29,957 research outputs found
Reasoning with qualitative preferences for optimization of component-based system development
A component-based system is a set of entities that work together in well-defined ways to satisfy a given requirement specified by the stakeholders for the system. This requirement can be modeled as a set of combinations of traits, which represent acceptable alternatives for providing the required functionality. A system satisfies its requirement if and only if it provides one of the required sets of traits in its entirety. Beyond the requirement, system stakeholders may also have preferences with respect to optional functionality that could be provided by a system, tradeoffs between non-functional properties, or other system design options. This work focuses on integrating support for both qualitative preference reasoning and formal verification into the component-based system design process in order to choose a set of components for the system that, when composed, will (1) satisfy the stakeholders\u27 requirement for the system and (2) provide a set of traits that is optimal with respect to the given preferences. Our primary research objective is to develop a generic, modular, end-to-end framework for developing component-based systems of any type which are correct according to the system requirement and most preferred with respect to the stakeholders\u27 preferences. Applications of the framework to problems in Web service composition, goal-oriented requirements engineering, and other areas will be discussed, along with future work toward integrating multi-stakeholder preference reasoning and partial satisfaction of traits into the framework
Metaheuristic models for decision support in the software construction process
En la actualidad, los ingenieros software no solo tienen la responsabilidad de construir
sistemas que desempe~nen una determinada funcionalidad, sino que cada vez
es más importante que dichos sistemas también cumplan con requisitos no funcionales
como alta disponibilidad, efciencia o seguridad, entre otros. Para lograrlo,
los ingenieros se enfrentan a un proceso continuo de decisión, pues deben estudiar
las necesidades del sistema a desarrollar y las alternativas tecnológicas existentes
para implementarlo. Todo este proceso debe estar encaminado a la obtención de
sistemas software de gran calidad, reutilizables y que faciliten su mantenimiento y
modificación en un escenario tan exigente y competitivo.
La ingeniería del software, como método sistemático para la construcción de software,
ha aportado una serie de pautas y tareas que, realizadas de forma disciplinada
y adaptadas al contexto de desarrollo, posibilitan la obtención de software de calidad.
En concreto, el proceso de análisis y diseño del software ha adquirido una gran
importancia, pues en ella se concibe la estructura del sistema, en términos de sus bloques
funcionales y las interacciones entre ellos. Es en este momento cuando se toman
las decisiones acerca de la arquitectura, incluyendo los componentes que la conforman,
que mejor se adapta a los requisitos, tanto funcionales como no funcionales,
que presenta el sistema y que claramente repercuten en su posterior desarrollo. Por
tanto, es necesario que el ingeniero analice rigurosamente las alternativas existentes,
sus implicaciones en los criterios de calidad impuestos y la necesidad de establecer
compromisos entre ellos. En este contexto, los ingenieros se guían principalmente
por sus habilidades y experiencia, por lo que dotarles de métodos de apoyo a la
decisión representaría un avance significativo en el área.
La aplicación de técnicas de inteligencia artificial en este ámbito ha despertado un
gran interés en los últimos años. En particular, la inteligencia artificial ha encontrado
en la ingeniería del software un ámbito de aplicación complejo, donde diferentes
técnicas pueden ayudar a conseguir la semi-automatización de tareas tradicionalmente
realizadas de forma manual. De la unión de ambas áreas surge la denominada
ingeniería del software basada en búsqueda, que propone la reformulación de las
actividades propias de la ingeniería del software como problemas de optimización.
A continuación, estos problemas podrían ser resueltos mediante técnicas de búsqueda
como las metaheurísticas. Este tipo de técnicas se caracterizan por explorar el
espacio de posibles soluciones de una manera \inteligente", a menudo simulando
procesos naturales como es el caso de los algoritmos evolutivos.
A pesar de ser un campo de investigación muy reciente, es posible encontrar propuestas
para automatizar una gran variedad de tareas dentro del ciclo de vida del software, como son la priorización de requisitos, la planifcación de recursos, la refactorización del código fuente o la generación de casos de prueba. En el ámbito del
análisis y diseño de software, cuyas tareas requieren de creatividad y experiencia,
conseguir una automatización completa resulta poco realista. Es por ello por lo que
la resolución de sus tareas mediante enfoques de búsqueda debe ser tratada desde la
perspectiva del ingeniero, promoviendo incluso la interacción con ellos. Además, el
alto grado de abstracción de algunas de sus tareas y la dificultad de evaluar cuantitativamente
la calidad de un diseño software, suponen grandes retos en la aplicación
de técnicas de búsqueda durante las fases tempranas del proceso de construcción de
software.
Esta tesis doctoral busca realizar aportaciones significativas al campo de la ingeniería
del software basada en búsqueda y, más concretamente, al área de la optimización
de arquitecturas software. Aunque se están realizando importantes avances en este
área, la mayoría de propuestas se centran en la obtención de arquitecturas de bajo
nivel o en la selección y despliegue de artefactos software ya desarrollados. Por tanto,
no existen propuestas que aborden el modelado arquitectónico a un nivel de abstracción elevado, donde aún no existe un conocimiento profundo sobre cómo será el
sistema y, por tanto, es más difícil asistir al ingeniero. Como problema de estudio,
se ha abordado principalmente la tarea del descubrimiento de arquitecturas software
basadas en componentes. El objetivo de este problema consiste en abstraer los bloques
arquitectónicos que mejor definen la estructura actual del software, así como
sus interacciones, con el fin de facilitar al ingeniero su posterior análisis y mejora.
Durante el desarrollo de esta tesis doctoral se ha explorado el uso de una gran variedad
de técnicas de búsqueda, estudiando su idoneidad y realizando las adaptaciones
necesarias para hacer frente a los retos mencionados anteriormente. La primera propuesta
se ha centrado en la formulación del descubrimiento de arquitecturas como
problema de optimización, abordando la representación computacional de los artefactos
software que deben ser modelados y definiendo medidas software para evaluar
su calidad durante el proceso de búsqueda. Además, se ha desarrollado un primer
modelo basado en algoritmos evolutivos mono-objetivo para su resolución, el cual ha
sido validado experimentalmente con sistemas software reales. Dicho modelo se caracteriza
por ser comprensible y
exible, pues sus componentes han sido diseñados
considerando estándares y herramientas del ámbito de la ingeniería del software,
siendo además configurable en función de las necesidades del ingeniero.
A continuación, el descubrimiento de arquitecturas ha sido tratado desde una perspectiva
multiobjetivo, donde varias medidas software, a menudo en con
icto, deben
ser simultáneamente optimizadas. En este caso, la resolución del problema se ha
llevado a cabo mediante ocho algoritmos del estado del arte, incluyendo propuestas recientes del ámbito de la optimización de muchos objetivos. Tras ser adaptados al
problema, estos algoritmos han sido comparados mediante un extenso estudio experimental
con el objetivo de analizar la ifnuencia que tiene el número y la elección
de las métricas a la hora de guiar el proceso de búsqueda. Además de realizar una
validación del rendimiento de estos algoritmos siguiendo las prácticas habituales
del área, este estudio aporta un análisis detallado de las implicaciones que supone
la optimización de múltiples objetivos en la obtención de modelos de soporte a la
decisión.
La última propuesta en el contexto del descubrimiento de arquitecturas software
se centra en la incorporación de la opinión del ingeniero al proceso de búsqueda.
Para ello se ha diseñado un mecanismo de interacción que permite al ingeniero indicar
tanto las características deseables en las soluciones arquitectónicas (preferencias
positivas) como aquellos aspectos que deben evitarse (preferencias negativas). Esta
información es combinada con las medidas software utilizadas hasta el momento,
permitiendo al algoritmo evolutivo adaptar la búsqueda conforme el ingeniero interactúe. Dadas las características del modelo, su validación se ha realizado con la
participación de ingenieros con distinta experiencia en desarrollo software, a fin de
demostrar la idoneidad y utilidad de la propuesta.
En el transcurso de la tesis doctoral, los conocimientos adquiridos y las técnicas
desarrolladas también han sido extrapolados a otros ámbitos de la ingeniería del
software basada en búsqueda mediante colaboraciones con investigadores del área.
Cabe destacar especialmente la formalización de una nueva disciplina transversal,
denominada ingeniería del software basada en búsqueda interactiva, cuyo fin es promover
la participación activa del ingeniero durante el proceso de búsqueda. Además,
se ha explorado la aplicación de algoritmos de muchos objetivos a un problema clásico
de la computación orientada a servicios, como es la composición de servicios web.Nowadays, software engineers have not only the responsibility of building systems that provide a particular functionality, but they also have to guarantee that these systems ful l demanding non-functional requirements like high availability, e ciency or security. To achieve this, software engineers face a continuous decision process, as they have to evaluate system needs and existing technological alternatives to implement it. All this process should be oriented towards obtaining high-quality and reusable systems, also making future modi cations and maintenance easier in such a competitive scenario. Software engineering, as a systematic method to build software, has provided a number of guidelines and tasks that, when done in a disciplinarily manner and properly adapted to the development context, allow the creation of high-quality software. More speci cally, software analysis and design has acquired great relevance, being the phase in which the software structure is conceived in terms of its functional blocks and their interactions. In this phase, engineers have to make decisions about the most suitable architecture, including its constituent components. Such decisions are made according to the system requirements, either functional or non-functional, and will have a great impact on its future development. Therefore, the engineer has to rigorously analyse existing alternatives, their implications on the imposed quality criteria and the need of establishing trade-o s among them. In this context, engineers are mostly guided by their own capabilities and experience, so providing them with decision support methods would represent a signi cant contribution. The application of arti cial intelligent techniques in this area has experienced a growing interest in the last years. Particularly, software engineering represents a complex application domain to arti cial intelligence, whose diverse techniques can help in the semi-automation of tasks traditionally performed manually. The union of both elds has led to the appearance of search-based software engineering, which proposes reformulating software engineering activities as optimisation problems. For their resolution, search techniques like metaheuristics can be then applied. This type of technique performs an \intelligent" exploration of the space of candidate solutions, often inspired by natural processes as happens with evolutionary algorithms. Despite the novelty of this research eld, there are proposals to automate a great variety of tasks within the software lifecycle, such as requirement prioritisation, resource planning, code refactoring or test case generation. Focusing on analysis and design, whose tasks require creativity and experience, trying to achieve full automation is not realistic. Therefore, solving design tasks by means of search approaches should be oriented towards the engineer's perspective, even promoting their interaction. Furthermore, design tasks are also characterised by a high level of abstraction and the di culty of quantitatively evaluating design quality. All these aspects represent key challenges for the application of search techniques in early phases of the software construction process. The aim of this Ph.D. Thesis is to make signi cant contributions in search-based software engineering and, specially, in the area of software architecture optimisation. Although it is an area in which signi cant progress is being done, most of the current proposals are focused on generating low-level architectures or selecting and deploying already developed artefacts. Therefore, there is a lack of proposals dealing with architectural modelling at a high level of abstraction. At this level, engineers do not have a deep understanding of the system yet, meaning that assisting them is even more di cult. As case study, the discovery of component-based software architectures has been primary addressed. The objective for this problem consists in the abstraction of the architectural blocks, and their interactions, that best de ne the current structure of a software system. This can be viewed as the rst step an engineer would perform in order to further analyse and improve the system architecture. In this Ph.D. Thesis, the use of a great variety of search techniques has been explored. The suitability of these techniques has been studied, also making the necessary adaptations to cope with the aforementioned challenges. A rst proposal has been focused on the formulation of software architecture discovery as an optimisation problem, which consists in the computational representation of its software artefacts and the de nition of software metrics to evaluate their quality during the search process. Moreover, a single-objective evolutionary algorithm has been designed for its resolution, which has been validated using real software systems. The resulting model is comprehensible and exible, since its components have been designed under software engineering standards and tools and are also con gurable according to engineer's needs. Next, the discovery of software architectures has been tackled from a multi-objective perspective, in which several software metrics, often in con ict, have to be simultaneously optimised. In this case, the problem is solved by applying eight state-of-theart algorithms, including some recent many-objective approaches. These algorithms have been adapted to the problem and compared in an extensive experimental study, whose purpose is to analyse the in uence of the number and combination of metrics when guiding the search process. Apart from the performance validation following usual practices within the eld, this study provides a detailed analysis of the practical
implications behind the optimisation of multiple objectives in the context of
decision support.
The last proposal is focused on interactively including the engineer's opinion in the
search-based architecture discovery process. To do this, an interaction mechanism
has been designed, which allows the engineer to express desired characteristics for
the solutions (positive preferences), as well as those aspects that should be avoided
(negative preferences). The gathered information is combined with the software
metrics used until the moment, thus making possible to adapt the search as the
engineer interacts. Due to the characteristics of the proposed model, engineers of
di erent expertise in software development have participated in its validation with
the aim of showing the suitability and utility of the approach.
The knowledge acquired along the development of the Thesis, as well as the proposed
approaches, have also been transferred to other search-based software engineering
areas as a result of research collaborations. In this sense, it is worth noting the
formalisation of interactive search-based software engineering as a cross-cutting discipline,
which aims at promoting the active participation of the engineer during the
search process. Furthermore, the use of many-objective algorithms has been explored
in the context of service-oriented computing to address the so-called web service
composition problem
Developing front-end Web 2.0 technologies to access services, content and things in the future Internet
The future Internet is expected to be composed of a mesh of interoperable web services accessible from all over the web. This approach has not yet caught on since global user?service interaction is still an open issue. This paper states one vision with regard to next-generation front-end Web 2.0 technology that will enable integrated access to services, contents and things in the future Internet. In this paper, we illustrate how front-ends that wrap traditional services and resources can be tailored to the needs of end users, converting end users into prosumers (creators and consumers of service-based applications). To do this, we propose an architecture that end users without programming skills can use to create front-ends, consult catalogues of resources tailored to their needs, easily integrate and coordinate front-ends and create composite applications to orchestrate services in their back-end. The paper includes a case study illustrating that current user-centred web development tools are at a very early stage of evolution. We provide statistical data on how the proposed architecture improves these tools. This paper is based on research conducted by the Service Front End (SFE) Open Alliance initiative
Quantifiable non-functional requirements modeling and static verification for web service compositions
As service oriented architectures have become more widespread in industry, many complex web services are assembled using independently developed modular services from different vendors. Although the functionalities of the composite web services are ensured during the composition process, the non-functional requirements (NFRs) are often ignored in this process. Since quality of services plays a more and more important role in modern service-based systems, there is a growing need for effective approaches to verifying that a composite web service not only offers the required functionality but also satisfies the desired NFRs.
Current approaches to verifying NFRs of composite services (as opposed to individual services) remain largely ad-hoc and informal in nature. This is especially problematic for high-assurance composite web services. High-assurance composite web services are those composite web services with special concern on critical NFRs such as security, safety and reliability. Examples of such applications include traffic control, medical decision support and the coordinated response systems for civil emergencies. The latter serves to motivate and illustrate the work described here.
In this dissertation we develop techniques for ensuring that a composite service meets the user-specified NFRs expressible as hard constraints, e.g., the messages of
particular operations must be authenticated. We introduce an automata-based framework for verifying that a composite service satisfies the desired NFRs based on the known guarantees regarding the non-functional properties of the component services. This automata-based model is able to represent NFRs that are hard, quantitative constraints on the composite web services. This model addresses two issues previously not handled in the modeling and verification of NFRs for composite web services: (1) the scope of the NFRs and (2) consistency checking of multiple NFRs.
A scope of a NFR on a web service composition is the effective range of the NFR on the sub-workflows and modular services of the web service composition. It allows more precise description of a NFR constraint and more efficient verification. When multiple NFRs exist and overlap in their scopes, consistency checking is necessary to avoid wasted verification efforts on conflicting constraints. The approach presented here captures scope information in the model and uses it to check the consistency of multiple NFRs prior to the static verification of web service compositions. We illustrate how our approach can be used to verify security requirements for an Emergency Management System.
We then focus on families of highly-customizable, composed web services where repeated verification of similar sets of NFRs can waste computation resources. We introduce a new approach to extend software product line engineering techniques to the web service composition domain. The resulting technique uses a partitioning similar to that between domain engineering and application engineering in the product-line context. It specifies the options that the user can select and constructs the resulting web service
compositions. By first creating a web-service composition search space that satisfies the common requirements and then querying the search space as the user makes customization decisions, the technique provides a more efficient way to verify customizable web services. A decision model, illustrated with examples from the emergency-response application, is created to interact with the customers and ensure the consistency of their specifications. The capability to reuse the composition search space is shown to improve the quality of the composite services and reduce the cost of re-verifying the same compositions. By distinguishing the commonalities and the variabilities of the web services, we divide the web composition into two stages: the preparation stage (to construct all commonalities) and the customization stage (to choose optional and alternative features). We thus draw most of the computation overhead into the first stage during the design in order to enable improved runtime efficiency during the second stage.
A simulation platform was constructed to conduct experiments on the two verification approaches and three strategies introduced in this dissertation. The results of these experiments were analyzed to show the advantage of our automaton-based model in its verification efficiency with scoping information. We have shown how to choose the most efficient verification strategy from the three strategies of verifying multiple NFRs introduced in this dissertation under different circumstances. The results indicate that the software product line approach has significant efficiency improvement over traditional on-demand verification for highly customizable web service compositions
Representing and reasoning with qualitative preferences for compositional systems
Many applications call for techniques for representing and reasoning about preferences, i.e., relative desirability over a set of alternatives. Preferences over the alternatives are typically derived from preferences with respect to the various attributes of the alternatives (e.g., a student\u27s preference for one course over another may be influenced by his preference for the topic, the time of the day when the course is offered, etc.). Such preferences are often qualitative and conditional. When the alternatives are expressed as tuples of valuations of the relevant attributes, preferences between alternatives can often be expressed in the form of (a) preferences over the values of each attribute, and (b) relative importance of certain attributes over others. An important problem in reasoning with multi-attribute qualitative preferences is dominance testing, i.e., to find if one alternative (assignment to all attributes) is preferred over another. This problem is hard (PSPACE-complete) in general for well known qualitative conditional preference languages such as TCP-nets.
We provide two practical approaches to dominance testing. First, we study a restricted unconditional preference language, and provide a dominance relation that can be computed in polynomial time by evaluating the satisfiability of an appropriately constructed logic formula. Second, we show how to reduce dominance testing for TCP-nets to reachability analysis in an induced preference graph. We provide an encoding of TCP-nets in the form of a Kripke structure for CTL. We show how to compute dominance using NuSMV, a model checker for CTL.
We address the problem of identifying a preferred outcome in a setting where the outcomes or alternatives to be compared are composite in nature (i.e., collections of components that satisfy certain functional requirements). We define a dominance relation that allows us to compare collections of objects in terms of preferences over attributes of the objects that make up the collection, and show that the dominance relation is a strict partial order under certain conditions. We provide algorithms that use this dominance relation to identify only (sound), all (complete), or at least one (weakly complete) of the most preferred collections. We establish some key properties of the dominance relation and analyze the quality of solutions produced by the algorithms. We present results of simulation experiments aimed at comparing the algorithms, and report interesting conjectures and results that were derived from our analysis.
Finally, we show how the above formalism and algorithms can be used in preference-based service composition, substitution, and adaptation
Research and Development Workstation Environment: the new class of Current Research Information Systems
Against the backdrop of the development of modern technologies in the field
of scientific research the new class of Current Research Information Systems
(CRIS) and related intelligent information technologies has arisen. It was
called - Research and Development Workstation Environment (RDWE) - the
comprehensive problem-oriented information systems for scientific research and
development lifecycle support. The given paper describes design and development
fundamentals of the RDWE class systems. The RDWE class system's generalized
information model is represented in the article as a three-tuple composite web
service that include: a set of atomic web services, each of them can be
designed and developed as a microservice or a desktop application, that allows
them to be used as an independent software separately; a set of functions, the
functional filling-up of the Research and Development Workstation Environment;
a subset of atomic web services that are required to implement function of
composite web service. In accordance with the fundamental information model of
the RDWE class the system for supporting research in the field of ontology
engineering - the automated building of applied ontology in an arbitrary domain
area, scientific and technical creativity - the automated preparation of
application documents for patenting inventions in Ukraine was developed. It was
called - Personal Research Information System. A distinctive feature of such
systems is the possibility of their problematic orientation to various types of
scientific activities by combining on a variety of functional services and
adding new ones within the cloud integrated environment. The main results of
our work are focused on enhancing the effectiveness of the scientist's research
and development lifecycle in the arbitrary domain area.Comment: In English, 13 pages, 1 figure, 1 table, added references in Russian.
Published. Prepared for special issue (UkrPROG 2018 conference) of the
scientific journal "Problems of programming" (Founder: National Academy of
Sciences of Ukraine, Institute of Software Systems of NAS Ukraine
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