Keys and Armstrong databases in trees with restructuring

The definition of keys, antikeys, Armstrong-instances are extended to complex values in the presence of several constructors. These include tuple, list, set and a union constructor. Nested data structures are built using the various constructors in a tree-like fashion. The union constructor complicates all results and proofs significantly. The reason for this is that it comes along with non-trivial restructuring rules. Also, so-called counter attributes need to be introduced. It is shown that keys can be identified with closed sets of subattributes under a certain closure operator. Minimal keys correspond to closed sets minimal under set-wise containment. The existence of Armstrong databases for given minimal key systems is investigated. A sufficient condition is given and some necessary conditions are also exhibited. Weak keys can be obtained if functional dependency is replaced by weak functional dependency in the definition. It is shown, that this leads to the same concept. Strong keys are defined as principal ideals in the subattribute lattice. Characterization of antikeys for strong keys is given. Some numerical necessary conditions for the existence of Armstrong databases in case of degenerate keys are shown. This leads to the theory of bounded domain attributes. The complexity of the problem is shown through several examples

Weak functional dependencies on trees with restructuring

We present an axiomatisation for weak functional dependencies, i.e. disjunctions of functional dependencies, in the presence of several constructors for complex values. The investigated constructors capture records, sets, multisets, lists, disjoint union and optionality, i.e. the complex values are indeed trees. The constructors cover the gist of all complex value data models including object oriented databases and XML. Functional and weak functional dependencies are expressed on a lattice of subattributes, which even carries the structure of a Brouwer algebra as long as the union-constructor is absent. Its presence, however, complicates all results and proofs significantly. The reason for this is that the union-constructor causes non-trivial restructuring rules to hold. In particular, if either the set- or the the union-constructor is absent, a subset of the rules is complete for the implication of ordinary functional dependencies, while in the general case no finite axiomatisation for functional dependencies exists

Framework for dependency analysis of software artifacts

Cílem této práce je seznámit se s komponentově orientovanými systémy, s reprezentací a analýzou grafových dat a s existujícími metodami a nástroji pro statickou analýzu komponentově orientovaných systémů, které jsou vyvíjeny na Katedře informatiky a výpočetní techniky Západočeské univerzity v Plzni. Na základě zjištěných poznatků je výsledkem této práce návrh a implementace frameworku s důrazem na podporu vývoje ve více programovacích jazycích a na schopnost zpracovávat velké datové sady. Vytvořený framework pak může sloužit pro podporu výzkumu komponentově orientovaných systémů. Autor této práce navrhuje zobecnění a rozšíření frameworku pro analýzu závislostí softwarových artefaktů, který byl vytvořen v rámci diplomové práce M. Hotovce. Model ukládání dat frameworku byl rovněž analyzován s důrazem na grafové databáze. Jako řešení pro ukládání dat byla nakonec zvolena databáze ArangoDB. Dále byla implementována knihovna s jádrem frameworku v jazyce Java, které umožňuje vývoj nástrojů frameworku. Výsledná návrhová rozhodnutí umožňují využití frameworku v širší škále případů použití, jako je například extrakce a verifikace kompatibility komponent, což bylo demonstrováno replikací této funkcionality v nástroji frameworku vytvořeném v rámci této práce.ObhájenoThis thesis aims to familiarize with the component-based systems, graph data representation and analysis and with existing methods and tools for static analysis of component-based systems which are being developed at the Department of Computer Science at the University of West Bohemia in Pilsen, Czech Republic. Based on the findings, the result of this thesis is a framework design and implementation with emphasis on support for development in multiple programming languages and on the ability to process large datasets. The created framework then can serve to support the research of the component-based systems. The author of this thesis proposes generalization and extension of the framework for software artifacts dependency analysis which has been created as a part of M. Hotovec's master's thesis. The framework data storage model has also been analyzed with emphasis on graph databases. ArangoDB database has been eventually chosen as a storage solution and a core library in Java has been implemented to allow the development of framework tools. The resulting design decisions allows the framework to be used in broader range of use cases such as components compatibility extraction and verification, which has been demonstrated by replicating this functionality in a framework tool created as a part of this thesis

DataSpread: scaling spreadsheets using relational databases

Spreadsheet software is the tool of choice for ad-hoc tabular data management, manipulation, querying, and visualization with adoption by billions of users. However, spreadsheets are not scalable, unlike database systems. We develop DataSpread, a system that holistically unifies databases and spreadsheets with a goal to work with massive spreadsheets: DataSpread retains all of the advantages of spreadsheets, including ease of use, ad-hoc analysis and visualization capabilities, and a schema-free nature, while also adding the scalability and collaboration abilities of traditional relational databases. We design DataSpread with a spreadsheet front-end and a regular relational database back-end. To integrate spreadsheets and databases, in this thesis, we develop a storage and indexing engine for spreadsheet data. We first formalize and study the problem of representing and manipulating spreadsheet data within a relational database. We demonstrate that identifying the optimal representation is NP-Hard via a reduction from partitioning of rectangles; however, under certain reasonable assumptions, can be solved in PTIME. We develop a collection of mechanisms for representing spreadsheet data, and evaluate these representations on a workload of typical data manipulation operations. We augment our mechanisms with novel positionally-aware indexing structures that further improve performance. DataSpread can scale to billions of cells, returning results for common operations within seconds. Lastly, to motivate our research questions, we perform an extensive survey of spreadsheet use for ad-hoc tabular data management

Towards unifying spreadsheets with databases for ad-hoc interactive data management at scale

We are witnessing the increasing availability of data across a spectrum of domains, necessitating the interactive ad-hoc management and analysis of this data, in order to put it to use. Unfortunately, interactive ad-hoc management of very large datasets presents a host of challenges, ranging from performance to interface usability. This thesis introduces a new research direction of manipulation of large datasets using an interactive interface and makes several steps towards this direction. In particular, we develop DataSpread, a tool that enables users to work with arbitrary large datasets via a direct manipulation interface. DataSpread holistically unifies spreadsheets and relational databases to leverage the benefits of both. However, this holistic integration is not trivial due to the differences in the architecture and ideologies of the two paradigms: spreadsheets and databases. We have built a prototype of DataSpread, which, in addition to motivating the underlying challenges, demonstrates the feasibility and usefulness of this holistic integration. We focus on the following challenges encountered while developing DataSpread. (i) Representation—here, we address the challenges of flexibly representing ad-hoc spreadsheet data within a relational database; (ii) Indexing—here, we develop indexing data structures for supporting and maintaining access by position; (iii) Formula Computation—here, we introduce an asynchronous formula computation framework that addresses the challenge of ensuring consistency and interactivity at the same time; and (iv) Organization—here, we develop a framework to best organize data based on a workload, e.g., queries specified on the spreadsheet interface