Cyclic Datatypes modulo Bisimulation based on Second-Order Algebraic Theories

Cyclic data structures, such as cyclic lists, in functional programming are tricky to handle because of their cyclicity. This paper presents an investigation of categorical, algebraic, and computational foundations of cyclic datatypes. Our framework of cyclic datatypes is based on second-order algebraic theories of Fiore et al., which give a uniform setting for syntax, types, and computation rules for describing and reasoning about cyclic datatypes. We extract the "fold" computation rules from the categorical semantics based on iteration categories of Bloom and Esik. Thereby, the rules are correct by construction. We prove strong normalisation using the General Schema criterion for second-order computation rules. Rather than the fixed point law, we particularly choose Bekic law for computation, which is a key to obtaining strong normalisation. We also prove the property of "Church-Rosser modulo bisimulation" for the computation rules. Combining these results, we have a remarkable decidability result of the equational theory of cyclic data and fold.Comment: 38 page

Model-Based Testing of JBoss Drools

Technika testování založeného na modelu (MBT) využívá model chování systému k automatickému generování sady testů, čímž snižuje nákladnost testování oproti konvenčnímu manuálnímu vývoji a udržbě testů. Tato práce se zaměřuje na využití zvoleného MBT nástroje OSMO při testování reálného softwarového produktu. Konkrétně se o jedná kompilátor podnikových pravidel využívaný v systému Drools, který je spoluvyvíjený společností Red Hat. V práci je popsán způsob zavedení MBT přístupu s ohledem na jeho dobré přijetí komunitou vývojářů, dále pak vytvoření modelu možných vstupů testovaného kompilátoru a zhodnocení vytvořené testovací sady. Využití MBT přístupu vedlo k odhalení pěti nahlášených a tří potencionálních a dosud nehlášených chyb v testovaném kódu. Práce na příkladu shrnuje hlavní přednosti i praktické nedostatky využití MBT technik v praxi.Model-based testing (MBT) is using a model of expected behavior of the system to automatically generate a set of tests. It aims at reducing the testing cost when compared to the traditional testing techniques. This work focuses on testing a real-world software system using the selected MBT tool OSMO. The tested system is responsible for compiling business rules and it is one of the main components of the Drools platform, developed by Red Hat. The work describes the introduction of MBT considering the good reception from the community of developers, then the creation of compiler input models and evaluation of the newly created test suite. The usage of the MBT resulted in detection of five reported and three potential issues in the tested code. Using the Drools compiler example, the work summarizes the main strengths and also weaknesses of practical use of MBT techniques.

A JBI Information Object Engineering Environment Utilizing Metadata Fragments for Refining Searches on Semantically-Related Object Types

The Joint Battlespace Infosphere (JBI) architecture defines the Information Object (IO) as its basic unit of data. This research proposes an IO engineering methodology that will introduce componentized IO type development. This enhancement will improve the ability of JBI users to create and store IO type schemas, and query and subscribe to information objects, which may be semantically related by their inclusion of common metadata elements. Several parallel efforts are being explored to enable efficient storage and retrieval of IOs. Utilizing relational database access methods, applying a component-based IO type development concept, and exploiting XML inclusion mechanisms, this research improves the means by which a JBI can deliver related IO types to subscribers from a single query or subscription. The proposal of this new IO type architecture also integrates IO type versioning, type coercion, and namespacing standards into the methodology. The combined proposed framework provides a better means by which a JBI can deliver the right information to the right users at the right time

Context-Based Entity Matching for Big Data

In the Big Data era, where variety is the most dominant dimension, the RDF data model enables the creation and integration of actionable knowledge from heterogeneous data sources. However, the RDF data model allows for describing entities under various contexts, e.g., people can be described from its demographic context, but as well from their professional contexts. Context-aware description poses challenges during entity matching of RDF datasets—the match might not be valid in every context. To perform a contextually relevant entity matching, the specific context under which a data-driven task, e.g., data integration is performed, must be taken into account. However, existing approaches only consider inter-schema and properties mapping of different data sources and prevent users from selecting contexts and conditions during a data integration process. We devise COMET, an entity matching technique that relies on both the knowledge stated in RDF vocabularies and a context-based similarity metric to map contextually equivalent RDF graphs. COMET follows a two-fold approach to solve the problem of entity matching in RDF graphs in a context-aware manner. In the first step, COMET computes the similarity measures across RDF entities and resorts to the Formal Concept Analysis algorithm to map contextually equivalent RDF entities. Finally, COMET combines the results of the first step and executes a 1-1 perfect matching algorithm for matching RDF entities based on the combined scores. We empirically evaluate the performance of COMET on testbed from DBpedia. The experimental results suggest that COMET accurately matches equivalent RDF graphs in a context-dependent manner

Processing Analytical Queries in the AWESOME Polystore [Information Systems Architectures]

Modern big data applications usually involve heterogeneous data sources and analytical functions, leading to increasing demand for polystore systems, especially analytical polystore systems. This paper presents AWESOME system along with a domain-specific language ADIL. ADIL is a powerful language which supports 1) native heterogeneous data models such as Corpus, Graph, and Relation; 2) a rich set of analytical functions; and 3) clear and rigorous semantics. AWESOME is an efficient tri-store middle-ware which 1) is built on the top of three heterogeneous DBMSs (Postgres, Solr, and Neo4j) and is easy to be extended to incorporate other systems; 2) supports the in-memory query engines and is equipped with analytical capability; 3) applies a cost model to efficiently execute workloads written in ADIL; 4) fully exploits machine resources to improve scalability. A set of experiments on real workloads demonstrate the capability, efficiency, and scalability of AWESOME

Extensible metadata repository for information systems

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer ScienceInformation Systems are, usually, systems that have a strong integration component and some of those systems rely on integration solutions that are based on metadata (data that describes data). In that situation, there’s a need to deal with metadata as if it were “normal”information. For that matter, the existence of a metadata repository that deals with the integrity, storage, validity and eases the processes of information integration in the information system is a wise choice. There are several metadata repositories available in the market, but none of them is prepared to deal with the needs of information systems or is generic enough to deal with the multitude of situations/domains of information and with the necessary integration features. In the SESS project (an European Space Agency project), a generic metadata repository was developed, based on XML technologies. This repository provided the tools for information integration, validity, storage, share, import, as well as system and data integration, but it required the use of fix syntactic rules that were stored in the content of the XML files. This situation causes severe problems when trying to import documents from external data sources (sources unaware of these syntactic rules). In this thesis a metadata repository that provided the same mechanisms of storage, integrity, validity, etc, but is specially focused on easy integration of metadata from any type of external source (in XML format) and provides an environment that simplifies the reuse of already existing types of metadata to build new types of metadata, all this without having to modify the documents it stores was developed. The repository stores XML documents (known as Instances), which are instances of a Concept, that Concept defines a XML structure that validates its Instances. To deal with reuse, a special unit named Fragment, which allows defining a XML structure (which can be created by composing other Fragments) that can be reused by Concepts when defining their own structure. Elements of the repository (Instances,Concepts and Fragment) have an identifier based on (and compatible with) URIs, named Metadata Repository Identifier (MRI). Those identifiers, as well as management information(including relations) are managed by the repository, without the need to use fix syntactic rules, easing integration. A set of tests using documents from the SESS project and from software-house ITDS was used to successfully validate the repository against the thesis objectives of easy integration and promotion of reuse

Provenance-aware knowledge representation: A survey of data models and contextualized knowledge graphs

Expressing machine-interpretable statements in the form of subject-predicate-object triples is a well-established practice for capturing semantics of structured data. However, the standard used for representing these triples, RDF, inherently lacks the mechanism to attach provenance data, which would be crucial to make automatically generated and/or processed data authoritative. This paper is a critical review of data models, annotation frameworks, knowledge organization systems, serialization syntaxes, and algebras that enable provenance-aware RDF statements. The various approaches are assessed in terms of standard compliance, formal semantics, tuple type, vocabulary term usage, blank nodes, provenance granularity, and scalability. This can be used to advance existing solutions and help implementers to select the most suitable approach (or a combination of approaches) for their applications. Moreover, the analysis of the mechanisms and their limitations highlighted in this paper can serve as the basis for novel approaches in RDF-powered applications with increasing provenance needs

Formalization of the neuro-biological models for spike neurons.

When modelizing cortical neuronal maps (here spiking neuronal networks) within the scope of the FACETS project, researchers in neuro-science and computer-science use NeuroML, a XML language, to specify biological neuronal networks. These networks could be simulated either using analogue or event-based techniques. Specifications include : - parametric model specification - model equation symbolic definition - formalization of related semantic aspects (paradigms, ..) and they are used by "non-computer-scientists". In this context XML is used to specify data structures, not documents. The first version of NeuroML uses Java to map XML biological data which can be later simulated within GENESIS, NEURON, etc. The second version uses tools for handling XML data, as XSL, to transform an XML file. To allow NeuroML to be used intensively within the scope of the FACETS project, we will entirely analyse the software. First we are going to evaluate this software deeply in the Technical Report section. Then we will propose a prototype to write down NeuroML code easily

Survey over Existing Query and Transformation Languages

A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability of many current Semantic Web approaches to cope with data available in such diverging representation formalisms as XML, RDF, or Topic Maps. A common query language is the first step to allow transparent access to data in any of these formats. To further the understanding of the requirements and approaches proposed for query languages in the conventional as well as the Semantic Web, this report surveys a large number of query languages for accessing XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from all these areas. From the detailed survey of these query languages, a common classification scheme is derived that is useful for understanding and differentiating languages within and among all three areas