37' publication_identifier: issn: - 2664-1690 publication_status: published publisher: IST Austria pubrep_id: '870' related_material: record: - id: '10416' relation: later_version status: public status: public title: Optimal Dyck reachability for data-dependence and alias analysis type: technical_report user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2017' ... --- _id: '10417' abstract: - lang: eng text: "We present a new dynamic partial-order reduction method for stateless model checking of concurrent programs. A common approach for exploring program behaviors relies on enumerating the traces of the program, without storing the visited states (aka stateless exploration). As the number of distinct traces grows exponentially, dynamic partial-order reduction (DPOR) techniques have been successfully used to partition the space of traces into equivalence classes (Mazurkiewicz partitioning), with the goal of exploring only few representative traces from each class.\r\n\r\nWe introduce a new equivalence on traces under sequential consistency semantics, which we call the observation equivalence. Two traces are observationally equivalent if every read event observes the same write event in both traces. While the traditional Mazurkiewicz equivalence is control-centric, our new definition is data-centric. We show that our observation equivalence is coarser than the Mazurkiewicz equivalence, and in many cases even exponentially coarser. We devise a DPOR exploration of the trace space, called data-centric DPOR, based on the observation equivalence." acknowledgement: "The research was partly supported by Austrian Science Fund (FWF) Grant No P23499- N23, FWF\r\nNFN Grant No S11407-N23 (RiSE/SHiNE), ERC Start grant (279307: Graph Games), and Czech\r\nScience Foundation grant GBP202/12/G061." article_number: '31' article_processing_charge: No article_type: original author: - first_name: Marek full_name: Chalupa, Marek last_name: Chalupa - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Andreas full_name: Pavlogiannis, Andreas id: 49704004-F248-11E8-B48F-1D18A9856A87 last_name: Pavlogiannis orcid: 0000-0002-8943-0722 - first_name: Nishant full_name: Sinha, Nishant last_name: Sinha - first_name: Kapil full_name: Vaidya, Kapil last_name: Vaidya citation: ama: Chalupa M, Chatterjee K, Pavlogiannis A, Sinha N, Vaidya K. Data-centric dynamic partial order reduction. Proceedings of the ACM on Programming Languages. 2017;2(POPL). doi:10.1145/3158119 apa: 'Chalupa, M., Chatterjee, K., Pavlogiannis, A., Sinha, N., & Vaidya, K. (2017). Data-centric dynamic partial order reduction. Proceedings of the ACM on Programming Languages. Los Angeles, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3158119' chicago: Chalupa, Marek, Krishnendu Chatterjee, Andreas Pavlogiannis, Nishant Sinha, and Kapil Vaidya. “Data-Centric Dynamic Partial Order Reduction.” Proceedings of the ACM on Programming Languages. Association for Computing Machinery, 2017. https://doi.org/10.1145/3158119. ieee: M. Chalupa, K. Chatterjee, A. Pavlogiannis, N. Sinha, and K. Vaidya, “Data-centric dynamic partial order reduction,” Proceedings of the ACM on Programming Languages, vol. 2, no. POPL. Association for Computing Machinery, 2017. ista: Chalupa M, Chatterjee K, Pavlogiannis A, Sinha N, Vaidya K. 2017. Data-centric dynamic partial order reduction. Proceedings of the ACM on Programming Languages. 2(POPL), 31. mla: Chalupa, Marek, et al. “Data-Centric Dynamic Partial Order Reduction.” Proceedings of the ACM on Programming Languages, vol. 2, no. POPL, 31, Association for Computing Machinery, 2017, doi:10.1145/3158119. short: M. Chalupa, K. Chatterjee, A. Pavlogiannis, N. Sinha, K. Vaidya, Proceedings of the ACM on Programming Languages 2 (2017). conference: end_date: 2018-01-13 location: Los Angeles, CA, United States name: 'POPL: Programming Languages' start_date: 2018-01-07 date_created: 2021-12-05T23:01:49Z date_published: 2017-12-27T00:00:00Z date_updated: 2023-02-23T12:27:16Z day: '27' department: - _id: KrCh doi: 10.1145/3158119 ec_funded: 1 external_id: arxiv: - '1610.01188' intvolume: ' 2' issue: POPL language: - iso: eng main_file_link: - open_access: '1' url: https://dl.acm.org/doi/10.1145/3158119 month: '12' oa: 1 oa_version: Published Version project: - _id: 2584A770-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 23499-N23 name: Modern Graph Algorithmic Techniques in Formal Verification - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering - _id: 2581B60A-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '279307' name: 'Quantitative Graph Games: Theory and Applications' publication: Proceedings of the ACM on Programming Languages publication_identifier: eissn: - 2475-1421 publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' related_material: record: - id: '5448' relation: earlier_version status: public - id: '5456' relation: earlier_version status: public scopus_import: '1' status: public title: Data-centric dynamic partial order reduction type: journal_article user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 2 year: '2017' ... --- _id: '5456' abstract: - lang: eng text: "We present a new dynamic partial-order reduction method for stateless model checking of concurrent programs. A common approach for exploring program behaviors relies on enumerating the traces of the program, without storing the visited states (aka stateless exploration). As the number of distinct traces grows exponentially, dynamic partial-order reduction (DPOR) techniques have been successfully used to partition the space of traces into equivalence classes (Mazurkiewicz partitioning), with the goal of exploring only few representative traces from each class.\r\nWe introduce a new equivalence on traces under sequential consistency semantics, which we call the observation equivalence. Two traces are observationally equivalent if every read event observes the same write event in both traces. While the traditional Mazurkiewicz equivalence is control-centric, our new definition is data-centric. We show that our observation equivalence is coarser than the Mazurkiewicz equivalence, and in many cases even exponentially coarser. We devise a DPOR exploration of the trace space, called data-centric DPOR, based on the observation equivalence.\r\n1. For acyclic architectures, our algorithm is guaranteed to explore exactly one representative trace from each observation class, while spending polynomial time per class. Hence, our algorithm is optimal wrt the observation equivalence, and in several cases explores exponentially fewer traces than any enumerative method based on the Mazurkiewicz equivalence.\r\n2. For cyclic architectures, we consider an equivalence between traces which is finer than the observation equivalence; but coarser than the Mazurkiewicz equivalence, and in some cases is exponentially coarser. Our data-centric DPOR algorithm remains optimal under this trace equivalence. \r\nFinally, we perform a basic experimental comparison between the existing Mazurkiewicz-based DPOR and our data-centric DPOR on a set of academic benchmarks. Our results show a significant reduction in both running time and the number of explored equivalence classes." alternative_title: - IST Austria Technical Report author: - first_name: Marek full_name: Chalupa, Marek last_name: Chalupa - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Andreas full_name: Pavlogiannis, Andreas id: 49704004-F248-11E8-B48F-1D18A9856A87 last_name: Pavlogiannis orcid: 0000-0002-8943-0722 - first_name: Nishant full_name: Sinha, Nishant last_name: Sinha - first_name: Kapil full_name: Vaidya, Kapil last_name: Vaidya citation: ama: Chalupa M, Chatterjee K, Pavlogiannis A, Sinha N, Vaidya K. Data-Centric Dynamic Partial Order Reduction. IST Austria; 2017. doi:10.15479/AT:IST-2017-872-v1-1 apa: Chalupa, M., Chatterjee, K., Pavlogiannis, A., Sinha, N., & Vaidya, K. (2017). Data-centric dynamic partial order reduction. IST Austria. https://doi.org/10.15479/AT:IST-2017-872-v1-1 chicago: Chalupa, Marek, Krishnendu Chatterjee, Andreas Pavlogiannis, Nishant Sinha, and Kapil Vaidya. Data-Centric Dynamic Partial Order Reduction. IST Austria, 2017. https://doi.org/10.15479/AT:IST-2017-872-v1-1. ieee: M. Chalupa, K. Chatterjee, A. Pavlogiannis, N. Sinha, and K. Vaidya, Data-centric dynamic partial order reduction. IST Austria, 2017. ista: Chalupa M, Chatterjee K, Pavlogiannis A, Sinha N, Vaidya K. 2017. Data-centric dynamic partial order reduction, IST Austria, 36p. mla: Chalupa, Marek, et al. Data-Centric Dynamic Partial Order Reduction. IST Austria, 2017, doi:10.15479/AT:IST-2017-872-v1-1. short: M. Chalupa, K. Chatterjee, A. Pavlogiannis, N. Sinha, K. Vaidya, Data-Centric Dynamic Partial Order Reduction, IST Austria, 2017. date_created: 2018-12-12T11:39:26Z date_published: 2017-10-23T00:00:00Z date_updated: 2023-02-23T12:26:54Z day: '23' ddc: - '000' department: - _id: KrCh doi: 10.15479/AT:IST-2017-872-v1-1 file: - access_level: open_access checksum: d2635c4cf013000f0a1b09e80f9e4ab7 content_type: application/pdf creator: system date_created: 2018-12-12T11:53:26Z date_updated: 2020-07-14T12:46:59Z file_id: '5487' file_name: IST-2017-872-v1+1_main.pdf file_size: 910347 relation: main_file file_date_updated: 2020-07-14T12:46:59Z has_accepted_license: '1' language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: '36' publication_identifier: issn: - 2664-1690 publication_status: published publisher: IST Austria pubrep_id: '872' related_material: record: - id: '10417' relation: later_version status: public - id: '5448' relation: earlier_version status: public status: public title: Data-centric dynamic partial order reduction type: technical_report user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2017' ... --- _id: '551' abstract: - lang: eng text: 'Evolutionary graph theory studies the evolutionary dynamics in a population structure given as a connected graph. Each node of the graph represents an individual of the population, and edges determine how offspring are placed. We consider the classical birth-death Moran process where there are two types of individuals, namely, the residents with fitness 1 and mutants with fitness r. The fitness indicates the reproductive strength. The evolutionary dynamics happens as follows: in the initial step, in a population of all resident individuals a mutant is introduced, and then at each step, an individual is chosen proportional to the fitness of its type to reproduce, and the offspring replaces a neighbor uniformly at random. The process stops when all individuals are either residents or mutants. The probability that all individuals in the end are mutants is called the fixation probability, which is a key factor in the rate of evolution. We consider the problem of approximating the fixation probability. The class of algorithms that is extremely relevant for approximation of the fixation probabilities is the Monte-Carlo simulation of the process. Previous results present a polynomial-time Monte-Carlo algorithm for undirected graphs when r is given in unary. First, we present a simple modification: instead of simulating each step, we discard ineffective steps, where no node changes type (i.e., either residents replace residents, or mutants replace mutants). Using the above simple modification and our result that the number of effective steps is concentrated around the expected number of effective steps, we present faster polynomial-time Monte-Carlo algorithms for undirected graphs. Our algorithms are always at least a factor O(n2/ log n) faster as compared to the previous algorithms, where n is the number of nodes, and is polynomial even if r is given in binary. We also present lower bounds showing that the upper bound on the expected number of effective steps we present is asymptotically tight for undirected graphs. ' alternative_title: - LIPIcs article_number: '61' author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Rasmus full_name: Ibsen-Jensen, Rasmus id: 3B699956-F248-11E8-B48F-1D18A9856A87 last_name: Ibsen-Jensen orcid: 0000-0003-4783-0389 - first_name: Martin full_name: Nowak, Martin last_name: Nowak citation: ama: 'Chatterjee K, Ibsen-Jensen R, Nowak M. Faster Monte Carlo algorithms for fixation probability of the Moran process on undirected graphs. In: Leibniz International Proceedings in Informatics. Vol 83. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2017. doi:10.4230/LIPIcs.MFCS.2017.61' apa: 'Chatterjee, K., Ibsen-Jensen, R., & Nowak, M. (2017). Faster Monte Carlo algorithms for fixation probability of the Moran process on undirected graphs. In Leibniz International Proceedings in Informatics (Vol. 83). Aalborg, Denmark: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.MFCS.2017.61' chicago: Chatterjee, Krishnendu, Rasmus Ibsen-Jensen, and Martin Nowak. “Faster Monte Carlo Algorithms for Fixation Probability of the Moran Process on Undirected Graphs.” In Leibniz International Proceedings in Informatics, Vol. 83. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2017. https://doi.org/10.4230/LIPIcs.MFCS.2017.61. ieee: K. Chatterjee, R. Ibsen-Jensen, and M. Nowak, “Faster Monte Carlo algorithms for fixation probability of the Moran process on undirected graphs,” in Leibniz International Proceedings in Informatics, Aalborg, Denmark, 2017, vol. 83. ista: 'Chatterjee K, Ibsen-Jensen R, Nowak M. 2017. Faster Monte Carlo algorithms for fixation probability of the Moran process on undirected graphs. Leibniz International Proceedings in Informatics. MFCS: Mathematical Foundations of Computer Science (SG), LIPIcs, vol. 83, 61.' mla: Chatterjee, Krishnendu, et al. “Faster Monte Carlo Algorithms for Fixation Probability of the Moran Process on Undirected Graphs.” Leibniz International Proceedings in Informatics, vol. 83, 61, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2017, doi:10.4230/LIPIcs.MFCS.2017.61. short: K. Chatterjee, R. Ibsen-Jensen, M. Nowak, in:, Leibniz International Proceedings in Informatics, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2017. conference: end_date: 2017-08-25 location: Aalborg, Denmark name: 'MFCS: Mathematical Foundations of Computer Science (SG)' start_date: 2017-08-21 date_created: 2018-12-11T11:47:08Z date_published: 2017-11-01T00:00:00Z date_updated: 2021-01-12T08:02:34Z day: '01' ddc: - '004' department: - _id: KrCh doi: 10.4230/LIPIcs.MFCS.2017.61 file: - access_level: open_access checksum: 2eed5224c0e4e259484a1d71acb8ba6a content_type: application/pdf creator: system date_created: 2018-12-12T10:18:04Z date_updated: 2020-07-14T12:47:00Z file_id: '5322' file_name: IST-2018-924-v1+1_LIPIcs-MFCS-2017-61.pdf file_size: 535077 relation: main_file file_date_updated: 2020-07-14T12:47:00Z has_accepted_license: '1' intvolume: ' 83' language: - iso: eng month: '11' oa: 1 oa_version: Published Version publication: Leibniz International Proceedings in Informatics publication_identifier: isbn: - 978-395977046-0 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik publist_id: '7263' pubrep_id: '924' quality_controlled: '1' scopus_import: 1 status: public title: Faster Monte Carlo algorithms for fixation probability of the Moran process on undirected graphs 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: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 83 year: '2017' ...