28,420 research outputs found
Knowledge-based reusable software synthesis system
The Eli system, a knowledge-based reusable software synthesis system, is being developed for NASA Langley under a Phase 2 SBIR contract. Named after Eli Whitney, the inventor of interchangeable parts, Eli assists engineers of large-scale software systems in reusing components while they are composing their software specifications or designs. Eli will identify reuse potential, search for components, select component variants, and synthesize components into the developer's specifications. The Eli project began as a Phase 1 SBIR to define a reusable software synthesis methodology that integrates reusabilityinto the top-down development process and to develop an approach for an expert system to promote and accomplish reuse. The objectives of the Eli Phase 2 work are to integrate advanced technologies to automate the development of reusable components within the context of large system developments, to integrate with user development methodologies without significant changes in method or learning of special languages, and to make reuse the easiest operation to perform. Eli will try to address a number of reuse problems including developing software with reusable components, managing reusable components, identifying reusable components, and transitioning reuse technology. Eli is both a library facility for classifying, storing, and retrieving reusable components and a design environment that emphasizes, encourages, and supports reuse
A Framework for Agile Development of Component-Based Applications
Agile development processes and component-based software architectures are
two software engineering approaches that contribute to enable the rapid
building and evolution of applications. Nevertheless, few approaches have
proposed a framework to combine agile and component-based development, allowing
an application to be tested throughout the entire development cycle. To address
this problematic, we have built CALICO, a model-based framework that allows
applications to be safely developed in an iterative and incremental manner. The
CALICO approach relies on the synchronization of a model view, which specifies
the application properties, and a runtime view, which contains the application
in its execution context. Tests on the application specifications that require
values only known at runtime, are automatically integrated by CALICO into the
running application, and the captured needed values are reified at execution
time to resume the tests and inform the architect of potential problems. Any
modification at the model level that does not introduce new errors is
automatically propagated to the running system, allowing the safe evolution of
the application. In this paper, we illustrate the CALICO development process
with a concrete example and provide information on the current implementation
of our framework
Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores
Modern business applications and scientific databases call for inherently
dynamic data storage environments. Such environments are characterized by two
challenging features: (a) they have little idle system time to devote on
physical design; and (b) there is little, if any, a priori workload knowledge,
while the query and data workload keeps changing dynamically. In such
environments, traditional approaches to index building and maintenance cannot
apply. Database cracking has been proposed as a solution that allows on-the-fly
physical data reorganization, as a collateral effect of query processing.
Cracking aims to continuously and automatically adapt indexes to the workload
at hand, without human intervention. Indexes are built incrementally,
adaptively, and on demand. Nevertheless, as we show, existing adaptive indexing
methods fail to deliver workload-robustness; they perform much better with
random workloads than with others. This frailty derives from the inelasticity
with which these approaches interpret each query as a hint on how data should
be stored. Current cracking schemes blindly reorganize the data within each
query's range, even if that results into successive expensive operations with
minimal indexing benefit. In this paper, we introduce stochastic cracking, a
significantly more resilient approach to adaptive indexing. Stochastic cracking
also uses each query as a hint on how to reorganize data, but not blindly so;
it gains resilience and avoids performance bottlenecks by deliberately applying
certain arbitrary choices in its decision-making. Thereby, we bring adaptive
indexing forward to a mature formulation that confers the workload-robustness
previous approaches lacked. Our extensive experimental study verifies that
stochastic cracking maintains the desired properties of original database
cracking while at the same time it performs well with diverse realistic
workloads.Comment: VLDB201
Testing in the incremental design and development of complex products
Testing is an important aspect of design and development which consumes significant time and resource in many companies. However, it has received less research attention than many other activities in product development, and especially, very few publications report empirical studies of engineering testing. Such studies are needed to establish the importance of testing and inform the development of pragmatic support methods. This paper combines insights from literature study with findings from three empirical studies of testing. The case studies concern incrementally developed complex products in the automotive domain. A description of testing practice as observed in these studies is provided, confirming that testing activities are used for multiple purposes depending on the context, and are intertwined with design from start to finish of the development process, not done after it as many models depict. Descriptive process models are developed to indicate some of the key insights, and opportunities for further research are suggested
Alternative model-building for the study of socially interactive robots
In this discussion paper, we consider the potential merits of applying an alternative approach to model building (Empirical Modelling, also known as EM) in studying social aspects of human-robot interaction (HRI). The first section of the paper considers issues in modelling for HRI. The second introduces EM principles, outlining their potential application to modelling for HRI and its implications. The final section examines the prospects for applying EM to HRI from a practical perspective with reference to a simple case study and to existing models
Considering the User in the Wireless World
The near future promises significant advances in communication capabilities, but one of the keys to success is the capability understanding of the people with regards to its value and usage. In considering the role of the user in the wireless world of the future, the Human Perspective Working Group (WG1) of the Wireless World Research Forum has gathered input and developed positions in four important areas: methods, processes, and best practices for user-centered research and design; reference frameworks for modeling user needs within the context of wireless systems; user scenario creation and analysis; and user interaction technologies. This article provides an overview of WG1's work in these areas that are critical to ensuring that the future wireless world meets and exceeds the expectations of people in the coming decades
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