Publications
86 results found
Bertrand N, Bortolussi L, Wiklicky H, 2016, Editorial: Quantitative Aspects of Programming Languages and Systems Preface, THEORETICAL COMPUTER SCIENCE, Vol: 655, Pages: 91-91, ISSN: 0304-3975
Wiklicky H, 2016, On dynamical probabilities, or: how to learn to shoot straight, Coordination 2016, Publisher: Springer Verlag, Pages: 262-277, ISSN: 1439-7358
In order to support, for example, a quantitative analysis of various algorithms, protocols etc. probabilistic features have been introduced into a number of programming languages and calculi. It is by now quite standard to define the formal semantics of (various) probabilistic languages, for example, in terms of Discrete Time Markov Chains (DTMCs). In most cases however the probabilities involved are represented by constants, i.e. one deals with static probabilities. In this paper we investigate a semantical framework which allows for changing, i.e. dynamic probabilities which is still based on time-homogenous DTMCs, i.e. the transition matrix representing the semantics of a program does not change over time.
Di Pierro A, Wiklicky H, 2015, Probabilistic abstract interpretation: From trace semantics to DTMC’s and linear regression, Essays Dedicated to Hanne Riis Nielson and Flemming Nielson on the Occasion of Their 60th Birthdays, Editors: Probst, Hankin, Hansen, Publisher: Springer, Pages: 111-139, ISBN: 9783319278094
In order to perform probabilistic program analysis we need to consider probabilistic languages or languages with a probabilistic semantics, as well as a corresponding framework for the analysis which is able to accommodate probabilistic properties and properties of probabilistic computations. To this purpose we investigate the relationship between three different types of probabilistic semantics for a core imperative language, namely Kozen’s Fixpoint Semantics, our Linear Operator Semantics and probabilistic versions of Maximal Trace Semantics. We also discuss the relationship between Probabilistic Abstract Interpretation (PAI) and statistical or linear regression analysis. While classical Abstract Interpretation, based on Galois connection, allows only for worst-case analyses, the use of the Moore-Penrose pseudo inverse in PAI opens the possibility of exploiting statistical and noisy observations in order to analyse and identify various system properties.
Wiklicky H, 2014, Program synthesis and linear operator semantics, Pages: 17-33, ISSN: 2075-2180
For deterministic and probabilistic programs we investigate the problem of program synthesis and program optimisation (with respect to non-functional properties) in the general setting of global optimisation. This approach is based on the representation of the semantics of programs and program fragments in terms of linear operators, i.e. as matrices. We exploit in particular the fact that we can automatically generate the representation of the semantics of elementary blocks. These can then can be used in order to compositionally assemble the semantics of a whole program, i.e. the generator of the corresponding Discrete Time Markov Chain (DTMC).We also utilise a generalised version of Abstract Interpretation suitable for this linear algebraic or functional analytical framework in order to formulate semantical constraints (invariants) and optimisation objectives (for example performance requirements).
Wiklicky H, Di Pierro A, 2014, Probabilistic Analysis of Programs: A Weak Limit Approach, FOPARA, Publisher: Springer Verlag
Massink M, Norman G, Wiklicky H, 2014, Quantitative Aspects of Programming Languages and Systems (2011-12) Preface, THEORETICAL COMPUTER SCIENCE, Vol: 538, Pages: 1-1, ISSN: 0304-3975
Di Pierro A, Wiklicky H, 2013, Semantics of Probabilistic Programs: A Weak Limit Approach, 11th Asian Symposium on Programming Languages and Systems
Di Pierro A, Wiklicky H, 2013, Probabilistic data flow analysis: a linear equational approach, GandALF 2013, Pages: 150-165
Gabbrielli M, Meo MC, Tacchella P, et al., 2013, Unfolding for CHR programs, Theory and Practice of Logic Programming
Pan I, Das S, 2013, Preface, Studies in Computational Intelligence, Vol: 438, ISSN: 1860-949X
Lawrence N, Girolami M, 2012, Preface, Journal of Machine Learning Research, Vol: 22, ISSN: 1532-4435
Schirmer M, Hoehn E, Vogt T, 2011, Preface, IAHS-AISH Publication, Vol: 342, ISSN: 0144-7815
Di Pierro A, Hankin C, Wiklicky H, 2011, Probabilistic timing covert channels: to close or not to close?, INTERNATIONAL JOURNAL OF INFORMATION SECURITY, Vol: 10, Pages: 83-106, ISSN: 1615-5262
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- Citations: 4
Aldini A, Bernardo M, Di Pierro A, et al., 2010, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol: 6154 LNCS, ISSN: 0302-9743
Di Pierro A, Hankin C, Wiklicky H, 2010, Program Analysis Probably Counts, COMPUTER JOURNAL, Vol: 53, Pages: 871-880, ISSN: 0010-4620
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- Citations: 1
, 2010, Formal Methods for Quantitative Aspects of Programming Languages, 10th International School on Formal Methods for the Design of Computer, Communication and Software Systems, SFM 2010, Bertinoro, Italy, June 21-26, 2010, Advanced Lectures, Publisher: Springer
Di Pierro A, Hankin CL, Wiklicky H, 2010, Probabilistic Semantics and Program Analysis, Formal Methods for Quantitative Aspects of Programming Languages, Editors: Aldini, Bernardo, Di Pierro, Wiklicky, Pages: 1-42
Di Pierro A, Sotin P, Wiklicky H, 2008, Relational Analysis and Precision via Probabilistic Abstract Interpretation, Electronic Notes in Theoretical Computer Science, Vol: 220, Pages: 23-42, ISSN: 1571-0661
Di Pierro A, Wiklicky H, 2008, Semantic Abstraction and Quantum Computation, Electronic Notes in Theoretical Computer Science, Vol: 210, Pages: 49-63, ISSN: 1571-0661
We present a logico-algebraic approach to probabilistic abstract interpretation based on the ortholattice structure of the projective measurement operators in quantum mechanics. On this base, we present a novel interpretation of quantum measurement as a probabilistic abstraction showing that the measurement of a physical observable essentially corresponds to a static analysis of the observed property. © 2008 Elsevier B.V. All rights reserved.
Di Pierro A, Hankin CL, Wiklicky H, 2008, Quantifying Timing Leaks and Cost Optimisation, International Conference on Information and Communications Security, Publisher: Springer, Pages: 81-96
Pierro AD, Hankin C, Wiklicky H, 2008, Quantifying Timing Leaks and Cost Optimisation, CoRR, Vol: abs/0807.3879
Di Pierro A, Hankin C, Wiklicky H, 2007, On Probabilistic Techniques for Data Flow Analysis, Electronic Notes in Theoretical Computer Science, Vol: 190, Pages: 59-77, ISSN: 1571-0661
We present a semantics-based technique for analysing probabilistic properties of imperative programs. This consists in a probabilistic version of classical data flow analysis. We apply this technique to pWhile programs, i.e programs written in a probabilistic version of a simple While language. As a first step we introduce a syntax based definition of a linear operator semantics (LOS) which is equivalent to the standard structural operational semantics of While. The LOS of a pWhile program can be seen as the generator of a Discrete Time Markov Chain and plays a similar role as a collecting or trace semantics for classical While. Probabilistic Abstract Interpretation techniques are then employed in order to define data flow analyses for properties like Parity and Live Variables. © 2007.
Di Pierro A, Wiklicky H, 2007, Quantitative aspects of programming languages - Preface, THEORETICAL COMPUTER SCIENCE, Vol: 382, Pages: 1-2, ISSN: 0304-3975
Di Pierro A, Hankin C, Siveroni I, et al., 2007, Tempus fugit: How to plug it, JOURNAL OF LOGIC AND ALGEBRAIC PROGRAMMING, Vol: 72, Pages: 173-190, ISSN: 1567-8326
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- Citations: 5
, 2007, 13th International Workshop on Expressiveness in Concurrency (EXPRESS'06), Publisher: Elsevier
Di Pierro A, Hankin C, Wiklicky H, 2007, A systematic approach to probabilistic pointer analysis, 5th Asian Symposium on Programming Languages and Systems, Publisher: SPRINGER-VERLAG BERLIN, Pages: 335-350, ISSN: 0302-9743
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- Citations: 7
Di Pierro A, Hankin CL, Wiklicky H, 2007, Abstract Interpretation for Worst and Average Case Analysis, Program Analysis and Compilation, Theory and Practice, Editors: Reps, Sagiv, Bauer, Pages: 160-174
Pierro AD, Wiklicky H, 2007, Preface: Quantitative aspects of programming languages., Theor. Comput. Sci., Vol: 382, Pages: 1-2
Di Pierro A, Wiklicky H, 2006, Operator Algebras and the Operational Semantics of Probabilistic Languages, Electronic Notes in Theoretical Computer Science, Vol: 161, Pages: 131-150, ISSN: 1571-0661
We investigate the construction of linear operators representing the semantics of probabilistic programming languages expressed via probabilistic transition systems. Finite transition relations, corresponding to finite automata, can easily be represented by finite dimensional matrices; for the infinite case we need to consider an appropriate generalisation of matrix algebras. We argue that C*-algebras, or more precisely Approximately Finite (or AF) algebras, provide a sufficiently rich mathematical structure for modelling probabilistic processes. We show how to construct for a given probabilistic language a unique AF algebra A and how to represent the operational semantics of processes within this framework: finite computations correspond directly to operators in A, while infinite processes are represented by elements in the so-called strong closure of this algebra. © 2006 Elsevier B.V. All rights reserved.
Di Pierro A, Hankin C, Wiklicky H, 2006, Reversible combinatory logic, 1st International Workshop on Developments in Computational Models (DCM), Publisher: CAMBRIDGE UNIV PRESS, Pages: 621-637, ISSN: 0960-1295
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- Citations: 10
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