A pattern language to join early and late requirements

At present, the early phase of Requirements Engineering is a new research area in the Software Engineering field. This phase is concerned with the analysis of the organizational context in which a software system will be used. The models used in this phase allow us to describe an organizational environment using actors, goals, business processes and relationships. The late phase of Requirements Engineering, which is focused on representing the expected functionality of the software system, is more developed, so there are multiple techniques and tools to describe the software system that will be developed inside its operational environment. However, although there are methodologies which give separate support to each phase of requirements engineering, the development of methods to derive late requirements from the early requirements in a methodological way has been neglected in recent research works. This is due, in great measure, to the large difference between the abstraction levels of these two specification models. The objective of this paper is to propose a pattern language which allows us to reduce the abstraction level between early requirements and late requirements in a systematic way. This is done in an MDA-based approach.Facultad de Informátic

Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

Complex Event Processing (CEP)

Event-driven information systems demand a systematic and automatic processing of events. Complex Event Processing (CEP) encompasses methods, techniques, and tools for processing events while they occur, i.e., in a continuous and timely fashion. CEP derives valuable higher-level knowledge from lower-level events; this knowledge takes the form of so called complex events, that is, situations that can only be recognized as a combination of several events. 1 Application Areas Service Oriented Architecture (SOA), Event-Driven Architecture (EDA), cost-reductions in sensor technology and the monitoring of IT systems due to legal, contractual, or operational concerns have lead to a significantly increased generation of events in computer systems in recent years. This development is accompanied by a demand to manage and process these events in an automatic, systematic, and timely fashion. Important application areas for Complex Event Processing (CEP) are the following

On the Modeling of Correct Service Flows with BPEL4WS

Frameworks for composing Web Services offer a promising approach for realizing enterprise-wide and cross-organizational business applications. With BPEL4WS a powerful composition language exists. BPEL implementations allow orchestrating complex, stateful interactions among Web Services in a process-oriented way. One important task in this context is to ensure that respective flow specifications can be correctly processed, i.e., there will be no bad surprises (e.g., deadlocks, invocation of service operations with missing input data) at runtime. In this paper we subdivide BPEL schemes into different classes and discuss to which extent instances of these classes can be analyzed for the absence of control flow errors and inconsistencies. Altogether our work shall contribute to a more systematic evolution of the BPEL standard instead of overloading it with too many features

Patterns-based Evaluation of Open Source BPM Systems: The Cases of jBPM, OpenWFE, and Enhydra Shark

In keeping with the proliferation of free software development initiatives and the increased interest in the business process management domain, many open source workflow and business process management systems have appeared during the last few years and are now under active development. This upsurge gives rise to two important questions: what are the capabilities of these systems? and how do they compare to each other and to their closed source counterparts? i.e. in other words what is the state-of-the-art in the area?. To gain an insight into the area, we have conducted an in-depth analysis of three of the major open source workflow management systems - jBPM, OpenWFE and Enhydra Shark, the results of which are reported here. This analysis is based on the workflow patterns framework and provides a continuation of the series of evaluations performed using the same framework on closed source systems, business process modeling languages and web-service composition standards. The results from evaluations of the three open source systems are compared with each other and also with the results from evaluations of three representative closed source systems - Staffware, WebSphere MQ and Oracle BPEL PM, documented in earlier works. The overall conclusion is that open source systems are targeted more toward developers rather than business analysts. They generally provide less support for the patterns than closed source systems, particularly with respect to the resource perspective which describes the various ways in which work is distributed amongst business users and managed through to completion

Bilingual word recognition in a sentence context

This article provides an overview of bilingualism research on visual word recognition in isolation and in sentence context. Many studies investigating the processing of words out-of-context have shown that lexical representations from both languages are activated when reading in one language (language-nonselective lexical access). A newly developed research line asks whether language-nonselective access generalizes to word recognition in sentence contexts, providing a language cue and/or semantic constraint information for upcoming words. Recent studies suggest that the language of the preceding words is insufficient to restrict lexical access to words of the target language, even when reading in the native language. Eyetracking studies revealing the time course of word activation further showed that semantic constraint does not restrict language-nonselective access at early reading stages, but there is evidence that it has a relatively late effect. The theoretical implications for theories of bilingual word recognition are discussed in light of the Bilingual Interactive Activation + model (Dijkstra & Van Heuven, 2002)

AsterixDB: A Scalable, Open Source BDMS

AsterixDB is a new, full-function BDMS (Big Data Management System) with a feature set that distinguishes it from other platforms in today's open source Big Data ecosystem. Its features make it well-suited to applications like web data warehousing, social data storage and analysis, and other use cases related to Big Data. AsterixDB has a flexible NoSQL style data model; a query language that supports a wide range of queries; a scalable runtime; partitioned, LSM-based data storage and indexing (including B+-tree, R-tree, and text indexes); support for external as well as natively stored data; a rich set of built-in types; support for fuzzy, spatial, and temporal types and queries; a built-in notion of data feeds for ingestion of data; and transaction support akin to that of a NoSQL store. Development of AsterixDB began in 2009 and led to a mid-2013 initial open source release. This paper is the first complete description of the resulting open source AsterixDB system. Covered herein are the system's data model, its query language, and its software architecture. Also included are a summary of the current status of the project and a first glimpse into how AsterixDB performs when compared to alternative technologies, including a parallel relational DBMS, a popular NoSQL store, and a popular Hadoop-based SQL data analytics platform, for things that both technologies can do. Also included is a brief description of some initial trials that the system has undergone and the lessons learned (and plans laid) based on those early "customer" engagements