Programmiersprachen und Rechenkonzepte

Die GI-Fachgruppe 2.1.4 "Programmiersprachen und Rechenkonzepte" veranstaltete vom 3. bis 5. Mai 2004 im Physikzentrum Bad Honnef ihren jährlichen Workshop. Dieser Bericht enthält eine Zusammenstellung der Beiträge. Das Treffen diente wie in jedem Jahr gegenseitigem Kennenlernen, der Vertiefung gegenseitiger Kontakte, der Vorstellung neuer Arbeiten und Ergebnisse und vor allem der intensiven Diskussion. Ein breites Spektrum von Beiträgen, von theoretischen Grundlagen über Programmentwicklung, Sprachdesign, Softwaretechnik und Objektorientierung bis hin zur überraschend langen Geschichte der Rechenautomaten seit der Antike bildete ein interessantes und abwechlungsreiches Programm. Unter anderem waren imperative, funktionale und funktional-logische Sprachen, Software/Hardware-Codesign, Semantik, Web-Programmierung und Softwaretechnik, generative Programmierung, Aspekte und formale Testunterstützung Thema. Interessante Beiträge zu diesen und weiteren Themen gaben Anlaß zu Erfahrungsaustausch und Fachgesprächen auch mit den Teilnehmern des zeitgleich im Physikzentrum Bad Honnef stattfindenden Workshops "Reengineering". Allen Teilnehmern möchte ich dafür danken, daß sie mit ihren Vorträgen und konstruktiven Diskussionsbeiträgen zum Gelingen des Workshops beigetragen haben. Dank für die Vielfalt und Qualität der Beiträge gebührt den Autoren. Ein Wort des Dankes gebührt ebenso den Mitarbeitern und der Leitung des Physikzentrums Bad Honnef für die gewohnte angenehme und anregende Atmosphäre und umfassende Betreuung

Workshop on Verification and Theorem Proving for Continuous Systems (NetCA Workshop 2005)

Oxford, UK, 26 August 200

Fast and Lean Immutable Multi-Maps on the JVM based on Heterogeneous Hash-Array Mapped Tries

An immutable multi-map is a many-to-many thread-friendly map data structure with expected fast insert and lookup operations. This data structure is used for applications processing graphs or many-to-many relations as applied in static analysis of object-oriented systems. When processing such big data sets the memory overhead of the data structure encoding itself is a memory usage bottleneck. Motivated by reuse and type-safety, libraries for Java, Scala and Clojure typically implement immutable multi-maps by nesting sets as the values with the keys of a trie map. Like this, based on our measurements the expected byte overhead for a sparse multi-map per stored entry adds up to around 65B, which renders it unfeasible to compute with effectively on the JVM. In this paper we propose a general framework for Hash-Array Mapped Tries on the JVM which can store type-heterogeneous keys and values: a Heterogeneous Hash-Array Mapped Trie (HHAMT). Among other applications, this allows for a highly efficient multi-map encoding by (a) not reserving space for empty value sets and (b) inlining the values of singleton sets while maintaining a (c) type-safe API. We detail the necessary encoding and optimizations to mitigate the overhead of storing and retrieving heterogeneous data in a hash-trie. Furthermore, we evaluate HHAMT specifically for the application to multi-maps, comparing them to state-of-the-art encodings of multi-maps in Java, Scala and Clojure. We isolate key differences using microbenchmarks and validate the resulting conclusions on a real world case in static analysis. The new encoding brings the per key-value storage overhead down to 30B: a 2x improvement. With additional inlining of primitive values it reaches a 4x improvement

The Hidden Injuries Of Overloading \u27ADT

The most commonly stated definition of abstract data type (ADT) is that it is a domain of values and the operations over that domain. So, for example, a language\u27s built-in types, like int are seen to be ADTs. It is our opinion that a pure interpretation of this definition yields a semantics in which using an ADT is the same as using built-in types: the operations are side effect free and there is no concern over alias, shallow copy or synchronization problems. Unfortunately, the term abstract data type has over time been associated with at least three distinct meanings, and those incompatible definitions have often been conflated, causing confusion to students and textbook authors alike. We believe that this has resulted in a loss of appreciation for the value-based semantics of ADTs

Kolmogorov Complexity Theory over the Reals

Kolmogorov Complexity constitutes an integral part of computability theory, information theory, and computational complexity theory -- in the discrete setting of bits and Turing machines. Over real numbers, on the other hand, the BSS-machine (aka real-RAM) has been established as a major model of computation. This real realm has turned out to exhibit natural counterparts to many notions and results in classical complexity and recursion theory; although usually with considerably different proofs. The present work investigates similarities and differences between discrete and real Kolmogorov Complexity as introduced by Montana and Pardo (1998)

Entanglement entropy for a Maxwell field: Numerical calculation on a two dimensional lattice

We study entanglement entropy (EE) for a Maxwell field in 2+1 dimensions. We do numerical calculations in two dimensional lattices. This gives a concrete example of the general results of our recent work on entropy for lattice gauge fields using an algebraic approach. To evaluate the entropies we extend the standard calculation methods for the entropy of Gaussian states in canonical commutation algebras to the more general case of algebras with center and arbitrary numerical commutators. We find that while the entropy depends on the details of the algebra choice, mutual information has a well defined continuum limit. We study several universal terms for the entropy of the Maxwell field and compare with the case of a massless scalar field. We find some interesting new phenomena: An "evanescent" logarithmically divergent term in the entropy with topological coefficient which does not have any correspondence with ultraviolet entanglement in the universal quantities, and a non standard way in which strong subadditivity is realized. Based on the results of our calculations we propose a generalization of strong subadditivity for the entropy on some algebras that are not in tensor product.Comment: 27 pages, 15 figure