Context Update for Lambdas and Vectors

Vector models of language are based on the contextual aspects of words and how they co-occur in text. Truth conditional models focus on the logical aspects of language, the denotations of phrases, and their compositional properties. In the latter approach the denotation of a sentence determines its truth conditions and can be taken to be a truth value, a set of possible worlds, a context change potential, or similar. In this short paper, we develop a vector semantics for language based on the simply typed lambda calculus. Our semantics uses techniques familiar from the truth conditional tradition and is based on a form of dynamic interpretation inspired by Heim's context updates

Verbesserung von Cloud Sicherheit mithilfe von vertrauenswürdiger Ausführung

The increasing popularity of cloud computing also leads to a growing demand for security guarantees in cloud settings. Cloud customers want to be able to execute sensitive data processing in clouds only if a certain level of security can be guaranteed to them despite the unlimited power of the cloud provider over her infrastructure. However, security models for cloud computing mostly require the customers to trust the provider, its infrastructure and software stack completely. While this may be viable to some, it is by far not to all customers, and in turn reduces the speed of cloud adoption. In this thesis, the applicability of trusted execution technology to increase security in a cloud scenario is elaborated, as these technologies are recently becoming widespread available even in commodity hardware. However, applications should not naively be ported completely for usage of trusted execution technology as this would affect the resulting performance and security negatively. Instead they should be carefully crafted with specific characteristics of the used trusted execution technology in mind. Therefore, this thesis first comprises the discussion of various security goals of cloud-based applications and an overview of cloud security. Furthermore, it is investigated how the ARM TrustZone technology can be used to increase security of a cloud platform for generic applications. Next, securing standalone applications using trusted execution is described at the example of Intel SGX, focussing on relevant metrics that influence security as well as performance of such an application. Also based on Intel SGX, in this thesis a design of a trusted serverless cloud platform is proposed, reflecting the latest evolution of cloud-based applications.Die steigende Popularität von Cloud Computing führt zu immer mehr Nachfrage und auch strengeren Anforderungen an die Sicherheit in der Cloud. Nur wenn trotz der technischen Möglichkeiten eines Cloud Anbieters über seine eigene Infrastruktur ein entsprechendes Maß an Sicherheit garantiert werden kann, können Cloud Kunden sensible Daten einer Cloud Umgebung anvertrauen und diese dort verarbeiten. Das vorherrschende Paradigma bezüglich Sicherheit erfordert aktuell jedoch zumeist, dass der Kunde dem Cloud Provider, dessen Infrastruktur sowie den damit verbundenen Softwarekomponenten komplett vertraut. Während diese Vorgehensweise für manche Anwendungsfälle einen gangbaren Weg darstellen mag, ist dies bei Weitem nicht für alle Cloud Kunden eine Option, was nicht zuletzt auch die Annahme von Cloud Angeboten durch potentielle Kunden verlangsamt. In dieser Dissertation wird nun die Anwendbarkeit verschiedener Technologien für vertrauenswürdige Ausführung zur Verbesserung der Sicherheit in der Cloud untersucht, da solche Technologien in letzter Zeit auch in preiswerteren Hardwarekomponenten immer verbreiteter und verfügbarer werden. Es ist jedoch keine triviale Aufgabe existierende Anwendungen zur portieren, sodass diese von solch gearteten Technologien profitieren können, insbesondere wenn neben Sicherheit auch Effizienz und Performanz der Anwendung berücksichtigt werden soll. Stattdessen müssen Anwendungen sorgfältig unter verschiedenen spezifischen Gesichtspunkten der jeweiligen Technologie umgestaltet werden. Aus diesem Grund umfasst diese Dissertation zunächst eine Diskussion verschiedener Sicherheitsziele für Cloud-basierte Anwendungen und eine Übersicht über die Thematik "Cloud Sicherheit". Zunächst wird dann das Potential der ARM TrustZone Technologie zur Absicherung einer Cloud Plattform für generische Anwendungen untersucht. Anschließend wird beschrieben wie eigenständige und bestehende Anwendungen mittels vertrauenswürdiger Ausführung am Beispiel Intel SGX abgesichert werden können. Dabei wurde der Fokus auf relevante Metriken gesetzt, die die Sicherheit und Performanz einer solchen Anwendung beeinflussen. Zuletzt wird, ebenfalls basierend auf Intel SGX, eine vertrauenswürdige "Serverless" Cloud Plattform vorgestellt und damit auf aktuelle Trends für Cloud Plattformen eingegangen

Static and Dynamic Vector Semantics for Lambda Calculus Models of Natural Language

To appear in Journal of Language Modelling. Short versions presented in DSALT 2016, SaLMoM 2016, LACL 2016. A version presented in AC 2017To appear in Journal of Language Modelling. Short versions presented in DSALT 2016, SaLMoM 2016, LACL 2016. A version presented in AC 2017To appear in Journal of Language Modelling. Short versions presented in DSALT 2016, SaLMoM 2016, LACL 2016. A version presented in AC 2017Vector models of language are based on the contextual aspects of language, the distributions of words and how they co-occur in text. Truth conditional models focus on the logical aspects of language, compositional properties of words and how they compose to form sentences. In the truth conditional approach, the denotation of a sentence determines its truth conditions, which can be taken to be a truth value, a set of possible worlds, a context change potential, or similar. In the vector models, the degree of co-occurrence of words in context determines how similar the meanings of words are. In this paper, we put these two models together and develop a vector semantics for language based on the simply typed lambda calculus models of natural language. We provide two types of vector semantics: a static one that uses techniques familiar from the truth conditional tradition and a dynamic one based on a form of dynamic interpretation inspired by Heim's context change potentials. We show how the dynamic model can be applied to entailment between a corpus and a sentence and we provide examples

Classical Copying versus Quantum Entanglement in Natural Language: The Case of VP-ellipsis

In Proceedings CAPNS 2018, arXiv:1811.02701In Proceedings CAPNS 2018, arXiv:1811.0270

Doctor of Philosophy in Computer Science

dissertationControl-flow analysis of higher-order languages is a difficult problem, yet an important one. It aids in enabling optimizations, improved reliability, and improved security of programs written in these languages. This dissertation explores three techniques to improve the precision and speed of a small-step abstract interpreter: using a priority work list, environment unrolling, and strong function call. In an abstract interpreter, the interpreter is no longer deterministic and choices can be made in how the abstract state space is explored and trade-offs exist. A priority queue is one option. There are also many ways to abstract the concrete interpreter. Environment unrolling gives a slightly different approach than is usually taken, by holding off abstraction in order to gain precision, which can lead to a faster analysis. Strong function call is an approach to clean up some of the imprecision when making a function call that is introduced when abstractly interpreting a program. An alternative approach to building an abstract interpreter to perform static analysis is through the use of constraint solving. Existing techniques to do this have been developed over the last several decades. This dissertation maps these constraints to three different problems, allowing control-flow analysis of higher-order languages to be solved with tools that are already mature and well developed. The control-flow problem is mapped to pointer analysis of first-order languages, SAT, and linear-algebra operations. These mappings allow for fast and parallel implementations of control-flow analysis of higher-order languages. A recent development in the field of static analysis has been pushdown control-flow analysis, which is able to precisely match calls and returns, a weakness in the existing techniques. This dissertation also provides an encoding of pushdown control-flow analysis to linear-algebra operations. In the process, it demonstrates that under certain conditions (monovariance and flow insensitivity) that in terms of precision, a pushdown control-flow analysis is in fact equivalent to a direct style constraint-based formulation

Evaluating Composition Models for Verb Phrase Elliptical Sentence Embeddings

Ellipsis is a natural language phenomenon where part of a sentence is missing and its information must be recovered from its surrounding context, as in “Cats chase dogs and so do foxes.”. Formal semantics has different methods for resolving ellipsis and recovering the missing information, but the problem has not been considered for distributional semantics, where words have vector embeddings and combinations thereof provide embeddings for sentences. In elliptical sentences these combinations go beyond linear as copying of elided information is necessary. In this paper, we develop different models for embedding VP-elliptical sentences. We extend existing verb disambiguation and sentence similarity datasets to ones containing elliptical phrases and evaluate our models on these datasets for a variety of non-linear combinations and their linear counterparts. We compare results of these compositional models to state of the art holistic sentence encoders. Our results show that non-linear addition and a non-linear tensor-based composition outperform the naive non-compositional baselines and the linear models, and that sentence encoders perform well on sentence similarity, but not on verb disambiguation

Modular, higher order cardinality analysis in theory and practice

Since the mid '80s, compiler writers for functional languages (especially lazy ones) have been writing papers about identifying and exploiting thunks and lambdas that are used only once. However, it has proved difficult to achieve both power and simplicity in practice. In this paper, we describe a new, modular analysis for a higher order language, which is both simple and effective. We prove the analysis sound with respect to a standard call-by-need semantics, and present measurements of its use in a full-scale, state-of-the-art optimising compiler. The analysis finds many single-entry thunks and one-shot lambdas and enables a number of program optimisations. This paper extends our preceding conference publication (Sergey et al. 2014 Proceedings of the 41st Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL 2014). ACM, pp. 335–348) with proofs, expanded report on evaluation and a detailed examination of the factors causing the loss of precision in the analysis