Architectural design of experience based factory model for software development process in cloud computing: integration with workflow and multi-agent system

A model which is based on experience factory approach has been proposed earlier, calledEBF-SD, to overcome the limitations of experience management in software developmentdomain. An application prototype, which is then called SDeX, is developed based on theproposed model. The study on correlation analysis indicates that automation do have positiverelationship with other components: knowledge management, cloud, collaboration and portal.This paper further discusses the high level prototype development with the emphasis on thearchitectural design. Automation features are incorporated in the design in which workflowsystem and intelligent agents are integrated, and the facilitation of cloud environment isempowered to further support the automation.Keywords: architectural design; knowledge management; experience factory; workflow;multi-agent system; cloud automation

The Development and Evaluation of Experience-Based Factory Model for Software Development Process

Knowledge, and experiences in software development have been accumulated over time throughout the project lifecycle. Previous studies have shown that the management of knowledge and experiences in software development has always been an issue. Therefore, the knowledge transfer and information flow are inefficient, misinterpretation, and inconsistencies always occur between individuals or teams, and the organization fails to learn from past projects. It is understood that efficient knowledge and experience management for software development organizations is crucial for the purpose of sharing and future reuse. This paper discusses the prototype development for a proposed model, which is based on the experience factory approach, to manage knowledge and experiences for the software development process. Discussions include the system functionalities and design, infrastructure requirements, and implementation approach. The efficiency and effectiveness of the prototype are evaluated as survey research based on Jennex & Olfman knowledge management success model. Rasch analysis is used for data reliability and validity. Results show positive feedback on the model’s efficiency and effectiveness. Additionally, as agreed by most respondents, the top three of the model contributions are: to encourage learning organization, to prevent knowledge loss and to aid in decision making

Regression Analysis on Experience Based Factory Model for Software Development Process

Software organizations are still struggling to reuse the best of their knowledge and experiences in future projects. Often, when there are changes on employee re-assignment, a lot of time and effort are spent for knowledge transfer activities. This however may not assure that all knowledge and experiences are well transferred and shared; some could be missing or misplaced. In this study, a model has been proposed for managing knowledge and experiences based on experience factory approach to provide a more efficient and effective experience management for software development community. Experience Factory is an infrastructure that aims for reuse of products, processes and experiences gained during a system life cycle. A set of components have been identified as the predictors of the model which eventually forms the two main organizations: project organization and experience factory organization. This study further has gone through a correlational survey research to verify the relationship between the identified predictors towards the experience factory goals. Reliability analysis has been conducted to validate the measures, while correlation and regression analyses have been carried out to examine the relationship between the constructs and the goals. Results reveal that reliability of the model is high and construct validity is satisfactory. Experience factory organization is found having more positively significant towards experience goals as compared to project organization; however, there is no significant impact towards the model due to inexistence of causal relation

Distributed Software Development with Knowledge Experience Packages

In software production process, a lot of knowledge is created and remain silent. Therefore, it cannot be reused to improve the effectiveness and the efficiency of these processes. This problem is amplified in the case of a distributed production. In fact, distributed software development requires complex context specific knowledge regarding the particularities of different technologies, the potential of existing software, the needs and expectations of the users. This knowledge, which is gained during the project execution, is usually tacit and is completely lost by the company when the production is completed. Moreover, each time a new production unit is hired, despite the diversity of culture and capacity of people, it is necessary to standardize the working skills and methods of the different teams if the company wants to keep the quality level of processes and products. In this context, we used the concept of Knowledge Experience Package (KEP), already specified in previous works and the tool realized to support KEP approach. In this work, we have carried out an experiment in an industrial context in which we compared the software development supported by KEPs with the development achieved without it