International Journal of Software Engineering and Knowledge Engineering

We tackle the problem of knowledge mining on the Web. In this paper, we propose MGKM algebraic system for iterative search documents sets, and then develop an approach to extract topics on the web with Multi-Granularity Knowledge Mining algorithm (MGKM). The proposed approach maps the data space of the original method to a vector space of sentence, improving the original DBCO algorithm. We outline the interface between our scheme and the current data Web, and show that, in contrast to the existing approaches, no exponential blowup is produced by the MGKM. Based on the experiments with real-world data sets of 310 users in three study sites, we demonstrate that knowledge mining in the proposed approach is efficient, especially for large-scale web learning resources. According to the user ratings data of four learning sites in the 150 days, the average rate of increase of user rating after the system is used reaches 25.18%.

Knowledge management (KM) in software engineering and software process improvement (SPI) are challenging. Most existing KM and SPI frameworks are too expensive to deploy or do not take an organization's specific needs or knowledge into consideration. There is thus a need for scalable improvement approaches that leverage knowledge already residing in the organizations.

This paper presents the Practice Selection Framework (PSF), an Experience Factory approach, enabling lightweight experience capture and use by utilizing postmortem reviews. Experiences gathered concern performance and applicability of practices used in the organization, gained from concluded projects. Project managers use these as decision support for selecting practices to use in future projects, enabling explicit knowledge transfer across projects and the development organization as a whole. Process managers use the experiences to determine if there is potential for improvement of practices used in the organization. This framework was developed and subsequently validated in industry to get feedback on usability and usefulness from practitioners. The validation consisted of tailoring and testing the framework using real data from the organization and comparing it to current practices used in the organization to ensure that the approach meets industry needs. The results from the validation are encouraging and the participants' assessment of PSF and particularly the tailoring developed was positive.

Unreliable component security hinders the development of component technology. Component security testing is rarely researched with comprehensive focus; several approaches or technologies for detecting vulnerabilities in component security have been proposed, but most are infeasible. A testing approach for component security, which is based on the chemical abstract machine, is proposed for detecting explicit and implicit component security vulnerabilities. We develop an extended chemical abstract machine model, called eCHAM, and generate a state transfer tree and testing sequence for components based on the proposed model. The model can help test the explicit security exceptions of components according to the testing approach of interface fault injection. Condition and state mutation algorithms for identifying implicit security exceptions are also proposed. Vulnerability testing reports are obtained according to the test results. Experiments were conducted in an integration testing platform to verify the applicability of the proposed approach. Results show that the approach is effective and practicable. The proposed approach can detect explicit and implicit security exceptions of components.

RDF is widely used as an ontology language for representing the metadata in Semantic Web, knowledge management system and E-commerce. Since ontologies model the knowledge in a particular domain, they may change over time. Furthermore, ontologies are usually developed and controlled in a distributed and collaborative way. Thus, it is very important to be able to manage multiple versions for RDF data. Earlier studies on RDF versions have focused on providing the accesses to different versions (i.e. snapshots) and computing the differences between those two versions. However, the existing approaches suffer from the space overhead for large scale data, since all snapshots should be redundantly kept in a repository. Moreover, it is very time consuming to compute the delta between two specific versions, which is very common in RDF applications. In this paper, we propose a framework for RDF version management in relational databases. It stores the original version and the deltas between two consecutive versions, thereby reducing the space requirement considerably. The other benefit of our approach is appropriate for change queries. On the flip side, in order to answer a query on a specific logical version, version should be constructed on the fly by applying the deltas between the original version and the logical version. This can slow down query performance. In order to overcome this, we propose a compression technique for deltas, called Aggregated Delta, to create a logical version directly rather than executing the sequence of deltas. An experimental study with real life RDF data sets shows our framework maintains multiple versions efficiently.

Nowadays, mobile devices have an increasing role in the generation and visualization of multimedia content. The issues raised by the management of multimedia content in mobile environments are mostly due to the variety of available devices, their limitations in front of the traditional ones, the network characteristics, the variety of the multimedia content types and formats, as well as to the lack of common standards related to the provisioning of services. In this context, Alembik aims to address these limitations and to provide a framework to transcode and adapt the multimedia content at runtime to the properties of the requiring mobile device. The main keywords which characterize Alembik are: dynamicity, flexibility, extensibility, standardization, user transparency, platform independence, high performance, and open source.

One of the main characteristics of most Web applications is their high dynamism. Once implemented and deployed for the first time, new functionalities are added to meet new or changed requirements. Some of these functionalities may appear on the Web in response to an unexpected event, or phenomena (such as a natural calamity) after which they are removed. Some others are activated periodically, to coincide with a particular date, or period of the year (such as, return to school, Christmas holidays, etc.). Implementing such volatile functionalities usually impacts on a number of aspects of a Web application, including content, navigation, presentation, business processes, and user operations. Their cyclic activation/deactivation, which requires repetitive changes in the application code, may be the cause of waste of effort and application quality deterioration, up to incorrect functioning.

In this paper, we present an approach to decouple the design and implementation of volatile functionalities from that of stable ones, i.e. the core functionalities of the application. The approach is instantiated in the context of the Object-Oriented Hypermedia Design Method (OOHDM), but its principles and related techniques are generally applicable to any other Web engineering method. We show how our approach enables the deployment and removal of these functionalities in a cost-effective and safe way and at runtime, thus providing business agility. A framework to classify volatile functionalities and a number of examples are also reported.