@inproceedings{4378,
abstract = {Techniques such as verification condition generation, predicate abstraction, and expressive type systems reduce software verification to proving formulas in expressive logics. Programs and their specifications often make use of data structures such as sets, multisets, algebraic data types, or graphs. Consequently, formulas generated from verification also involve such data structures. To automate the proofs of such formulas we propose a logic (a “calculus”) of such data structures. We build the calculus by starting from decidable logics of individual data structures, and connecting them through functions and sets, in ways that go beyond the frameworks such as Nelson-Oppen. The result are new decidable logics that can simultaneously specify properties of different kinds of data structures and overcome the limitations of the individual logics. Several of our decidable logics include abstraction functions that map a data structure into its more abstract view (a tree into a multiset, a multiset into a set), into a numerical quantity (the size or the height), or into the truth value of a candidate data structure invariant (sortedness, or the heap property). For algebraic data types, we identify an asymptotic many-to-one condition on the abstraction function that guarantees the existence of a decision procedure. In addition to the combination based on abstraction functions, we can combine multiple data structure theories if they all reduce to the same data structure logic. As an instance of this approach, we describe a decidable logic whose formulas are propositional combinations of formulas in: weak monadic second-order logic of two successors, two-variable logic with counting, multiset algebra with Presburger arithmetic, the Bernays-Schönfinkel-Ramsey class of first-order logic, and the logic of algebraic data types with the set content function. The subformulas in this combination can share common variables that refer to sets of objects along with the common set algebra operations. Such sound and complete combination is possible because the relations on sets definable in the component logics are all expressible in Boolean Algebra with Presburger Arithmetic. Presburger arithmetic and its new extensions play an important role in our decidability results. In several cases, when we combine logics that belong to NP, we can prove the satisfiability for the combined logic is still in NP.},
author = {Kuncak, Viktor and Piskac, Ruzica and Suter, Philippe and Wies, Thomas},
editor = {Barthe, Gilles and Hermenegildo, Manuel},
location = {Madrid, Spain},
pages = {26 -- 44},
publisher = {Springer},
title = {{Building a calculus of data structures}},
doi = {10.1007/978-3-642-11319-2_6},
volume = {5944},
year = {2010},
}
@inproceedings{4380,
abstract = {Cloud computing is an emerging paradigm aimed to offer users pay-per-use computing resources, while leaving the burden of managing the computing infrastructure to the cloud provider. We present a new programming and pricing model that gives the cloud user the flexibility of trading execution speed and price on a per-job basis. We discuss the scheduling and resource management challenges for the cloud provider that arise in the implementation of this model. We argue that techniques from real-time and embedded software can be useful in this context.},
author = {Henzinger, Thomas A and Tomar, Anmol and Singh, Vasu and Wies, Thomas and Zufferey, Damien},
location = {Arizona, USA},
pages = {1 -- 8},
publisher = {ACM},
title = {{A marketplace for cloud resources}},
doi = {10.1145/1879021.1879022},
year = {2010},
}
@inproceedings{4381,
abstract = {Cloud computing aims to give users virtually unlimited pay-per-use computing resources without the burden of managing the underlying infrastructure. We claim that, in order to realize the full potential of cloud computing, the user must be presented with a pricing model that offers flexibility at the requirements level, such as a choice between different degrees of execution speed and the cloud provider must be presented with a programming model that offers flexibility at the execution level, such as a choice between different scheduling policies. In such a flexible framework, with each job, the user purchases a virtual computer with the desired speed and cost characteristics, and the cloud provider can optimize the utilization of resources across a stream of jobs from different users. We designed a flexible framework to test our hypothesis, which is called FlexPRICE (Flexible Provisioning of Resources in a Cloud Environment) and works as follows. A user presents a job to the cloud. The cloud finds different schedules to execute the job and presents a set of quotes to the user in terms of price and duration for the execution. The user then chooses a particular quote and the cloud is obliged to execute the job according to the chosen quote. FlexPRICE thus hides the complexity of the actual scheduling decisions from the user, but still provides enough flexibility to meet the users actual demands. We implemented FlexPRICE in a simulator called PRICES that allows us to experiment with our framework. We observe that FlexPRICE provides a wide range of execution options-from fast and expensive to slow and cheap-- for the whole spectrum of data-intensive and computation-intensive jobs. We also observe that the set of quotes computed by FlexPRICE do not vary as the number of simultaneous jobs increases.},
author = {Henzinger, Thomas A and Tomar, Anmol and Singh, Vasu and Wies, Thomas and Zufferey, Damien},
location = {Miami, USA},
pages = {83 -- 90},
publisher = {IEEE},
title = {{FlexPRICE: Flexible provisioning of resources in a cloud environment}},
doi = {10.1109/CLOUD.2010.71},
year = {2010},
}
@inproceedings{4382,
abstract = {Transactional memory (TM) has shown potential to simplify the task of writing concurrent programs. Inspired by classical work on databases, formal definitions of the semantics of TM executions have been proposed. Many of these definitions assumed that accesses to shared data are solely performed through transactions. In practice, due to legacy code and concurrency libraries, transactions in a TM have to share data with non-transactional operations. The semantics of such interaction, while widely discussed by practitioners, lacks a clear formal specification. Those interactions can vary, sometimes in subtle ways, between TM implementations and underlying memory models. We propose a correctness condition for TMs, parametrized opacity, to formally capture the now folklore notion of strong atomicity by stipulating the two following intuitive requirements: first, every transaction appears as if it is executed instantaneously with respect to other transactions and non-transactional operations, and second, non-transactional operations conform to the given underlying memory model. We investigate the inherent cost of implementing parametrized opacity. We first prove that parametrized opacity requires either instrumenting non-transactional operations (for most memory models) or writing to memory by transactions using potentially expensive read-modify-write instructions (such as compare-and-swap). Then, we show that for a class of practical relaxed memory models, parametrized opacity can indeed be implemented with constant-time instrumentation of non-transactional writes and no instrumentation of non-transactional reads. We show that, in practice, parametrizing the notion of correctness allows developing more efficient TM implementations.},
author = {Guerraoui, Rachid and Henzinger, Thomas A and Kapalka, Michal and Singh, Vasu},
location = {Santorini, Greece},
pages = {263 -- 272},
publisher = {ACM},
title = {{Transactions in the jungle}},
doi = {10.1145/1810479.1810529},
year = {2010},
}
@inproceedings{4388,
abstract = {GIST is a tool that (a) solves the qualitative analysis problem of turn-based probabilistic games with ω-regular objectives; and (b) synthesizes reasonable environment assumptions for synthesis of unrealizable specifications. Our tool provides the first and efficient implementations of several reduction-based techniques to solve turn-based probabilistic games, and uses the analysis of turn-based probabilistic games for synthesizing environment assumptions for unrealizable specifications.},
author = {Chatterjee, Krishnendu and Henzinger, Thomas A and Jobstmann, Barbara and Radhakrishna, Arjun},
location = {Edinburgh, UK},
pages = {665 -- 669},
publisher = {Springer},
title = {{GIST: A solver for probabilistic games}},
doi = {10.1007/978-3-642-14295-6_57},
volume = {6174},
year = {2010},
}