@inproceedings{1729,
abstract = {We present a computer-aided programming approach to concurrency. The approach allows programmers to program assuming a friendly, non-preemptive scheduler, and our synthesis procedure inserts synchronization to ensure that the final program works even with a preemptive scheduler. The correctness specification is implicit, inferred from the non-preemptive behavior. Let us consider sequences of calls that the program makes to an external interface. The specification requires that any such sequence produced under a preemptive scheduler should be included in the set of such sequences produced under a non-preemptive scheduler. The solution is based on a finitary abstraction, an algorithm for bounded language inclusion modulo an independence relation, and rules for inserting synchronization. We apply the approach to device-driver programming, where the driver threads call the software interface of the device and the API provided by the operating system. Our experiments demonstrate that our synthesis method is precise and efficient, and, since it does not require explicit specifications, is more practical than the conventional approach based on user-provided assertions.},
author = {Cerny, Pavol and Clarke, Edmund and Henzinger, Thomas A and Radhakrishna, Arjun and Ryzhyk, Leonid and Samanta, Roopsha and Tarrach, Thorsten},
location = {San Francisco, CA, United States},
pages = {180 -- 197},
publisher = {Springer},
title = {{From non-preemptive to preemptive scheduling using synchronization synthesis}},
doi = {10.1007/978-3-319-21668-3_11},
volume = {9207},
year = {2015},
}
@article{1731,
abstract = {We consider two-player zero-sum games on graphs. These games can be classified on the basis of the information of the players and on the mode of interaction between them. On the basis of information the classification is as follows: (a) partial-observation (both players have partial view of the game); (b) one-sided complete-observation (one player has complete observation); and (c) complete-observation (both players have complete view of the game). On the basis of mode of interaction we have the following classification: (a) concurrent (both players interact simultaneously); and (b) turn-based (both players interact in turn). The two sources of randomness in these games are randomness in transition function and randomness in strategies. In general, randomized strategies are more powerful than deterministic strategies, and randomness in transitions gives more general classes of games. In this work we present a complete characterization for the classes of games where randomness is not helpful in: (a) the transition function probabilistic transition can be simulated by deterministic transition); and (b) strategies (pure strategies are as powerful as randomized strategies). As consequence of our characterization we obtain new undecidability results for these games. },
author = {Chatterjee, Krishnendu and Doyen, Laurent and Gimbert, Hugo and Henzinger, Thomas A},
journal = {Information and Computation},
number = {12},
pages = {3 -- 16},
publisher = {Elsevier},
title = {{Randomness for free}},
doi = {10.1016/j.ic.2015.06.003},
volume = {245},
year = {2015},
}
@inproceedings{1661,
abstract = {The computation of the winning set for one-pair Streett objectives and for k-pair Streett objectives in (standard) graphs as well as in game graphs are central problems in computer-aided verification, with application to the verification of closed systems with strong fairness conditions, the verification of open systems, checking interface compatibility, well-formed ness of specifications, and the synthesis of reactive systems. We give faster algorithms for the computation of the winning set for (1) one-pair Streett objectives (aka parity-3 problem) in game graphs and (2) for k-pair Streett objectives in graphs. For both problems this represents the first improvement in asymptotic running time in 15 years.},
author = {Chatterjee, Krishnendu and Henzinger, Monika and Loitzenbauer, Veronika},
booktitle = {Proceedings - Symposium on Logic in Computer Science},
location = {Kyoto, Japan},
publisher = {IEEE},
title = {{Improved algorithms for one-pair and k-pair Streett objectives}},
doi = {10.1109/LICS.2015.34},
volume = {2015-July},
year = {2015},
}
@misc{5435,
abstract = {We consider Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) objectives.
There have been two different views: (i) the expectation semantics, where the goal is to optimize the expected mean-payoff objective, and (ii) the satisfaction semantics, where the goal is to maximize the probability of runs such that the mean-payoff value stays above a given vector.
We consider the problem where the goal is to optimize the expectation under the constraint that the satisfaction semantics is ensured, and thus consider a generalization that unifies the existing semantics. Our problem captures the notion of optimization with respect to strategies that are risk-averse (i.e., ensures certain probabilistic guarantee).
Our main results are algorithms for the decision problem which are always polynomial in the size of the MDP.
We also show that an approximation of the Pareto-curve can be computed in time polynomial in the size of the MDP, and the approximation factor, but exponential in the number of dimensions. Finally, we present a complete characterization of the strategy complexity (in terms of memory bounds and randomization) required to solve our problem.},
author = {Chatterjee, Krishnendu and Komarkova, Zuzana and Kretinsky, Jan},
issn = {2664-1690},
pages = {51},
publisher = {IST Austria},
title = {{Unifying two views on multiple mean-payoff objectives in Markov decision processes}},
doi = {10.15479/AT:IST-2015-318-v2-1},
year = {2015},
}
@article{523,
abstract = {We consider two-player games played on weighted directed graphs with mean-payoff and total-payoff objectives, two classical quantitative objectives. While for single-dimensional games the complexity and memory bounds for both objectives coincide, we show that in contrast to multi-dimensional mean-payoff games that are known to be coNP-complete, multi-dimensional total-payoff games are undecidable. We introduce conservative approximations of these objectives, where the payoff is considered over a local finite window sliding along a play, instead of the whole play. For single dimension, we show that (i) if the window size is polynomial, deciding the winner takes polynomial time, and (ii) the existence of a bounded window can be decided in NP ∩ coNP, and is at least as hard as solving mean-payoff games. For multiple dimensions, we show that (i) the problem with fixed window size is EXPTIME-complete, and (ii) there is no primitive-recursive algorithm to decide the existence of a bounded window.},
author = {Chatterjee, Krishnendu and Doyen, Laurent and Randour, Mickael and Raskin, Jean},
journal = {Information and Computation},
number = {6},
pages = {25 -- 52},
publisher = {Elsevier},
title = {{Looking at mean-payoff and total-payoff through windows}},
doi = {10.1016/j.ic.2015.03.010},
volume = {242},
year = {2015},
}