Improving software quality using an ontology-based approach

Ensuring quality in software development is a challenging process. The concepts of anti-pattern and bad code smells utilize the knowledge of reoccurring problems to improve the quality of current and future software development. Anti-patterns describe recurring bad design solutions while bad code smells describe source code that is error-free but difficult to understand and maintain. Code refactoring aims to remove bad code smells without changing a program’s functionality while improving program quality. There are metrics-based tools to detect a few bad code smells from source code; however, the knowledge and understanding of these indicators of low quality software are still insufficient to resolve many of the problems they represent. Minimal research addresses the relationships between or among bad code smells, anti-patterns and refactoring. In this research, we present a new ontology, Ontology for Anti-patterns, Bad Code Smells and Refactoring (OABR), to define the concepts and their relation properties. Such an ontological infrastructure encourages a common understanding of these concepts among the software community and provides more concise definitions that help to avoid overlapping and inconsistent description. It utilizes reasoning capabilities associated with ontology to analyze the software development domain and offer new insights into the domain. Software quality issues such as understandability and maintainability can be improved by identifying and resolving anti-patterns associated with code smells as well as preventing bad code smells before coding begins

Performance assessment of an architecture with adaptative interfaces for people with special needs

People in industrial societies carry more and more portable electronic devices (e.g., smartphone or console) with some kind of wireles connectivity support. Interaction with auto-discovered target devices present in the environment (e.g., the air conditioning of a hotel) is not so easy since devices may provide inaccessible user interfaces (e.g., in a foreign language that the user cannot understand). Scalability for multiple concurrent users and response times are still problems in this domain. In this paper, we assess an interoperable architecture, which enables interaction between people with some kind of special need and their environment. The assessment, based on performance patterns and antipatterns, tries to detect performance issues and also tries to enhance the architecture design for improving system performance. As a result of the assessment, the initial design changed substantially. We refactorized the design according to the Fast Path pattern and The Ramp antipattern. Moreover, resources were correctly allocated. Finally, the required response time was fulfilled in all system scenarios. For a specific scenario, response time was reduced from 60 seconds to less than 6 seconds

A Semantics-Rich Information Technology Architecture for Smart Buildings

The design of smart homes, buildings and environments currently suffers from a low maturity of available methodologies and tools. Technologies, devices and protocols strongly bias the design process towards vertical integration, and more flexible solutions based on separation of design concerns are seldom applied. As a result, the current landscape of smart environments is mostly populated by defectively designed solutions where application requirements (e.g., end-user functionality) are too often mixed and intertwined with technical requirements (e.g., managing the network of devices). A mature and effective design process must, instead, rely on a clear separation between the application layer and the underlying enabling technologies, to enable effective design reuse. The role of smart gateways is to enable this separation of concerns and to provide an abstracted view of available automation technology to higher software layers. This paper presents a blueprint for the information technology (IT) architecture of smart buildings that builds on top of established software engineering practices, such as model-driven development and semantic representation, and that avoids many pitfalls inherent in legacy approaches. The paper will also present a representative use case where the approach has been applied and the corresponding modeling and software tools

Method for Reusing and Re-engineering Non-ontological Resources for Building Ontologies

This thesis is focused on the reuse and possible subsequent re-engineering of knowledge resources, as opposed to custom-building new ontologies from scratch. The deep analysis of the state of the art has revealed that there are some methods and tools in the literature for transforming non-ontological resources into ontologies, but with some limitations: _ Most of the methods presented are based on ad-hoc transformations for the resource type, and the resource implementation. _ Only a few take advantage of the resource data model, an important artifact for the re-engineering process [GGPSFVT08]. _ There is no any integrated framework, method or corresponding tool, that considers the resources types, data models and implementations identified in an unified way. _ With regard to the transformation approach, the majority of the methods perform a TBox transformation, many others perform an ABox transformation and some perform a population. However, no method includes the possibility to perform the three transformation approaches. _ Regarding to the degree of automation, almost all the methods perform a semi-automatic transformation of the resource. _ According to the explicitation of the hidden semantics in the relations of the resource components, we can state that the methods that perform a TBox transformation make explicit the semantics in the relations of the resource components. Most of those methods identify subClassOf relations, others identify ad-hoc relations, and some identify partOf relations. However, only a few methods make explicit the three types of relations. _ With respect to how the methods make explicit the hidden semantics in the relations of the resource terms, we can say that three methods rely on the domain expert for making explicit the semantics, and two rely on an external resource, e.g., DOLCE ontology. Moreover, there are two methods that rely on external resources but not for making explicit the hidden semantics, but for finding out a proper ontology for populating it. _ According to the provision of the methodological guidelines, almost all the methods provide methodological guidelines for the transformation. However these guidelines are not finely detailed; for instance, they do not provide information about who is in charge of performing a particular activity/task, nor when that activity/task has to be carried out. _ With regard to the techniques employed, most of the methods do not mention them at all. Only a few methods specify techniques as transformation rules, lexico-syntactic patterns, mapping rules and natural language techniques. In this thesis we have provided a method and its technological support that rely on re-engineering patterns in order to speed up the ontology development process by reusing and re-engineering as much as possible available non-ontological resources. To achieve this overall goal, we have decomposed it in the following objectives: (1) the definition of methodological aspects related with the reuse of non-ontolo-gical resource for building ontologies; (2) the definition of methodological aspects related with the re-engineering of non-ontological resources for building ontologies; (3) the creation of a library of patterns for re-engineering nonontological resources into ontologies; and (4) the development of a software library that implements the suggestions given by the re-engineering patterns. Having in mind these goals, in this chapter we present how the open research problems identified in Chapter 2 are solved by the main thesis contributions. Then, we discuss the verification of our hypotheses, and finally we provide an outlook for the future work in those topics

Software Perfomance Assessment at Architectural Level: A Methodology and its Application

Las arquitecturas software son una valiosa herramienta para la evaluación de las propiedades cualitativas y cuantitativas de los sistemas en sus primeras fases de desarrollo. Conseguir el diseño adecuado es crítico para asegurar la bondad de dichas propiedades. Tomar decisiones tempranas equivocadas puede implicar considerables y costosos cambios en un futuro. Dichas decisiones afectarían a muchas propiedades del sistema, tales como su rendimiento, seguridad, fiabilidad o facilidad de mantenimiento. Desde el punto de vista del rendimiento software, la ingeniería del rendimiento del software (SPE) es una disciplina de investigación madura y comúnmente aceptada que propone una evaluación basada en modelos en las primeras fases del ciclo de vida de desarrollo software. Un problema en este campo de investigación es que las metodologías hasta ahora propuestas no ofrecen una interpretación de los resultados obtenidos durante el análisis del rendimiento, ni utilizan dichos resultados para proponer alternativas para la mejora de la propia arquitectura software. Hasta la fecha, esta interpretación y mejora requiere de la experiencia y pericia de los ingenieros software, en especial de expertos en ingeniería de prestaciones. Además, a pesar del gran número de propuestas para evaluar el rendimiento de sistemas software, muy pocos de estos estudios teóricos son posteriormente aplicados a sistemas software reales. El objetivo de esta tesis es presentar una metodología para el asesoramiento de decisiones arquitecturales para la mejora, desde el punto de vista de las prestaciones, de las sistemas software. La metodología hace uso del Lenguaje Unificado de Modelado (UML) para representar las arquitecturas software y de métodos formales, concretamente redes de Petri, como modelo de prestaciones. El asesoramiento, basado en patrones y antipatrones, intenta detectar los principales problemas que afectan a las prestaciones del sistema y propone posibles mejoras para mejoras dichas prestaciones. Como primer paso, estudiamos y analizamos los resultados del rendimiento de diferentes estilos arquitectónicos. A continuación, sistematizamos los conocimientos previamente obtenidos para proponer una metodología y comprobamos su aplicabilidad asesorando un caso de estudio real, una arquitectura de interoperabilidad para adaptar interfaces a personas con discapacidad conforme a sus capacidades y preferencias. Finalmente, se presenta una herramienta para la evaluación del rendimiento como un producto derivado del propio ciclo de vida software

Interoperabilnost uslužnog računarstva pomoću aplikacijskih programskih sučelja

Cloud computing paradigm is accepted by an increasing number of organizations due to significant financial savings. On the other hand, there are some issues that hinder cloud adoption. One of the most important problems is the vendor lock-in and lack of interoperability as its outcome. The ability to move data and application from one cloud offer to another and to use resources of multiple clouds is very important for cloud consumers.The focus of this dissertation is on the interoperability of commercial providers of platform as a service. This cloud model was chosen due to many incompatibilities among vendors and lack of the existing solutions. The main aim of the dissertation is to identify and address interoperability issues of platform as a service. Automated data migration between different providers of platform as a service is also an objective of this study.The dissertation has the following main contributions: first, the detailed ontology of resources and remote API operations of providers of platform as a service was developed. This ontology was used to semantically annotate web services that connect to providers remote APIs and define mappings between PaaS providers. A tool that uses defined semantic web services and AI planning technique to detect and try to resolve found interoperability problems was developed. The automated migration of data between providers of platform as a service is presented. Finally, a methodology for the detection of platform interoperability problems was proposed and evaluated in use cases.Zbog mogućnosti financijskih ušteda, sve veći broj poslovnih organizacija razmatra korištenje ili već koristi uslužno računarstvo. Međutim, postoje i problemi koji otežavaju primjenu ove nove paradigme. Jedan od najznačajnih problema je zaključavanje korisnika od strane pružatelja usluge i nedostatak interoperabilnosti. Za korisnike je jako važna mogućnost migracije podataka i aplikacija s jednog oblaka na drugi, te korištenje resursa od više pružatelja usluga.Fokus ove disertacije je interoperabilnost komercijalnih pružatelja platforme kao usluge. Ovaj model uslužnog računarstva je odabran zbog nekompatibilnosti različitih pružatelja usluge i nepostojanja postojećih rješenja. Glavni cilj disertacije je identifikacija i rješavanje problema interoperabilnosti platforme kao usluge. Automatizirana migracija podataka između različitih pružatelja platforme kao usluge je također jedan od ciljeva ovog istraživanja.Znanstveni doprinos ove disertacije je sljedeći: Najprije je razvijena detaljna ontologija resursa i operacija iz aplikacijskih programskih sučelja pružatelja platforme kao usluge. Spomenuta ontologija se koristi za semantičko označavanje web servisa koji pozivaju udaljene operacije aplikacijskih programskih sučelja pružatelja usluga, a sama ontologija definira i mapiranja između pružatelja platforme kao usluge. Također je razvijen alat koji otkriva i pokušava riješiti probleme interoperabilnosti korištenjem semantičkih web servisa i tehnika AI planiranja. Prikazana je i arhitektura za automatiziranu migraciju podataka između različitih pružatelja platforme kao usluge. Na kraju je predložena metodologija za otkrivanje problema interoperabilnosti koja je evaluirana pomoću slučajeva korištenja

Interoperabilnost uslužnog računarstva pomoću aplikacijskih programskih sučelja

Cloud computing paradigm is accepted by an increasing number of organizations due to significant financial savings. On the other hand, there are some issues that hinder cloud adoption. One of the most important problems is the vendor lock-in and lack of interoperability as its outcome. The ability to move data and application from one cloud offer to another and to use resources of multiple clouds is very important for cloud consumers.The focus of this dissertation is on the interoperability of commercial providers of platform as a service. This cloud model was chosen due to many incompatibilities among vendors and lack of the existing solutions. The main aim of the dissertation is to identify and address interoperability issues of platform as a service. Automated data migration between different providers of platform as a service is also an objective of this study.The dissertation has the following main contributions: first, the detailed ontology of resources and remote API operations of providers of platform as a service was developed. This ontology was used to semantically annotate web services that connect to providers remote APIs and define mappings between PaaS providers. A tool that uses defined semantic web services and AI planning technique to detect and try to resolve found interoperability problems was developed. The automated migration of data between providers of platform as a service is presented. Finally, a methodology for the detection of platform interoperability problems was proposed and evaluated in use cases.Zbog mogućnosti financijskih ušteda, sve veći broj poslovnih organizacija razmatra korištenje ili već koristi uslužno računarstvo. Međutim, postoje i problemi koji otežavaju primjenu ove nove paradigme. Jedan od najznačajnih problema je zaključavanje korisnika od strane pružatelja usluge i nedostatak interoperabilnosti. Za korisnike je jako važna mogućnost migracije podataka i aplikacija s jednog oblaka na drugi, te korištenje resursa od više pružatelja usluga.Fokus ove disertacije je interoperabilnost komercijalnih pružatelja platforme kao usluge. Ovaj model uslužnog računarstva je odabran zbog nekompatibilnosti različitih pružatelja usluge i nepostojanja postojećih rješenja. Glavni cilj disertacije je identifikacija i rješavanje problema interoperabilnosti platforme kao usluge. Automatizirana migracija podataka između različitih pružatelja platforme kao usluge je također jedan od ciljeva ovog istraživanja.Znanstveni doprinos ove disertacije je sljedeći: Najprije je razvijena detaljna ontologija resursa i operacija iz aplikacijskih programskih sučelja pružatelja platforme kao usluge. Spomenuta ontologija se koristi za semantičko označavanje web servisa koji pozivaju udaljene operacije aplikacijskih programskih sučelja pružatelja usluga, a sama ontologija definira i mapiranja između pružatelja platforme kao usluge. Također je razvijen alat koji otkriva i pokušava riješiti probleme interoperabilnosti korištenjem semantičkih web servisa i tehnika AI planiranja. Prikazana je i arhitektura za automatiziranu migraciju podataka između različitih pružatelja platforme kao usluge. Na kraju je predložena metodologija za otkrivanje problema interoperabilnosti koja je evaluirana pomoću slučajeva korištenja

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