@misc{5402,
abstract = {Linearizability requires that the outcome of calls by competing threads to a concurrent data structure is the same as some sequential execution where each thread has exclusive access to the data structure. In an ordered data structure, such as a queue or a stack, linearizability is ensured by requiring threads commit in the order dictated by the sequential semantics of the data structure; e.g., in a concurrent queue implementation a dequeue can only remove the oldest element.
In this paper, we investigate the impact of this strict ordering, by comparing what linearizability allows to what existing implementations do. We first give an operational definition for linearizability which allows us to build the most general linearizable implementation as a transition system for any given sequential specification. We then use this operational definition to categorize linearizable implementations based on whether they are bound or free. In a bound implementation, whenever all threads observe the same logical state, the updates to the logical state and the temporal order of commits coincide. All existing queue implementations we know of are bound. We then proceed to present, to the best of our knowledge, the first ever free queue implementation. Our experiments show that free implementations have the potential for better performance by suffering less from contention.},
author = {Henzinger, Thomas A and Sezgin, Ali},
issn = {2664-1690},
pages = {16},
publisher = {IST Austria},
title = {{How free is your linearizable concurrent data structure?}},
doi = {10.15479/AT:IST-2013-123-v1-1},
year = {2013},
}
@misc{5403,
abstract = {We consider concurrent games played by two-players on a finite state graph, where in every round the players simultaneously choose a move, and the current state along with the joint moves determine the successor state. We study the most fundamental objective for concurrent games, namely, mean-payoff or limit-average objective, where a reward is associated to every transition, and the goal of player 1 is to maximize the long-run average of the rewards, and the objective of player 2 is strictly the opposite (i.e., the games are zero-sum). The path constraint for player 1 could be qualitative, i.e., the mean-payoff is the maximal reward, or arbitrarily close to it; or quantitative, i.e., a given threshold between the minimal and maximal reward. We consider the computation of the almost-sure (resp. positive) winning sets, where player 1 can ensure that the path constraint is satisfied with probability 1 (resp. positive probability). Almost-sure winning with qualitative constraint exactly corresponds to the question whether there exists a strategy to ensure that the payoff is the maximal reward of the game. Our main results for qualitative path constraints are as follows: (1) we establish qualitative determinacy results that show for every state either player 1 has a strategy to ensure almost-sure (resp. positive) winning against all player-2 strategies or player 2 has a spoiling strategy to falsify almost-sure (resp. positive) winning against all player-1 strategies; (2) we present optimal strategy complexity results that precisely characterize the classes of strategies required for almost-sure and positive winning for both players; and (3) we present quadratic time algorithms to compute the almost-sure and the positive winning sets, matching the best known bound of the algorithms for much simpler problems (such as reachability objectives). For quantitative constraints we show that a polynomial time solution for the almost-sure or the positive winning set would imply a solution to a long-standing open problem (of solving the value problem of mean-payoff games) that is not known to be in polynomial time.},
author = {Chatterjee, Krishnendu and Ibsen-Jensen, Rasmus},
issn = {2664-1690},
pages = {33},
publisher = {IST Austria},
title = {{Qualitative analysis of concurrent mean-payoff games}},
doi = {10.15479/AT:IST-2013-126-v1-1},
year = {2013},
}
@misc{5404,
abstract = {We study finite-state two-player (zero-sum) concurrent mean-payoff games played on a graph. We focus on the important sub-class of ergodic games where all states are visited infinitely often with probability 1. The algorithmic study of ergodic games was initiated in a seminal work of Hoffman and Karp in 1966, but all basic complexity questions have remained unresolved. Our main results for ergodic games are as follows: We establish (1) an optimal exponential bound on the patience of stationary strategies (where patience of a distribution is the inverse of the smallest positive probability and represents a complexity measure of a stationary strategy); (2) the approximation problem lie in FNP; (3) the approximation problem is at least as hard as the decision problem for simple stochastic games (for which NP and coNP is the long-standing best known bound). We show that the exact value can be expressed in the existential theory of the reals, and also establish square-root sum hardness for a related class of games.},
author = {Chatterjee, Krishnendu and Ibsen-Jensen, Rasmus},
issn = {2664-1690},
pages = {29},
publisher = {IST Austria},
title = {{The complexity of ergodic games}},
doi = {10.15479/AT:IST-2013-127-v1-1},
year = {2013},
}
@misc{5405,
abstract = {The theory of graph games is the foundation for modeling and synthesizing reactive processes. In the synthesis of stochastic processes, we use 2-1/2-player games where some transitions of the game graph are controlled by two adversarial players, the System and the Environment, and the other transitions are determined probabilistically. We consider 2-1/2-player games where the objective of the System is the conjunction of a qualitative objective (specified as a parity condition) and a quantitative objective (specified as a mean-payoff condition). We establish that the problem of deciding whether the System can ensure that the probability to satisfy the mean-payoff parity objective is at least a given threshold is in NP ∩ coNP, matching the best known bound in the special case of 2-player games (where all transitions are deterministic) with only parity objectives, or with only mean-payoff objectives. We present an algorithm running
in time O(d · n^{2d}·MeanGame) to compute the set of almost-sure winning states from which the objective
can be ensured with probability 1, where n is the number of states of the game, d the number of priorities
of the parity objective, and MeanGame is the complexity to compute the set of almost-sure winning states
in 2-1/2-player mean-payoff games. Our results are useful in the synthesis of stochastic reactive systems
with both functional requirement (given as a qualitative objective) and performance requirement (given
as a quantitative objective).},
author = {Chatterjee, Krishnendu and Doyen, Laurent and Gimbert, Hugo and Oualhadj, Youssouf},
issn = {2664-1690},
pages = {22},
publisher = {IST Austria},
title = {{Perfect-information stochastic mean-payoff parity games}},
doi = {10.15479/AT:IST-2013-128-v1-1},
year = {2013},
}
@misc{5406,
abstract = {We consider the distributed synthesis problem fortemporal logic specifications. Traditionally, the problem has been studied for LTL, and the previous results show that the problem is decidable iff there is no information fork in the architecture. We consider the problem for fragments of LTLand our main results are as follows: (1) We show that the problem is undecidable for architectures with information forks even for the fragment of LTL with temporal operators restricted to next and eventually. (2) For specifications restricted to globally along with non-nested next operators, we establish decidability (in EXPSPACE) for star architectures where the processes receive disjoint inputs, whereas we establish undecidability for architectures containing an information fork-meet structure. (3)Finally, we consider LTL without the next operator, and establish decidability (NEXPTIME-complete) for all architectures for a fragment that consists of a set of safety assumptions, and a set of guarantees where each guarantee is a safety, reachability, or liveness condition.},
author = {Chatterjee, Krishnendu and Henzinger, Thomas A and Otop, Jan and Pavlogiannis, Andreas},
issn = {2664-1690},
pages = {11},
publisher = {IST Austria},
title = {{Distributed synthesis for LTL Fragments}},
doi = {10.15479/AT:IST-2013-130-v1-1},
year = {2013},
}
@techreport{5407,
abstract = {This document is created as a part of the project “Repository for Research Data at IST Austria”. It summarises the mandatory features, which need to be fulfilled to provide an institutional repository as a platform and also a service to the scientists at the institute. It also includes optional features, which would be of strong benefit for the scientists and would increase the usage of the repository, and hence the visibility of research at IST Austria.},
author = {Porsche, Jana},
publisher = {IST Austria},
title = {{Technical requirements and features}},
year = {2013},
}
@misc{5408,
abstract = {We consider two-player partial-observation stochastic games where player 1 has partial observation and player 2 has perfect observation. The winning condition we study are omega-regular conditions specified as parity objectives. The qualitative analysis problem given a partial-observation stochastic game and a parity objective asks whether there is a strategy to ensure that the objective is satisfied with probability 1 (resp. positive probability). While the qualitative analysis problems are known to be undecidable even for very special cases of parity objectives, they were shown to be decidable in 2EXPTIME under finite-memory strategies. We improve the complexity and show that the qualitative analysis problems for partial-observation stochastic parity games under finite-memory strategies are
EXPTIME-complete; and also establish optimal (exponential) memory bounds for finite-memory strategies required for qualitative analysis. },
author = {Chatterjee, Krishnendu and Doyen, Laurent and Nain, Sumit and Vardi, Moshe},
issn = {2664-1690},
pages = {17},
publisher = {IST Austria},
title = {{The complexity of partial-observation stochastic parity games with finite-memory strategies}},
doi = {10.15479/AT:IST-2013-141-v1-1},
year = {2013},
}
@misc{5409,
abstract = {The edit distance between two (untimed) traces is the minimum cost of a sequence of edit operations (insertion, deletion, or substitution) needed to transform one trace to the other. Edit distances have been extensively studied in the untimed setting, and form the basis for approximate matching of sequences in different domains such as coding theory, parsing, and speech recognition.
In this paper, we lift the study of edit distances from untimed languages to the timed setting. We define an edit distance between timed words which incorporates both the edit distance between the untimed words and the absolute difference in timestamps. Our edit distance between two timed words is computable in polynomial time. Further, we show that the edit distance between a timed word and a timed language generated by a timed automaton, defined as the edit distance between the word and the closest word in the language, is PSPACE-complete. While computing the edit distance between two timed automata is undecidable, we show that the approximate version, where we decide if the edit distance between two timed automata is either less than a given parameter or more than delta away from the parameter, for delta>0, can be solved in exponential space and is EXPSPACE-hard. Our definitions and techniques can be generalized to the setting of hybrid systems, and we show analogous decidability results for rectangular automata.},
author = {Chatterjee, Krishnendu and Ibsen-Jensen, Rasmus and Majumdar, Rupak},
issn = {2664-1690},
pages = {12},
publisher = {IST Austria},
title = {{Edit distance for timed automata}},
doi = {10.15479/AT:IST-2013-144-v1-1},
year = {2013},
}
@misc{5410,
abstract = {Board games, like Tic-Tac-Toe and CONNECT-4, play an important role not only in development of mathematical and logical skills, but also in emotional and social development. In this paper, we address the problem of generating targeted starting positions for such games. This can facilitate new approaches for bringing novice players to mastery, and also leads to discovery of interesting game variants.
Our approach generates starting states of varying hardness levels for player 1 in a two-player board game, given rules of the board game, the desired number of steps required for player 1 to win, and the expertise levels of the two players. Our approach leverages symbolic methods and iterative simulation to efficiently search the extremely large state space. We present experimental results that include discovery of states of varying hardness levels for several simple grid-based board games. Also, the presence of such states for standard game variants like Tic-Tac-Toe on board size 4x4 opens up new games to be played that have not been played for ages since the default start state is heavily biased. },
author = {Ahmed, Umair and Chatterjee, Krishnendu and Gulwani, Sumit},
issn = {2664-1690},
pages = {13},
publisher = {IST Austria},
title = {{Automatic generation of alternative starting positions for traditional board games}},
doi = {10.15479/AT:IST-2013-146-v1-1},
year = {2013},
}
@inbook{5747,
author = {Dragoi, Cezara and Gupta, Ashutosh and Henzinger, Thomas A},
booktitle = {Computer Aided Verification},
isbn = {9783642397981},
issn = {0302-9743},
location = {Saint Petersburg, Russia},
pages = {174--190},
publisher = {Springer Berlin Heidelberg},
title = {{Automatic Linearizability Proofs of Concurrent Objects with Cooperating Updates}},
doi = {10.1007/978-3-642-39799-8_11},
volume = {8044},
year = {2013},
}