Suggestive Local Engine for SQL Developer: SLED

Information Technology (IT) industry recruits junior staff on regular basis. Most of the applications use databases to store or access the data. Structure Query Language (SQL) is used to communicate with database middleware. An expensive SQL statement may engage the data centers for longer time forcing the organizations to sellout high cost for data storage and maintenance. A tool is required for training the junior developers. This study proposes a Suggestive Local Engine for SQL Developer (SLED). It develops a warehouse using the optimized SQL statements collected from reputed software firms or expert team. This study uses the concept of data marts to grouped the data and frequent pattern search algorithm to calculate frequencies and support of patterns of SQLstatements. This system suggests the developers based on the common patterns of SQL statements used by those experts. It also warns the developers if their writing pattern maps to the outlier statement. This system helps all the junior developers in an organization and graduates in colleges or universities to practice with suggestions.Keywords: Suggestive engine optimized SQL, Data Warehous

The CHAIN-REDS Semantic Search Engine

e-Infrastructures, and in particular Data Repositories and Open Access Data Infrastructures, are essential platforms for e-Science and e-Research and are being built since several years both in Europe and the rest of the world to support diverse multi/inter-disciplinary Virtual Research Communities. So far, however, it is difficult for scientists to correlate papers to datasets used to produce them and to discover data and documents in an easy way. In this paper, the CHAINREDS project’s Knowledge Base and its Semantic Search Engine are presented, which attempt to address those drawbacks and contribute to the reproducibility of science

Meeting of the MINDS: an information retrieval research agenda

Since its inception in the late 1950s, the field of Information Retrieval (IR) has developed tools that help people find, organize, and analyze information. The key early influences on the field are well-known. Among them are H. P. Luhn's pioneering work, the development of the vector space retrieval model by Salton and his students, Cleverdon's development of the Cranfield experimental methodology, Spärck Jones' development of idf, and a series of probabilistic retrieval models by Robertson and Croft. Until the development of the WorldWideWeb (Web), IR was of greatest interest to professional information analysts such as librarians, intelligence analysts, the legal community, and the pharmaceutical industry

Grid service orchestration using the Business Process Execution Language (BPEL)

Modern scientific applications often need to be distributed across grids. Increasingly applications rely on services, such as job submission, data transfer or data portal services. We refer to such services as grid services. While the invocation of grid services could be hard coded in theory, scientific users want to orchestrate service invocations more flexibly. In enterprise applications, the orchestration of web services is achieved using emerging orchestration standards, most notably the Business Process Execution Language (BPEL). We describe our experience in orchestrating scientific workflows using BPEL. We have gained this experience during an extensive case study that orchestrates grid services for the automation of a polymorph prediction application

A Survey of Symbolic Execution Techniques

Many security and software testing applications require checking whether certain properties of a program hold for any possible usage scenario. For instance, a tool for identifying software vulnerabilities may need to rule out the existence of any backdoor to bypass a program's authentication. One approach would be to test the program using different, possibly random inputs. As the backdoor may only be hit for very specific program workloads, automated exploration of the space of possible inputs is of the essence. Symbolic execution provides an elegant solution to the problem, by systematically exploring many possible execution paths at the same time without necessarily requiring concrete inputs. Rather than taking on fully specified input values, the technique abstractly represents them as symbols, resorting to constraint solvers to construct actual instances that would cause property violations. Symbolic execution has been incubated in dozens of tools developed over the last four decades, leading to major practical breakthroughs in a number of prominent software reliability applications. The goal of this survey is to provide an overview of the main ideas, challenges, and solutions developed in the area, distilling them for a broad audience. The present survey has been accepted for publication at ACM Computing Surveys. If you are considering citing this survey, we would appreciate if you could use the following BibTeX entry: http://goo.gl/Hf5FvcComment: This is the authors pre-print copy. If you are considering citing this survey, we would appreciate if you could use the following BibTeX entry: http://goo.gl/Hf5Fv

OPEN-SOURCE IMPLEMENTATION FOR E-LEARNING SYSTEM IN INDONESIAN UNIVERSITIES

University and educational organizations have different strategies in deploying E-learning systems, one of which is the use of open-source e-learning systems. This research is designed to analyze the implementation of elearning system using open source in the Indonesian universities. The survey result shows that the majority of elearning system from public and private universities in Indonesia use open source which is integrated to the university portal. The integration is considered favorable as it generally improve the content quality of e-learning system. This survey shows that the most frequently used open system system in Indonesian university is moodle. The finding also indicates that the content of e-learning websites of the Indonesian Universities is relatively low in quality compared to world class universities e-learning website

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

Weaving aspects into web service orchestrations

Web Service orchestration engines need to be more open to enable the addition of new behaviours into service-based applications. In this paper, we illus- trate how, in a BPEL engine with aspect-weaving ca- pabilities, a process-driven application based on the Google Web Service can be dynamically adapted with new behaviours and hot-fixed to meet unforeseen post- deployment requirements. Business processes (the ap- plication skeletons) can be enriched with additional fea- tures such as debugging, execution monitoring, or an application-specific GUI. Dynamic aspects are also used on the processes themselves to tackle the problem of hot-fixes to long running processes. In this manner, composing a Web Service ’on-the-fly’ means weaving its choreography in- terface into the business process