@inproceedings{2182,
abstract = {We propose a general framework for abstraction with respect to quantitative properties, such as worst-case execution time, or power consumption. Our framework provides a systematic way for counter-example guided abstraction refinement for quantitative properties. The salient aspect of the framework is that it allows anytime verification, that is, verification algorithms that can be stopped at any time (for example, due to exhaustion of memory), and report approximations that improve monotonically when the algorithms are given more time. We instantiate the framework with a number of quantitative abstractions and refinement schemes, which differ in terms of how much quantitative information they keep from the original system. We introduce both state-based and trace-based quantitative abstractions, and we describe conditions that define classes of quantitative properties for which the abstractions provide over-approximations. We give algorithms for evaluating the quantitative properties on the abstract systems. We present algorithms for counter-example based refinements for quantitative properties for both state-based and segment-based abstractions. We perform a case study on worst-case execution time of executables to evaluate the anytime verification aspect and the quantitative abstractions we proposed.},
author = {Cerny, Pavol and Henzinger, Thomas A and Radhakrishna, Arjun},
booktitle = {Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of programming language},
location = {Rome, Italy},
pages = {115 -- 128},
publisher = {ACM},
title = {{Quantitative abstraction refinement}},
doi = {10.1145/2429069.2429085},
year = {2013},
}
@inproceedings{2209,
abstract = {A straight skeleton is a well-known geometric structure, and several algorithms exist to construct the straight skeleton for a given polygon or planar straight-line graph. In this paper, we ask the reverse question: Given the straight skeleton (in form of a planar straight-line graph, with some rays to infinity), can we reconstruct a planar straight-line graph for which this was the straight skeleton? We show how to reduce this problem to the problem of finding a line that intersects a set of convex polygons. We can find these convex polygons and all such lines in $O(nlog n)$ time in the Real RAM computer model, where $n$ denotes the number of edges of the input graph. We also explain how our approach can be used for recognizing Voronoi diagrams of points, thereby completing a partial solution provided by Ash and Bolker in 1985.
},
author = {Biedl, Therese and Held, Martin and Huber, Stefan},
location = {St. Petersburg, Russia},
pages = {37 -- 46},
publisher = {IEEE},
title = {{Recognizing straight skeletons and Voronoi diagrams and reconstructing their input}},
doi = {10.1109/ISVD.2013.11},
year = {2013},
}
@inproceedings{2210,
abstract = {A straight skeleton is a well-known geometric structure, and several algorithms exist to construct the straight skeleton for a given polygon. In this paper, we ask the reverse question: Given the straight skeleton (in form of a tree with a drawing in the plane, but with the exact position of the leaves unspecified), can we reconstruct the polygon? We show that in most cases there exists at most one polygon; in the remaining case there is an infinite number of polygons determined by one angle that can range in an interval. We can find this (set of) polygon(s) in linear time in the Real RAM computer model.},
author = {Biedl, Therese and Held, Martin and Huber, Stefan},
booktitle = {29th European Workshop on Computational Geometry},
location = {Braunschweig, Germany},
pages = {95 -- 98},
publisher = {TU Braunschweig},
title = {{Reconstructing polygons from embedded straight skeletons}},
year = {2013},
}
@inproceedings{2237,
abstract = {We describe new extensions of the Vampire theorem prover for computing tree interpolants. These extensions generalize Craig interpolation in Vampire, and can also be used to derive sequence interpolants. We evaluated our implementation on a large number of examples over the theory of linear integer arithmetic and integer-indexed arrays, with and without quantifiers. When compared to other methods, our experiments show that some examples could only be solved by our implementation.},
author = {Blanc, Régis and Gupta, Ashutosh and Kovács, Laura and Kragl, Bernhard},
location = {Stellenbosch, South Africa},
pages = {173 -- 181},
publisher = {Springer},
title = {{Tree interpolation in Vampire}},
doi = {10.1007/978-3-642-45221-5_13},
volume = {8312},
year = {2013},
}
@inproceedings{2238,
abstract = {We study the problem of achieving a given value in Markov decision processes (MDPs) with several independent discounted reward objectives. We consider a generalised version of discounted reward objectives, in which the amount of discounting depends on the states visited and on the objective. This definition extends the usual definition of discounted reward, and allows to capture the systems in which the value of different commodities diminish at different and variable rates.
We establish results for two prominent subclasses of the problem, namely state-discount models where the discount factors are only dependent on the state of the MDP (and independent of the objective), and reward-discount models where they are only dependent on the objective (but not on the state of the MDP). For the state-discount models we use a straightforward reduction to expected total reward and show that the problem whether a value is achievable can be solved in polynomial time. For the reward-discount model we show that memory and randomisation of the strategies are required, but nevertheless that the problem is decidable and it is sufficient to consider strategies which after a certain number of steps behave in a memoryless way.
For the general case, we show that when restricted to graphs (i.e. MDPs with no randomisation), pure strategies and discount factors of the form 1/n where n is an integer, the problem is in PSPACE and finite memory suffices for achieving a given value. We also show that when the discount factors are not of the form 1/n, the memory required by a strategy can be infinite.
},
author = {Chatterjee, Krishnendu and Forejt, Vojtěch and Wojtczak, Dominik},
location = {Stellenbosch, South Africa},
pages = {228 -- 242},
publisher = {Springer},
title = {{Multi-objective discounted reward verification in graphs and MDPs}},
doi = {10.1007/978-3-642-45221-5_17},
volume = {8312},
year = {2013},
}