262 research outputs found
Integrating distributed data streams
Abstract unavailable please refer to PD
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Transformational maintenance by reuse of design histories
This thesis provides theory and procedures for modifying software artifacts implemented by a formal transformation process. Installing modifications requires knowing not only what transformations were applied (a derivation history) to construct the artifact, but also why the application sequence ensures that the artifact meets its specification. The derivation history and the justification are collectively called a design history. A Design Maintenance System (DMS), when provided with a formal change called a maintenance delta, revises a design history to guide construction of a new artifact. A DMS can be used to integrate a stream of deltas into a history, providing implementations as a side effect, leading to an incremental-evolution model for software construction.We provide a broadly applicable formal model of transformation systems in which specifications are performance predicates, subsuming the functional specifications which are traditional for transformation systems. Such performance predicates provide vocabulary used in the design history to describe the effect of applying sets of transformations.A nonprocedural, performance-goal-oriented Transformation Control Language (TCL) is defined to control navigation of the design space for a transformation system. Recording the execution of a TCL metaprogram directly provides a design history.A complete classification of, and representation for, the set of possible maintenance deltas is given in terms of the inputs defined by the transformation system model. Such deltas include not only specification changes, but also changes to implementation support technologies. Delta integration procedures for revising derivation histories given functional or support technology deltas are provided, based on rearranging the order of transformations in the design space. Building on these operations, integration procedures that revise the design history for each type of delta are described. An agenda-oriented TCL execution process dovetails smoothly with the integration procedures.Our DMS is compared to a number of other maintenance systems. By using an explicit delta and verified commutativity, our DMS often reuses transformations correctly when others fail
Iterated Belief Revision Under Resource Constraints: Logic as Geometry
We propose a variant of iterated belief revision designed for settings with limited computational resources, such as mobile autonomous robots.
The proposed memory architecture---called the universal memory architecture (UMA)---maintains an epistemic state in the form of a system of default rules similar to those studied by Pearl and by Goldszmidt and Pearl (systems Z and Z+). A duality between the category of UMA representations and the category of the corresponding model spaces, extending the Sageev-Roller duality between discrete poc sets and discrete median algebras provides a two-way dictionary from inference to geometry, leading to immense savings in computation, at a cost in the quality of representation that can be quantified in terms of topological invariants. Moreover, the same framework naturally enables comparisons between different model spaces, making it possible to analyze the deficiencies of one model space in comparison to others.
This paper develops the formalism underlying UMA, analyzes the complexity of maintenance and inference operations in UMA, and presents some learning guarantees for different UMA-based learners. Finally, we present simulation results to illustrate the viability of the approach, and close with a discussion of the strengths, weaknesses, and potential development of UMA-based learners
Complex Event Processing with XChangeEQ
The emergence of event-driven architectures, automation of business processes, drastic cost-reductions in sensor technology, and a growing need to monitor IT systems (as well as other systems) due to legal, contractual, or operational considerations lead to an increasing generation of events. This development is accompanied by a growing demand for managing and processing events in an
automated and systematic way. Complex Event Processing (CEP) encompasses the (automatable) tasks involved in making sense of all events in a system by deriving higher-level knowledge from lower-level events while the events
occur, i.e., in a timely, online fashion and permanently.
At the core of CEP are queries which monitor streams of "simple" events for so-called complex events, that is, events or situations that manifest themselves in certain combinations of several events occurring (or not occurring) over time and that cannot be detected from looking only at single events. Querying events is fundamentally different from traditional querying and reasoning with database or Web data, since event queries are standing queries that are evaluated permanently over time against incoming streams of event data. In order to express complex events that are of interest to a particular application or user in a convenient, concise, cost-effective and maintainable manner, special purpose Event Query Languages (EQLs) are needed.
This thesis investigates practical and theoretical issues related to querying complex events, covering the spectrum from language design over declarative semantics to operational semantics for incremental query evaluation. Its central topic is the development of the high-level event query language XChangeEQ.
In contrast to previous data stream and event query languages, XChangeEQ's language design recognizes the four querying dimensions of data extractions, event composition, temporal relationships, and, for non-monotonic queries involving negation or aggregation, event accumulation. XChangeEQ deals with complex structured data in event messages, thus addressing the need to query events communicated in XML formats over the Web. It supports deductive rules as an abstraction and reasoning mechanism for events. To achieve a full coverage of the four querying dimensions, it builds upon a separation of concerns of the four querying dimensions, which makes it easy-to-use and highly expressive.
A recurrent theme in the formal foundations of XChangeEQ is that, despite the fundamental differences between traditional database queries and event queries, many well-known results from databases and logic programming are, with some importance changes, applicable to event queries. Declarative semantics for XChangeEQ are given as a (Tarski-style) model theory with accompanying fixpoint theory. This approach accounts well for (1) data in events and (2) deductive rules defining new events from existing ones, two aspects often neglected in previous work of semantics of EQLs.
For the evaluation of event queries, this work introduces operational semantics based on an extended and tailored form of relational algebra and query plans with materialization points. Materialization points account for storing and maintaining information about those received events that are relevant for, i.e., can contribute to, future query answers, as well as for an incremental evaluation that avoids recomputing certain intermediate results. Efficient state maintenance in incremental evaluation is approached by "differentiating" algebra expressions, i.e., by deriving expressions for computing only the changes to materialization points. Knowing how long an event is relevant is a prerequisite for performing garbage collection during event query evaluation and also of central importance for developing cost-based query planners. To this end, this thesis introduces a notion of relevance of events (to a given query plan) and develops methods for determining temporal relevance, a particularly useful form based on time-related information
Applying Formal Methods to Networking: Theory, Techniques and Applications
Despite its great importance, modern network infrastructure is remarkable for
the lack of rigor in its engineering. The Internet which began as a research
experiment was never designed to handle the users and applications it hosts
today. The lack of formalization of the Internet architecture meant limited
abstractions and modularity, especially for the control and management planes,
thus requiring for every new need a new protocol built from scratch. This led
to an unwieldy ossified Internet architecture resistant to any attempts at
formal verification, and an Internet culture where expediency and pragmatism
are favored over formal correctness. Fortunately, recent work in the space of
clean slate Internet design---especially, the software defined networking (SDN)
paradigm---offers the Internet community another chance to develop the right
kind of architecture and abstractions. This has also led to a great resurgence
in interest of applying formal methods to specification, verification, and
synthesis of networking protocols and applications. In this paper, we present a
self-contained tutorial of the formidable amount of work that has been done in
formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial
Transactions in dynamic reactive environments
Most of today’s systems, especially when related to the Web or to multi-agent systems,
are not standalone or independent, but are part of a greater ecosystem, where they
need to interact with other entities, react to complex changes in the environment, and
act both over its own knowledge base and on the external environment itself. Moreover,
these systems are clearly not static, but are constantly evolving due to the execution of self updates or external actions. Whenever actions and updates are possible, the need to ensure properties regarding the outcome of performing such actions emerges. Originally purposed in the context of databases, transactions solve this problem by guaranteeing atomicity, consistency, isolation and durability of a special set of actions. However, current transaction solutions fail to guarantee such properties in dynamic environments, since they cannot combine transaction execution with reactive features, or with the execution of actions over domains that the system does not completely control (thus making rolling back a non-viable proposition). In this thesis, we investigate what and how transaction
properties can be ensured over these dynamic environments. To achieve this goal, we provide logic-based solutions, based on Transaction Logic, to precisely model and execute transactions in such environments, and where knowledge bases can be defined by
arbitrary logic theories.Fundação para a Ciência e a Tecnologia (FCT) - grant SFRH/BD/64038/2009, and conceived
within project ERRO (PTDC/EIA-CCO/121823/2010
Fundamental Approaches to Software Engineering
This open access book constitutes the proceedings of the 23rd International Conference on Fundamental Approaches to Software Engineering, FASE 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 23 full papers, 1 tool paper and 6 testing competition papers presented in this volume were carefully reviewed and selected from 81 submissions. The papers cover topics such as requirements engineering, software architectures, specification, software quality, validation, verification of functional and non-functional properties, model-driven development and model transformation, software processes, security and software evolution
Semantic search and composition in unstructured peer-to-peer networks
This dissertation focuses on several research questions in the area of semantic search and composition in unstructured peer-to-peer (P2P) networks. Going beyond the state of the art, the proposed semantic-based search strategy S2P2P offers a novel path-suggestion based query routing mechanism, providing a reasonable tradeoff between search performance and network traffic overhead. In addition, the first semantic-based data replication scheme DSDR is proposed. It enables peers to use semantic information to select replica numbers and target peers to address predicted future demands. With DSDR, k-random search can achieve better precision and recall than it can with a near-optimal non-semantic replication strategy. Further, this thesis introduces a functional automatic semantic service composition method, SPSC. Distinctively, it enables peers to jointly compose complex workflows with high cumulative recall but low network traffic overhead, using heuristic-based bidirectional haining and service memorization mechanisms. Its query branching method helps to handle dead-ends in a pruned search space. SPSC is proved to be sound and a lower bound of is completeness is given. Finally, this thesis presents iRep3D for semantic-index based 3D scene selection in P2P search. Its efficient retrieval scales to answer hybrid queries involving conceptual, functional and geometric aspects. iRep3D outperforms previous representative efforts in terms of search precision and efficiency.Diese Dissertation bearbeitet Forschungsfragen zur semantischen Suche und Komposition in unstrukturierten Peer-to-Peer Netzen(P2P). Die semantische Suchstrategie S2P2P verwendet eine neuartige Methode zur Anfrageweiterleitung basierend auf Pfadvorschlägen, welche den Stand der Wissenschaft übertrifft. Sie bietet angemessene Balance zwischen Suchleistung und Kommunikationsbelastung im Netzwerk. Außerdem wird das erste semantische System zur Datenreplikation genannt DSDR vorgestellt, welche semantische Informationen berücksichtigt vorhergesagten zukünftigen Bedarf optimal im P2P zu decken. Hierdurch erzielt k-random-Suche bessere Präzision und Ausbeute als mit nahezu optimaler nicht-semantischer Replikation. SPSC, ein automatisches Verfahren zur funktional korrekten Komposition semantischer Dienste, ermöglicht es Peers, gemeinsam komplexe Ablaufpläne zu komponieren. Mechanismen zur heuristischen bidirektionalen Verkettung und Rückstellung von Diensten ermöglichen hohe Ausbeute bei geringer Belastung des Netzes. Eine Methode zur Anfrageverzweigung vermeidet das Feststecken in Sackgassen im beschnittenen Suchraum. Beweise zur Korrektheit und unteren Schranke der Vollständigkeit von SPSC sind gegeben. iRep3D ist ein neuer semantischer Selektionsmechanismus für 3D-Modelle in P2P. iRep3D beantwortet effizient hybride Anfragen unter Berücksichtigung konzeptioneller, funktionaler und geometrischer Aspekte. Der Ansatz übertrifft vorherige Arbeiten bezüglich Präzision und Effizienz
Ranked Retrieval in Uncertain and Probabilistic Databases
Ranking queries are widely used in data exploration, data analysis and decision
making scenarios. While most of the currently proposed ranking techniques focus
on deterministic data, several emerging applications involve data that are imprecise
or uncertain. Ranking uncertain data raises new challenges in query semantics and
processing, making conventional methods inapplicable. Furthermore, the interplay
between ranking and uncertainty models introduces new dimensions for ordering query
results that do not exist in the traditional settings.
This dissertation introduces new formulations and processing techniques for ranking queries on uncertain data. The formulations are based on marriage of traditional ranking semantics with possible worlds semantics under widely-adopted uncertainty models. In particular, we focus on studying the impact of tuple-level and attribute-level uncertainty on the semantics and processing techniques of ranking queries.
Under the tuple-level uncertainty model, we introduce a processing framework leveraging the capabilities of relational database systems to recognize and handle data
uncertainty in score-based ranking. The framework encapsulates a state space model,
and efficient search algorithms that compute query answers by lazily materializing the
necessary parts of the space. Under the attribute-level uncertainty model, we give a new probabilistic ranking model, based on partial orders, to encapsulate the space of possible rankings originating from uncertainty in attribute values. We present a set of efficient query evaluation algorithms, including sampling-based techniques based on the theory of Markov chains and Monte-Carlo method, to compute query answers.
We build on our techniques for ranking under attribute-level uncertainty to support
rank join queries on uncertain data. We show how to extend current rank join methods
to handle uncertainty in scoring attributes. We provide a pipelined query operator
implementation of uncertainty-aware rank join algorithm integrated with sampling
techniques to compute query answers
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