30 citations · 111 across the 17 of their papers we have counts for
21 papers
Characterizing LTL Formulas by Examples (full version)
Balder ten Cate, Dana Fisman, Roi Ohayon +1
We investigate the extent to which Linear Temporal Logic (LTL) formulas can be uniquely characterized by a finite set of labeled examples. We consider different types of examples,…
Learning Broadcast Protocols
Dana Fisman, Noa Izsak, Swen Jacobs
The problem of learning a computational model from examples has been receiving growing attention. For the particularly challenging problem of learning models of distributed systems…
Constructing Concise Characteristic Samples for Acceptors of Omega Regular Languages
Dana Angluin, Dana Fisman
A characteristic sample for a language and a learning algorithm is a finite sample of words labeled by their membership in such that for any sample $T \s…
Learning of Structurally Unambiguous Probabilistic Grammars
Dana Fisman, Dolav Nitay, Michal Ziv-Ukelson
The problem of identifying a probabilistic context free grammar has two aspects: the first is determining the grammar's topology (the rules of the grammar) and the second is estima…
The Normalized Edit Distance with Uniform Operation Costs is a Metric
Dana Fisman, Joshua Grogin, Oded Margalit +1
We prove that the normalized edit distance proposed in [Marzal and Vidal 1993] is a metric when the cost of all the edit operations are the same. This closes a long standing gap in…
Inferring Symbolic Automata
Dana Fisman, Hadar Frenkel, Sandra Zilles
We study the learnability of symbolic finite state automata (SFA), a model shown useful in many applications in software verification. The state-of-the-art literature on this topic…
Safety Synthesis Sans Specification
Roderick Bloem, Hana Chockler, Masoud Ebrahimi +2
We define the problem of learning a transducer from a target language containing possibly conflicting transducers, using membership queries and conjecture queries. The re…
Learning of Structurally Unambiguous Probabilistic Grammars
Dolav Nitay, Dana Fisman, Michal Ziv-Ukelson
The problem of identifying a probabilistic context free grammar has two aspects: the first is determining the grammar's topology (the rules of the grammar) and the second is estima…
On the Complexity of Symbolic Finite-State Automata
Dana Fisman, Hadar Frenkel, Sandra Zilles
We revisit the complexity of procedures on SFAs (such as intersection, emptiness, etc.) and analyze them according to the measures we find suitable for symbolic automata: the numbe…
Learning Interpretable Models in the Property Specification Language
Rajarshi Roy, Dana Fisman, Daniel Neider
We address the problem of learning human-interpretable descriptions of a complex system from a finite set of positive and negative examples of its behavior. In contrast to most of…
Polynomial time algorithms for inclusion and equivalence of deterministic omega acceptors
Dana Angluin, Dana Fisman
The class of omega languages recognized by deterministic parity acceptors (DPAs) or deterministic Muller acceptors (DMAs) is exactly the regular omega languages. The inclusion prob…
SyGuS-Comp 2018: Results and Analysis
Rajeev Alur, Dana Fisman, Saswat Padhi +2
Syntax-guided synthesis (SyGuS) is the computational problem of finding an implementation that meets both a semantic constraint given by a logical formula in a background t…
Regular omega-Languages with an Informative Right Congruence
Dana Angluin, Dana Fisman
A regular language is almost fully characterized by its right congruence relation. Indeed, a regular language can always be recognized by a DFA isomorphic to the automaton correspo…
Streamable Regular Transductions
Rajeev Alur, Dana Fisman, Konstantinos Mamouras +2
Motivated by real-time monitoring and data processing applications, we develop a formal theory of quantitative queries for streaming data that can be evaluated efficiently. We cons…
Query learning of derived -tree languages in polynomial time
Dana Angluin, Timos Antonopoulos, Dana Fisman
We present the first polynomial time algorithm to learn nontrivial classes of languages of infinite trees. Specifically, our algorithm uses membership and equivalence queries to le…
SyGuS-Comp 2017: Results and Analysis
Rajeev Alur, Dana Fisman, Rishabh Singh +1
Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an implementation f that meets both a semantic constraint given by a logical formula phi in a background the…
Proceedings Sixth Workshop on Synthesis
Dana Fisman, Swen Jacobs
The SYNT workshop aims to bring together researchers interested in the broad area of synthesis of computing systems. The goal is to foster the development of frontier techniques in…
Families of DFAs as Acceptors of -Regular Languages
Dana Angluin, Udi Boker, Dana Fisman
Families of DFAs (FDFAs) provide an alternative formalism for recognizing -regular languages. The motivation for introducing them was a desired correlation between the automaton…
SyGuS-Comp 2016: Results and Analysis
Rajeev Alur, Dana Fisman, Rishabh Singh +1
Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an implementation f that meets both a semantic constraint given by a logical formula in a background the…
Results and Analysis of SyGuS-Comp'15
Rajeev Alur, Dana Fisman, Rishabh Singh +1
Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an implementation f that meets both a semantic constraint given by a logical formula in a background the…
Rational Synthesis
Dana Fisman, Orna Kupferman, Yoad Lustig
Synthesis is the automated construction of a system from its specification. The system has to satisfy its specification in all possible environments. Modern systems often interact…