XQTC: A Static Type-Checker for XQuery Using Backward Type Inference

We present a novel technique and a tool for static type-checking of XQuery programs. The tool looks for errors in the program by jointly analyzing the source code of the program, input and output schemas that respectively describe the sets of documents admissible as input and as output of the program. The crux and the novelty of our results reside in the joint use of backward type inference and a two-way logic to represent inferred tree type portions. This allowed us to design and implement a type-checker for XQuery which is more precise and supports a larger XQuery fragment compared to the approaches previously proposed in the literature; in particular compared to the only few actually implemented static type-checkers such as the one in Galax. The whole system uses compilers and a satisfiability solver for deciding containment for two-way regular tree expressions. Our tool takes an XQuery program and two schemas Sin and Sout as input. If the program is found incorrect, then it automatically generates a counter-example valid w.r.t. Sin and such that the program produces an invalid output w.r.t Sout. This counter-example can be used by the programmer to fix the program.Nous présentons une technique nouvelle et un outil pour le contrôle de type statique des programmes XQuery. L'outil recherche les erreurs dans le programme en analysant à la fois le code source du programme et les schémas d'entrée et de sortie qui décrivent respectivement les ensembles de documents admissibles en entrée et en sortie. L'originalité de nos résultats réside dans l'utilisation conjointe de l'inférence de type arrière et d'une logique avec programmes inverses pour représenter des fragments de types d'arbre. Cela nous a permis de concevoir et de réaliser un contrôleur de type pour XQuery qui est plus précis et supporte un fragment de XQuery plus large que les approches proposées précédemment dans la littérature, en particulier si on se réfère aux quelques contrôleurs de type statiques effectivement réalisés, tel que celui de Galax. L'ensemble du système utilise des compilateurs et un solveur pour décider de l'inclusion des expressions d'arbres régulières bi-directionnelles. Notre outil prend en entrée un programme XQuery et deux schémas Sin et Sout. Si le programme est reconnu incorrect, l'outil engendre automatiquement un contre-exemple valide vis-à-vis de Sin et tel que le programme produise un résultat invalide vis-à-vis de Sout. Ce contre-exemple peut alors être utilisé par le programmeur pour corriger son programme

Open archival information systems for database preservation

Tese de mestrado integrado. Engenharia Informática e Computação. Universidade do Porto. Faculdade de Engenharia. 201

Model-driven round-trip engineering of REST APIs

Les API web s'han convertit cada vegada més en un actiu clau per a les empreses, que n'han promogut la implementació i la integració en les seves activitats quotidianes. A la pràctica, la majoria d'aquestes API web són "REST-like", que significa que s'adhereixen parcialment a l'estil arquitectònic conegut com transferència d'estat representacional ('representational state transfer', REST en anglés). De fet, REST és un paradigma de disseny i no proposa cap estàndard. Com a conseqüència, tant desenvolupar com consumir API REST són tasques difícils i costoses per als proveïdors i clients de l'API. L'objectiu d'aquesta tesi és facilitar el disseny, la implementació, la composició i el consum de les API REST, basant-se en tècniques d'enginyeria dirigida per models ('model-driven engineering', MDE en anglés). Aquesta tesi proposa les contribucions següents: EMF-REST, APIDiscoverer, APITester, APIGenerator, i APIComposer. Aquestes contribucions constitueixen un ecosistema que avança l'estat de la qüestió al camp de l'enginyeria de programari automàtica per al desenvolupament i el consum de les API REST.Las API Web se han convertido en una pieza fundamental para un gran número de compañías, que han promovido su implementación e integración en las actividades cotidianas del negocio. En la práctica, estas API Web son "REST-like", lo que significa que se adhieren parcialmente al estilo arquitectónico conocido como transferencia de estado representacional ('representational state transfer', REST en inglés). De hecho, REST es un paradigma de diseño y no propone ningún estándar. Por ello, tanto el desarrollo como el consumo de API REST son tareas difíciles y que demandan mucho tiempo de los proveedores y los clientes de API. El objetivo de esta tesis es facilitar el diseño, la implementación, la composición y el consumo de API REST, apoyándose en el desarrollo de software dirigido por modelos (DSDM). Esta tesis propone las siguientes contribuciones: EMF-REST, APIDiscoverer, APITester, APIGenerator y APIComposer. Estas contribuciones constituyen un ecosistema que avanza el estado de la cuestión en el área de la ingeniería del software referida a la automatización de las tareas relacionadas con el desarrollo y consumo de API REST.Web APIs have become an increasingly key asset for businesses, and their implementation and integration in companies' daily activities has thus been on the rise. In practice, most of these Web APIs are "REST-like", meaning that they adhere partially to the Representational State Transfer (REST) architectural style. In fact, REST is a design paradigm and does not propose any standard, so developing and consuming REST APIs end up being challenging and time-consuming tasks for API providers and clients. Therefore, the aim of this thesis is to facilitate the design, implementation, composition and consumption of REST APIs by relying on Model-Driven Engineering (MDE). Likewise, it offers the following contributions: EMF-REST, APIDiscoverer, APITester, APIGenerator and APIComposer. Together, these contributions make up an ecosystem which advances the state of the art of automated software engineering for REST APIs

A framework for integrating and transforming between ontologies and relational databases

Bridging the gap between ontologies, expressed in the Web Ontology Language (OWL), and relational databases is a necessity for realising the Semantic Web vision. Relational databases are considered a good solution for storing and processing ontologies with a large amount of data. Moreover, the vast majority of current websites store data in relational databases, and therefore being able to generate ontologies from such databases is important to support the development of the Semantic Web. Most of the work concerning this topic has either (1) extracted an OWL ontology from an existing relational database that represents as exactly as possible the relational schema, using a limited range of OWL modelling constructs, or (2) extracted a relational database from an existing OWL ontology, that represents as much as possible the OWL ontology. By way of contrast, this thesis proposes a general framework for transforming and mapping between ontologies and databases, via an intermediate low-level Hyper-graph Data Model. The transformation between relational and OWL schemas is expressed using directional Both-As-View mappings, allowing a precise definition of the equivalence between the two schemas, hence data can be mapped back and forth between them. In particular, for a given OWL ontology, we interpret the expressive axioms either as triggers, conforming to the Open-World Assumption, that performs a forward-chaining materialisation of inferred data, or as constraints, conforming to the Closed-World Assumption, that performs a consistency checking. With regards to extracting ontologies from relational databases, we transform a relational database into an exact OWL ontology, then enhance it with rich OWL 2 axioms, using a combination of schema and data analysis. We then apply machine learning algorithms to rank the suggested axioms based on past users’ relevance. A proof-of-concept tool, OWLRel, has been implemented, and a number of well-known ontologies and databases have been used to evaluate the approach and the OWLRel tool.Open Acces

Empirically-Grounded Construction of Bug Prediction and Detection Tools

There is an increasing demand on high-quality software as software bugs have an economic impact not only on software projects, but also on national economies in general. Software quality is achieved via the main quality assurance activities of testing and code reviewing. However, these activities are expensive, thus they need to be carried out efficiently. Auxiliary software quality tools such as bug detection and bug prediction tools help developers focus their testing and reviewing activities on the parts of software that more likely contain bugs. However, these tools are far from adoption as mainstream development tools. Previous research points to their inability to adapt to the peculiarities of projects and their high rate of false positives as the main obstacles of their adoption. We propose empirically-grounded analysis to improve the adaptability and efficiency of bug detection and prediction tools. For a bug detector to be efficient, it needs to detect bugs that are conspicuous, frequent, and specific to a software project. We empirically show that the null-related bugs fulfill these criteria and are worth building detectors for. We analyze the null dereferencing problem and find that its root cause lies in methods that return null. We propose an empirical solution to this problem that depends on the wisdom of the crowd. For each API method, we extract the nullability measure that expresses how often the return value of this method is checked against null in the ecosystem of the API. We use nullability to annotate API methods with nullness annotation and warn developers about missing and excessive null checks. For a bug predictor to be efficient, it needs to be optimized as both a machine learning model and a software quality tool. We empirically show how feature selection and hyperparameter optimizations improve prediction accuracy. Then we optimize bug prediction to locate the maximum number of bugs in the minimum amount of code by finding the most cost-effective combination of bug prediction configurations, i.e., dependent variables, machine learning model, and response variable. We show that using both source code and change metrics as dependent variables, applying feature selection on them, then using an optimized Random Forest to predict the number of bugs results in the most cost-effective bug predictor. Throughout this thesis, we show how empirically-grounded analysis helps us achieve efficient bug prediction and detection tools and adapt them to the characteristics of each software project

(I) A Declarative Framework for ERP Systems(II) Reactors: A Data-Driven Programming Model for Distributed Applications

To those who can be swayed by argument and those who know they do not have all the answers This dissertation is a collection of six adapted research papers pertaining to two areas of research. (I) A Declarative Framework for ERP Systems: • POETS: Process-Oriented Event-driven Transaction Systems. The paper describes an ontological analysis of a small segment of the enterprise domain, namely the general ledger and accounts receivable. The result is an event-based approach to designing ERP systems and an abstract-level sketch of the architecture. • Compositional Specification of Commercial Contracts. The paper de-scribes the design, multiple semantics, and use of a domain-specific lan-guage (DSL) for modeling commercial contracts. • SMAWL: A SMAll Workflow Language Based on CCS. The paper show

PG-Keys: Keys for Property Graphs

International audienceWe report on a community effort between industry and academia to shape the future of property graph constraints. The standardization for a property graph query language is currently underway through the ISO Graph Query Language (GQL) project. Our position is that this project should pay close attention to schemas and constraints, and should focus next on key constraints. The main purposes of keys are enforcing data integrity and allowing the referencing and identifying of objects. Motivated by use cases from our industry partners, we argue that key constraints should be able to have different modes, which are combinations of basic restriction that require the key to be exclusive, mandatory, and singleton. Moreover, keys should be applicable to nodes, edges, and properties since these all can represent valid real-life entities. Our result is PG-Keys, a flexible and powerful framework for defining key constraints, which fulfills the above goals. PG-Keys is a design by the Linked Data Benchmark Council's Property Graph Schema Working Group, consisting of members from industry, academia, and ISO GQL standards group, intending to bring the best of all worlds to property graph practitioners. PG-Keys aims to guide the evolution of the standardization efforts towards making systems more useful, powerful, and expressive. CCS CONCEPTS • Information systems → Integrity checking; • Theory of computation → Data modeling; Database constraints theory