L.M.L. Chung

Bio: L.M.L. Chung is an academic researcher. The author has contributed to research in topics: Project management & Project management triangle. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Integrating project planning and process modeling for software development

Abstract: Software projects are typically managed in a rather ad hoc manner. On the contrary, many formal methodologies exist for software process management. However, processes are often lack the flexibility provided by the projects. In this paper, we present an integrated process and project management tool that derives benefits from both project and process management on the one hand and minimizes their disadvantages on the other.

Integrating process and work breakdown structure with design structure matrix

Abstract: ∗Department of Computer Science and Information Engineering, National Central University, Jhongli, Taiwan E-mail: {yjlee, jass, wtlee, jielee}@selab.csie.ncu.edu.tw ∗∗Department of Computer and Information Science, National Taichung University, Taichung, Taiwan E-mail: glenn@mail.ntcu.edu.tw ∗∗∗Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung, Taiwan E-mail: albert@mail.ntou.edu.tw

Productivity prediction model based on bayesian analysis and productivity console

Abstract: Software project management is one of the most critical activities in modern software development projects. Without realistic and objective management, the software development process cannot be managed in an effective way. There are three general problems in project management: effort estimation is not accurate, actual status is difficult to understand, and projects are often geographically dispersed. Estimating software development effort is one of the most challenging problems in project management. Various attempts have been made to solve the problem; so far, however, it remains a complex problem. The error rate of a renowned effort estimation model can be higher than 30% of the actual productivity. Therefore, inaccurate estimation results in poor planning and defies effective control of time and budgets in project management. In this research, we have built a productivity prediction model which uses productivity data from an ongoing project to reevaluate the initial productivity estimate and provides managers a better productivity estimate for project management. The actual status of the software project is not easy to understand due to problems inherent in software project attributes. The project attributes are dispersed across the various CASE (Computer-Aided Software Engineering) tools and are difficult to measure because they are not hard material like building blocks. In this research, we have created a productivity console which incorporates an expert system to measure project attributes objectively and provides graphical charts to visualize project status. The productivity console uses project attributes gathered in KB (Knowledge Base) of PAMPA II (Project Attributes Monitoring and Prediction Associate) that works with CASE tools and collects project attributes from the databases of the tools. The productivity console and PAMPA II work on a network, so geographically dispersed projects can be managed via the Internet without difficulty.

Enterprise process modeling methodology and environment supporting project management

Abstract: Development of the global economy makes modem enterprises confront challenges of efficient managements for large projects and complex processes. Projects are typically managed in rather special manners. On the contrary, there exist many methodologies for product process management to achieve consistency and continuance. However, processes often lack flexibility offered by projects. This paper discusses the relationship of conceptual characteristics between process and project, gives low-level details to tackle the difference between them, and proposes an enterprise process modeling method for project management. An integrated environment is designed to support the method from which both project management and process management can receive benefits and conform to the limitations.