Software architecture knowledge for intelligent light maintenance

The maintenance management plays an important role in the monitoring of business activities. It ensures a certain level of services in industrial systems by improving the ability to function in accordance with prescribed procedures. This has a decisive impact on the performance of these systems in terms of operational efficiency, reliability and associated intervention costs. To support the maintenance processes of a wide range of industrial services, a knowledge-based component is useful to perform the intelligent monitoring. In this context we propose a generic model for supporting and generating industrial lights maintenance processes. The modeled intelligent approach involves information structuring and knowledge sharing in the industrial setting and the implementation of specialized maintenance management software in the target information system. As a first step we defined computerized procedures from the conceptual structure of industrial data to ensure their interoperability and effective use of information and communication technologies in the software dedicated to the management of maintenance (E-candela). The second step is the implementation of this software architecture with specification of business rules, especially by organizing taxonomical information of the lighting systems, and applying intelligencebased operations and analysis to capitalize knowledge from maintenance experiences. Finally, the third step is the deployment of the software with contextual adaptation of the user interface to allow the management of operations, editions of the balance sheets and real-time location obtained through geolocation data. In practice, these computational intelligence-based modes of reasoning involve an engineering framework that facilitates the continuous improvement of a comprehensive maintenance regime

Harmonizing Software Standards with a Semantic Model

The application of standards in the software development process supports interoperability between systems. Maintenance of standards must be guaranteed on the organisational and technical level. The use of semantic technologies can contribute to the standard maintenance process by providing a harmonizing bridge between standards of different knowledge domains and languages and by providing a single point of administration for standard domain concepts. This paper describes a case study of the creation of a semantic layer between software standards for water management systems in The Netherland

Maintenance of Automated Test Suites in Industry: An Empirical study on Visual GUI Testing

Context: Verification and validation (V&V) activities make up 20 to 50 percent of the total development costs of a software system in practice. Test automation is proposed to lower these V&V costs but available research only provides limited empirical data from industrial practice about the maintenance costs of automated tests and what factors affect these costs. In particular, these costs and factors are unknown for automated GUI-based testing. Objective: This paper addresses this lack of knowledge through analysis of the costs and factors associated with the maintenance of automated GUI-based tests in industrial practice. Method: An empirical study at two companies, Siemens and Saab, is reported where interviews about, and empirical work with, Visual GUI Testing is performed to acquire data about the technique's maintenance costs and feasibility. Results: 13 factors are observed that affect maintenance, e.g. tester knowledge/experience and test case complexity. Further, statistical analysis shows that developing new test scripts is costlier than maintenance but also that frequent maintenance is less costly than infrequent, big bang maintenance. In addition a cost model, based on previous work, is presented that estimates the time to positive return on investment (ROI) of test automation compared to manual testing. Conclusions: It is concluded that test automation can lower overall software development costs of a project whilst also having positive effects on software quality. However, maintenance costs can still be considerable and the less time a company currently spends on manual testing, the more time is required before positive, economic, ROI is reached after automation

Machine learning research 1989-90

Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base

Team knowledge management within an outsourced business systems software maintenance environment: a case study using grounded theory methods

The effective management of knowledge is increasingly seen as an essential contributor to the success of a knowledge-based organisation. There is a wealth of methodologies and approaches providing guidelines or frameworks for managing knowledge in a wide range of domains such as software development, IS service delivery and project management but few are dedicated to software maintenance. This paper presents the case study research of an outsourced software maintenance operation in the e-commerce business unit of a large UK retailer, using grounded theory to investigate a framework for assessing and improving the knowledge management capability of the software maintenance teams. The framework assesses the operation in five areas: leadership, communication, tools, processes and cultures. The results offer an insight into the strengths and areas for improvement in the knowledge management arrangements

Predicting Defects in Software Using Grammar-Guided Genetic Programming

The knowledge of the software quality can allow an organization to allocate the needed resources for the code maintenance. Maintaining the software is considered as a high cost factor for most organizations. Consequently, there is need to assess software modules in respect of defects that will arise. Addressing the prediction of software defects by means of computational intelligence has only recently become evident. In this paper, we investigate the capability of the genetic programming approach for producing solution composed of decision rules. We applied the model into four software engineering databases of NASA. The overall performance of this system denotes its competitiveness as compared with past methodologies, and is shown capable of producing simple, highly accurate, tangible rules

MASK-SM : multi-agent system based knowledge management system to support knowledge sharing of software maintenance knowledge environment.

Knowledge management (KM) has become an important topic as organizations wish to take advantage of the information that they produce and that can be brought to bear on present decisions. This paper described a system to manage the information and knowledge generated during the software maintenance process (SMP). Knowledge Management System (KMS) is utilizing to help employees build a shared vision, since the same codification is used and misunderstanding in staff communications may be avoided. The architecture of the system is formed from a set of agent communities each community of practice(CoP) is in charge of managing a specific type of knowledge. The agents can learn from previous experience and share their knowledge with other agents or communities in a group of multi-agent system (MAS). This paper also described on the theoretical concept and approach of multi-agent technology framework that could be implemented software maintenance process (SMP) in order to facilitate knowledge sharing among the maintainers of the learning organization. as well as to demonstrate it into the system wise, on how the multi-agent technology could be utilized in the software maintenance process (SMP) system model for serving the maintainer that is developed by using groupware such as Lotus Notes software. This architecture will be named as MASK-SM (MAS Architecture to Facilitate Knowledge Sharing of Software Maintenance). The author followed the Prometheus methodology to design the MAS architecture. This paper applied the definition of ISO 9241-11 (1998) that examines effectiveness, efficiency, and satisfaction. The emphasis will be given to the software maintenance process (SMP) activities that may concern with multi-agent technology to help the maintainers especially in learning organization to work collaboratively including critical success factor in order to ensure that software maintenance process (SMP) initiatives would be delivered competitive advantage for the community of practice(CoP) as well as users of the organization