Perla Velasco-Elizondo

Resolving Data Mismatches in End-User Compositions

Many domains such as scientific computing and neuroscience require end users to compose heterogeneous computational entities to automate their professional tasks. However, an issue that frequently hampers such composition is data-mismatches between computational entities. Although, many composition frameworks today provide support for data mismatch resolution through special-purpose data converters, end users still have to put significant effort in dealing with data mismatches, e.g., identifying the available converters and determining which of them meet their QoS expectations. In this paper we present an approach that eliminates this effort by automating the detection and resolution of data mismatches. Specifically, it uses architectural abstractions to automatically detect different types of data mismatches, model-generation techniques to fix those mismatches, and utility theory to decide the best fix based on QoS constraints. We illustrate our approach in the neuroscience domain where data-mismatches can be fixed in an efficient manner on the order of few seconds.

An architectural approach to end user orchestrations

Computations are pervasive across many domains, where end users have to compose various heterogeneous computational entities to perform professional activities. Service-Oriented Architecture (SOA) is a widely used mechanism that can support such forms of compositions as it allows heterogeneous systems to be wrapped as services that can then be combined with each other. However, current SOA orchestration languages require writing scripts that are typically too low-level for end users to write, being targeted at professional programmers and business analysts. To address this problem, this paper proposes a composition approach based on an end user specification style called SCORE. SCORE is an architectural style that uses high-level constructs that can be tailored for different domains and automatically translated into executable constructs by tool support. We demonstrate the use of SCORE in two domains - dynamic network analysis and neuroscience, where users are intelligence analysts and neuroscientists respectively, who use the architectural style based vocabulary in SCORE as a basis of their domain-specific compositions that can be formally analyzed.

Knowledge representation and information extraction for analysing architectural patterns

We examine time and recall of automated and manual pattern analysis.Time and recall were always better for the automated analysis.Recall decreased when analysing heterogeneous pattern descriptions. Today, many software architecture design methods consider the use of architectural patterns as a fundamental design concept. When making an effective pattern selection, software architects must consider, among other aspects, its impact on promoting or inhibiting quality attributes. However, for inexperienced architects, this task often requires significant time and effort. Some reasons of the former include: the number of existing patterns, the emergence of new patterns, the heterogeneity in the natural language descriptions used to define them and the lack of tools for automatic pattern analysis. In this paper we describe an approach, based on knowledge representation and information extraction, for analysing architectural pattern descriptions with respect to specific quality attributes. The approach is automated by computable model that works as a prototype tool. We focus on the performance quality attribute and, by performing experiments on a corpus of patterns with forty-five architects of varying levels of experience, demonstrate that the proposed approach increases recall and reduces analysis time compared to manual analysis.

Automated Configuration of Monitoring Systems in an Immutable Infrastructure

Automated monitoring of Information Technology resources allows for the treatment of issues relating to availability, capacity, and other quality requirements. Currently, the use of monitoring systems in immutable infrastructures requires manually updating configurations every time a new server is launched, which is often time consuming and error prone. In this work, we propose a process to automate the configuration of monitoring systems in an immutable infrastructure. The process works for monitoring daemon services (Although Monit has the ability to monitor many other aspects of operating systems, this article only exposes the automation of the configuration of services or processes.) running in Debian-based operating systems and involves the use of technologies such as Ansible, Monit, and Slack. In contrast to manually updating configurations, the main advantages of the proposed method are: a reduction in time and user-friendliness when configuring the monitoring system.

Recuperación de información a través del índice invertido en Be Intelligent

espanolLos avances en el almacenamiento de informacion han producido un aumento significativo de las colecciones de documentos digitales. La informacion contenida en estas colecciones es vital para la toma de decisiones, de manera que almacenar, indexar y recuperar informacion especifica de estas colecciones es clave en las organizaciones, como lo establece el concepto de “busqueda empresarial”. Sin embargo, con la informacion almacenada en diferentes medios y formatos de archivo, la recuperacion es una tarea compleja que los sistemas basados en palabras clave no resuelven completamente. Para proporcionar una solucion a la administracion de documentos digitales de ADD Intelligence in Aviation, se desarrollo el sistema Be Intelligent que utiliza un indice invertido para indexar y recuperar facilmente los contenidos de documentos que satisfacen una consulta hecha en lenguaje natural. De esta manera se reduce el tiempo para encontrar la informacion que la empresa necesita durante la inspeccion de aeronaves. EnglishAdvances in information storage have produced a significant rise of digital document collections. The information contained in these collections is vital to decision making, so store, index and recover specific information from these collections is key in organizations, as “enterprise search” concept establishes. However, with information stored in different media and file formats, retrieval is a complex task that systems based on keywords do not completely solve. To offer a solution to store, index and recover digital document contents for ADD Intelligence in Aviation enterprise, Be Intelligent system was developed. Be Intelligent uses an inverted index to easily index and recover the contents of documents that satisfy a natural language query. As a result, time to find information needed to inspect airplanes, is reduced.

Towards Detecting MVC Architectural Smells

The term “bad smell” denotes a symptom of poor design or implementation that negatively impacts a software system’s properties. The research community has been actively identifying the characteristics of bad smells bad smells as well as developing approaches for detecting and fixing them. However, most of these efforts focus on smells that occur at code level: little consideration is given to smells that occur at higher levels of abstraction. This paper presents an initial effort to fill this gap by contributing to (i) the characterization of bad smells that are relevant to the Model-View-Controller architectural style and (ii) assessing the feasibility of their automatic detection using text analysis techniques in five systems, implemented with the Yii Framework. The obtained results show that the defined smells exist in practice and give some insight into which of them tend to occur more frequently. Regarding the automatic detection method, results show that it exhibits good performance and accuracy.

The Use of Inverted Index to Information Retrieval: ADD Intelligent in Aviation Case Study

Nowadays store, index and retrieve information from document collections is a complex but necessary task. For this reason, information retrieval is fundamental to decision-making in companies. The Be Intelligent system offers a solution to storing, indexing and retrieval of documents content of ADD Intelligent Aviation company. The system performs searches through natural language expressions, presents the user a list of results containing document name, page, author, date and paragraph with search terms highlighted. The list of documents that meets the search is ordered by the relevance between the expression in natural language and the content of a document. Be Intelligent system provides support for administration, indexing and retrieval of digital documents that the company uses during inspections of aircraft, reducing time to retrieve information.

Adding agile architecture practices to a Cyber-Physial System development

Competitive pressures force companies to develop products and services before their competitors. To achieve it, many of them have adopted agile methodologies such as Scrum that have proved to be more effective than traditional ones. However, despite successful applications of Scrum in various application domains, there is still a not clear understanding about how specific aspect of Cyber-Physical Systems (CPS) development should be tackled. In this article it has been shared the experience of a CPS development that used Scrum and the application of three specific agile software architecture practices to better support the build of a Minimum Viable Product (MVP). These practices can be classified as agile as they respect the Agile Manifestos principles.

Aggregate QoS Estimation of Service Compositions - An Analysis of Pattern-Oriented Approaches

For service-oriented systems the estimation of QoS is an important factor to determine whether a prospective service composition will meet the expectations of its final users. Many approaches to QoS estimation of service compositions have been proposed. However, not all of them allow the QoS of composition be estimated a priori and systematically from the QoS of its individual services. This is an important goal for many composition-based development approaches. This paper is a first effort to analyze QoS estimation approaches aligned to this goal. We revise approaches that use patterns as composition mechanisms as they enable the QoS of a service composition be estimated, a priori and systematically, by aggregating the QoS information of its constituent services. The result of this analysis offers insight in the main patterns and quality attributes addressed by these approaches as well as the adopted aggregation criteria. This will help us to achieve our ultimate goals of using these approaches on public services, assessing them for practicality, identifying gaps between theory and practice and possibilities for future work.

Answering Causal Questions and Developing Tool Support

People explore the world by asking questions about what is seen and felt. Thus, Question Answering is an attractive research area as a distinctive combination from a variety of disciplines, including artificial intelligence, information retrieval, information extraction, natural language processing and psychology. Psychological approaches focus more on theoretical aspects, whereas artificial intelligence, information retrieval, information extraction and natural language processing approaches investigate how practical Question Answering systems can be engineered.