729,988 research outputs found
Architectural reflection for software evolution
Software evolution is expensive. Lehman identifies several
problems associated with it: Continuous adaptation, increasing complexity, continuing growth, and declining quality. This paper proposes that a reflective software engineering environment will address these problems by employing languages and techniques from the software
architecture community.
Creating a software system will involve manipulating a collection of views, including low-level code views and high-level architectural views which will be tied together using reflection. This coupling will allow the development environment to automatically identify inconsistencies between the views, and support software engineers in managing architectures during evolution.
This paper proposes a research programme which will result in a software engineering environment which addresses problems of software evolution and the maintenance of consistency between architectural views of a software system
Algebraic incremental maintenance of XML views
International audienceMaterialized views can bring important performance benefits when querying XML documents. In the presence of XML document changes, materialized views need to be updated to faithfully reflect the changed document. In this work, we present an algebraic approach for propagating source updates to XML materialized views expressed in a powerful XML tree pattern formalism. Our approach differs from the state of the art in the area in two important ways. First, it relies on set-oriented, algebraic operations, to be contrasted with node-based previous approaches. Second, it exploits state-of-the-art features of XML stores and XML query evaluation engines, notably XML structural identifiers and associated structural join algorithms. We present algorithms for determining how updates should be propagated to views, and highlight the benefits of our approach over existing algorithms through a series of experiments
On the role of Prognostics and Health Management in advanced maintenance systems
The advanced use of the Information and Communication Technologies is evolving the way that systems are managed and maintained. A great number of techniques and methods have emerged in the light of these advances allowing to have an accurate and knowledge about the systems’ condition evolution and remaining useful life. The advances are recognized as outcomes of an innovative discipline, nowadays discussed under the term of Prognostics and Health Management (PHM). In order to analyze how maintenance will change by using PHM, a conceptual model is proposed built upon three views. The model highlights: (i) how PHM may impact the definition of maintenance policies; (ii) how PHM fits within the Condition Based Maintenance (CBM) and (iii) how PHM can be integrated into Reliability Centered Maintenance (RCM) programs. The conceptual model is the research finding of this review note and helps to discuss the role of PHM in advanced maintenance systems.EU Framework Programme Horizon 2020, 645733 - Sustain-Owner - H2020-MSCA-RISE-201
Panel on future challenges in modeling methodology
This panel paper presents the views of six researchers and practitioners of simulation modeling. Collectively we attempt to address a range of key future challenges to modeling methodology. It is hoped that the views of this paper, and the presentations made by the panelists at the 2004 Winter Simulation Conference will raise awareness and stimulate further discussion on the future of modeling methodology in areas such as modeling problems in business applications, human factors and geographically dispersed networks; rapid model development and maintenance; legacy modeling approaches; markup languages; virtual interactive process design and simulation; standards; and Grid computing
Materialized View Replacement using Markovs Analysis
Materialized view is used in large data centric applications to expedite
query processing. The efficiency of materialized view depends on degree of
result found against the queries over the existing materialized views.
Materialized views are constructed following different methodologies. Thus the
efficacy of the materialized views depends on the methodology based on which
these are formed. Construction of materialized views are often time consuming
and moreover after a certain time the performance of the materialized views
degrade when the nature of queries change. In this situation either new
materialized views could be constructed from scratch or the existing views
could be upgraded. Fresh construction of materialized views has higher time
complexity hence the modification of the existing views is a better
solution.Modification process of materialized view is classified under
materialized view maintenance scheme. Materialized view maintenance is a
continuous process and the system could be tuned to ensure a constant rate of
performance. If a materialized view construction process is not supported by
materialized view maintenance scheme that system would suffer from performance
degradation. In this paper a new materialized view maintenance scheme is
proposed using markovs analysis to ensure consistent performance. Markovs
analysis is chosen here to predict steady state probability over initial
probability
Efficient Incremental View Maintenance for Data Warehousing
Data warehousing and on-line analytical processing (OLAP) are essential elements for decision support applications. Since most OLAP queries are complex and are often executed over huge volumes of data, the solution in practice is to employ materialized views to improve query performance. One important issue for utilizing materialized views is to maintain the view consistency upon source changes. However, most prior work focused on simple SQL views with distributive aggregate functions, such as SUM and COUNT. This dissertation proposes to consider broader types of views than previous work. First, we study views with complex aggregate functions such as variance and regression. Such statistical functions are of great importance in practice. We propose a workarea function model and design a generic framework to tackle incremental view maintenance and answering queries using views for such functions. We have implemented this approach in a prototype system of IBM DB2. An extensive performance study shows significant performance gains by our techniques. Second, we consider materialized views with PIVOT and UNPIVOT operators. Such operators are widely used for OLAP applications and for querying sparse datasets. We demonstrate that the efficient maintenance of views with PIVOT and UNPIVOT operators requires more generalized operators, called GPIVOT and GUNPIVOT. We formally define and prove the query rewriting rules and propagation rules for such operators. We also design a novel view maintenance framework for applying these rules to obtain an efficient maintenance plan. Extensive performance evaluations reveal the effectiveness of our techniques. Third, materialized views are often integrated from multiple data sources. Due to source autonomicity and dynamicity, concurrency may occur during view maintenance. We propose a generic concurrency control framework to solve such maintenance anomalies. This solution extends previous work in that it solves the anomalies under both source data and schema changes and thus achieves full source autonomicity. We have implemented this technique in a data warehouse prototype developed at WPI. The extensive performance study shows that our techniques put little extra overhead on existing concurrent data update processing techniques while allowing for this new functionality
Briefing: Blue Carpet, Newcastle, UK: public realm design decision making from a user perspective
Public realm design decision making can be complex and variable with unpredictable results. Analysis of decision making, including the principles applied and the role of key players can help clarify ingredients for success. Crucially, assessment of the potential use of public realm space together with seeking various user views is essential. A public realm case study in Newcastle upon Tyne, UK, known as The Blue Carpet is analysed with reference to these factors. Conclusions indicate that employment of a city-wide public realm strategy, based on character analysis and urban design principles is likely to provide a sound basis for decision making. In addition, potential user views must be taken on board and project management requires a strong and consistent coordinator with a holistic remit covering design, use and maintenance
Secure Querying of Recursive XML Views: A Standard XPath-based Technique
Most state-of-the art approaches for securing XML documents allow users to
access data only through authorized views defined by annotating an XML grammar
(e.g. DTD) with a collection of XPath expressions. To prevent improper
disclosure of confidential information, user queries posed on these views need
to be rewritten into equivalent queries on the underlying documents. This
rewriting enables us to avoid the overhead of view materialization and
maintenance. A major concern here is that query rewriting for recursive XML
views is still an open problem. To overcome this problem, some works have been
proposed to translate XPath queries into non-standard ones, called Regular
XPath queries. However, query rewriting under Regular XPath can be of
exponential size as it relies on automaton model. Most importantly, Regular
XPath remains a theoretical achievement. Indeed, it is not commonly used in
practice as translation and evaluation tools are not available. In this paper,
we show that query rewriting is always possible for recursive XML views using
only the expressive power of the standard XPath. We investigate the extension
of the downward class of XPath, composed only by child and descendant axes,
with some axes and operators and we propose a general approach to rewrite
queries under recursive XML views. Unlike Regular XPath-based works, we provide
a rewriting algorithm which processes the query only over the annotated DTD
grammar and which can run in linear time in the size of the query. An
experimental evaluation demonstrates that our algorithm is efficient and scales
well.Comment: (2011
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