The thesis examines sequential mining approaches in the context of treatment recommendation for Gliblastoma (GBM) patients. GBM is the most lethal and biologically the most aggressive forms of brain tumor with median survival of approximately 1 year. A significant challenge in treating such rare forms of cancer is to make the best decision about optimal treatment plans for patients after standard of care. We tailor the existing sequential mining approaches by adding constraints to mine significant treatment options for cancer patients. The goal of the work is to analyze which treatment patterns play a role in prolonging the survival period of patients. In addition to the treatment analysis, we also discover some interesting clinical and genomic factors, which influence the survival period of patients. A treatment advisor tool has been developed based on the predictive features discovered. This tool is used to recommend treatment guidelines for a new patient based on the treatments meted out to other patients sharing clinical similarity with the new patient. The recommendations are also guided by the influential treatment patterns discovered in the study. The tool is based on the notion of patient similarity and uses a weighted function to calculate the same. The recommendations made by the tool may influence the clinicians to have the patients record some vital data on their own. With the progression of the treatment the clinicians may want to add to or modify some of the vital data elements previously decided to be recorded. In such a case a static database would not be very efficient to record the data since manual intervention is inevitable to incorporate the changes in the database structure. To solve this problem we have developed a dynamic database evolution framework, which uses a form based interface to interact with the clinician to add or modify the data elements in a database. The clinicians are flexible to create a new form for patients or modify existing forms based on a patient’s condition. As a result, appropriate schema modifications would be done in the relational database at the backend to incorporate these changes maintaining relational consistency.

Software developers adapt to the fast-moving nature of software systems with agile development techniques. However, database developers lack the tools and concepts to keep pace. Data, already existing in a running product, needs to be evolved accordingly, usually by manually written SQL scripts. A promising approach in database research is to use a declarative database evolution language, which couples both schema and data evolution into intuitive operations. Existing database evolution languages focus on usability but did not aim for completeness. However, this is an inevitable prerequisite for reasonable database evolution to avoid complex and error-prone workarounds. We argue that relational completeness is the feasible expressiveness for a database evolution language. Building upon an existing language, we introduce CoDEL. We define its semantic using relational algebra, propose a syntax, and show its relational completeness.

Orientadores: Gisele Busichia Baioco, Regina Lúcia de Oliveira Moraes / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Tecnologia / Made available in DSpace on 2018-08-24T15:26:05Z (GMT). No. of bitstreams: 1 Guedes_GustavoBartz_M.pdf: 5989312 bytes, checksum: 0e3053f8f1adcbcf13039b8caeb8a87e (MD5) Previous issue date: 2014 / Resumo: Sistemas de software evoluem ao longo do tempo devido a novos requisitos ou a alterações nos já existentes. As mudanças são ainda mais presentes nos métodos de desenvolvimento de software iterativos e incrementais, como os métodos ágeis, que pressupõem a entrega contínua de módulos operacionais de software. Os métodos ágeis, como o Scrum e a Programação Extrema, são baseados em aspectos gerenciais do projeto e em técnicas de codificação do sistema. Entretanto, mudanças nos requisitos provavelmente terão reflexo no esquema da base de dados, que deverá ser alterado para suportá-los. Quando o sistema se encontra em produção, alterações no esquema da base de dados são onerosas, pois é necessário manter a semântica dos dados em relação à aplicação. Portanto, este trabalho de mestrado apresenta o processo evolutivo de modularização de bases de dados, uma abordagem para projetar a base de dados de modo iterativo e incremental. A modularização é executada no projeto conceitual e amplia a capacidade de abstração do esquema de dados gerado facilitando as evoluções futuras. Por fim, foi desenvolvida uma ferramenta que automatiza o processo evolutivo de modularização de bases de dados, chamada de Evolutio DB Designer. Essa ferramenta permite modularizar o esquema da base de dados e gerar automaticamente o esquema relacional a partir dos módulos de bases de dados / Abstract: Software systems evolve through time due to new requirements or changing in the existing ones. The need for constant changes is even more present on the iterative and incremental software development methods, such as those based on the agile methodology, that demand continuous delivery of operational software modules. The agile development methods, like Scrum and Extreme Programming, are based on management aspects of the project and techniques for software coding. However, changes in the requirements will probably affect the database schema, which will have to be modified to accommodate them. In a production system, changes to the database schema are costly, because from the application¿s perspective the data semantics needs to be maintained. Therefore, the present work presents the evolutionary database modularization design process, an approach for the iterative and incremental design of the database. The modularization process is executed during the conceptual design improving the abstraction capacity of the generated data schema resulting in a graceful schema evolution. In addition, a tool that automates the evolutionary database modularization design process was developed, called Evolutio DB Designer. It allows the modular design of the database schema and automatically generates the relational data schema based on the database modules / Mestrado / Tecnologia e Inovação / Mestre em Tecnologia

Software developers adapt to the fast-moving nature of software systems with agile development techniques. However, database developers lack the tools and concepts to keep pace. Data, already existing in a running product, needs to be evolved accordingly, usually by manually written SQL scripts. A promising approach in database research is to use a declarative database evolution language, which couples both schema and data evolution into intuitive operations. Existing database evolution languages focus on usability but did not aim for completeness. However, this is an inevitable prerequisite for reasonable database evolution to avoid complex and error-prone workarounds. We argue that relational completeness is the feasible expressiveness for a database evolution language. Building upon an existing language, we introduce CoDEL. We define its semantic using relational algebra, propose a syntax, and show its relational completeness.

Modern agile software development methods allow to continuously evolve software systems by easily adding new features, fixing bugs, and adapting the software to changing requirements and conditions while it is continuously used by the users. A major obstacle in the agile evolution is the underlying database that persists the software system’s data from day one on. Hence, evolving the database schema requires to evolve the existing data accordingly—at this point, the currently established solutions are very expensive and error-prone and far from agile. In this thesis, we present InVerDa, a multi-schema-version database system to facilitate agile database development. Multi-schema-version database systems provide multiple schema versions within the same database, where each schema version itself behaves like a regular single-schema database. Creating new schema versions is very simple to provide the desired agility for database development. All created schema versions can co-exist and write operations are immediately propagated between schema versions with a best-effort strategy. Developers do not have to implement the propagation logic of data accesses between schema versions by hand, but InVerDa automatically generates it. To facilitate multi-schema-version database systems, we equip developers with a relational complete and bidirectional database evolution language (BiDEL) that allows to easily evolve existing schema versions to new ones. BiDEL allows to express the evolution of both the schema and the data both forwards and backwards in intuitive and consistent operations; the BiDEL evolution scripts are orders of magnitude shorter than implementing the same behavior with standard SQL and are even less likely to be erroneous, since they describe a developer’s intention of the evolution exclusively on the level of tables without further technical details. Having the developers’ intentions explicitly given in the BiDEL scripts further allows to create a new schema version by merging already existing ones. Having multiple co-existing schema versions in one database raises the need for a sophisticated physical materialization. Multi-schema-version database systems provide full data independence, hence the database administrator can choose a feasible materialization, whereby the multi-schema-version database system internally ensures that no data is lost. The search space of possible materializations can grow exponentially with the number of schema versions. Therefore, we present an adviser that releases the database administrator from diving into the complex performance characteristics of multi-schema-version database systems and merely proposes an optimized materialization for a given workload within seconds. Optimized materializations have shown to improve the performance for a given workload by orders of magnitude. We formally guarantee data independence for multi-schema-version database systems. To this end, we show that every single schema version behaves like a regular single-schema database independent of the chosen physical materialization. This important guarantee allows to easily evolve and access the database in agile software development—all the important features of relational databases, such as transaction guarantees, are preserved. To the best of our knowledge, we are the first to realize such a multi-schema-version database system that allows agile evolution of production databases with full support of co-existing schema versions and formally guaranteed data independence.

We introduce end-to-end support of co-existing schema versions within one database. While it is state of the art to run multiple versions of a continuously developed application concurrently, it is hard to do the same for databases. In order to keep multiple co-existing schema versions alive|which are all accessing the same data set|developers usually employ handwritten delta code (e.g. views and triggers in SQL). This delta code is hard to write and hard to maintain: if a database administrator decides to adapt the physical table schema, all handwritten delta code needs to be adapted as well, which is expensive and error-prone in practice. In this paper, we present InVerDa: developers use the simple bidirectional database evolution language BiDEL, which carries enough information to generate all delta code automatically. Without additional e_ort, new schema versions become immediately accessible and data changes in any version are visible in all schema versions at the same time. InVerDa also allows for easily changing the physical table design without a_ecting the availability of co-existing schema versions. This greatly increases robustness (orders of magnitude less lines of code) and allows for signi_cant performance optimization. A main contribution is the formal evaluation that each schema version acts like a common full-edged database schema independently of the chosen physical table design.

Software developers adapt to the fast-moving nature of software systems with agile development techniques. However, database developers lack the tools and concepts to keep the pace. Whenever the current database schema is evolved, the already existing data needs to be evolved as well. This is usually realized with manually written SQL scripts, which is error-prone and explains significant costs in software projects. A promising solution are declarative database evolution languages, which couple both schema and data evolution into intuitive operations. Existing database evolution languages focus on usability but do not strive for completeness. However, this is an inevitable prerequisite to avoid complex and error-prone workarounds. We present CODEL which is based on an existing language but is relationally complete. We precisely define its semantic using relational algebra, propose a syntax, and formally validate its relational completeness. Having a complete and comprehensive database evolution language facilitates valuable support throughout the whole evolution of a database. As an instance, we present VACO, a tool supporting developers with variant co-evolution. Given a variant schema derived from a core schema, VACO uses the richer semantics of CODEL to semi-automatically co-evolve this variant with the core.

Business organisations today are faced with the complex problem of dealing with evolution in their software information systems. This effectively concerns the accommodation and facilitation of change, in terms of both changing user requirements and changing technological requirements. An approach that uses the software development life-cycle as a vehicle to study the problem of evolution is adopted. This involves the stages of requirements analysis, system specification, design, implementation, and finally operation and maintenance. The problem of evolution is one requiring proactive as well as reactive solutions for any given application domain. Measuring evolvability in conceptual models and the specification of changing requirements are considered. However, even "best designs" are limited in dealing with unanticipated evolution, and require implementation phase paradigms that can facilitate an evolution correctly (semantic integrity), efficiently (minimal disruption of services) and consistently (all affected parts are consistent following the change). These are also discussed / Computing / M. Sc. (Information Systems)

Business organisations today are faced with the complex problem of dealing with evolution in their software information systems. This effectively concerns the accommodation and facilitation of change, in terms of both changing user requirements and changing technological requirements. An approach that uses the software development life-cycle as a vehicle to study the problem of evolution is adopted. This involves the stages of requirements analysis, system specification, design, implementation, and finally operation and maintenance. The problem of evolution is one requiring proactive as well as reactive solutions for any given application domain. Measuring evolvability in conceptual models and the specification of changing requirements are considered. However, even "best designs" are limited in dealing with unanticipated evolution, and require implementation phase paradigms that can facilitate an evolution correctly (semantic integrity), efficiently (minimal disruption of services) and consistently (all affected parts are consistent following the change). These are also discussed / Computing / M. Sc. (Information Systems)