Modeling software artifact count attribute with s-curves

The estimation of software project attributes, such as size, is important for software project resource planning and process control. However, research regarding software attribute modeling, such as size, effort, and cost, are high-level and static in nature. This research defines a new operation-level software project attribute that describes the operational characteristic of a software project. The result is a measurement based on the s-curve parameter that can be used as a control variable for software project management. This result is derived from modeling the count of artifact instances created by the software engineering process, which are stored by software tools. Because of the orthogonal origin of this attribute in regard to traditional static estimators, this s-curve based software attribute can function as an additional indicator of software project activities and also as a quantitative metric for assessing development team capability

Productivity prediction model based on Bayesian analysis and productivity console

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

Measuring, monitoring, and assessing software process using PAMPA 2.0 knowledge-based system

My research is about monitoring the software development process to assess Capability maturity level. Capability Maturity Model (CMM) was developed to improve the software process based on subjective assessment by teams of experts. We propose an objective CMM assessment, which replaces expensive and time-consuming human effort by a knowledge-based system. Compared to Subjective CMM assessment, Objective CMM assessment can be less expensive, takes less time, and is easy to estimate the software development environment maturity. The accuracy of Objective CMM assessment can be the same as Subjective CMM assessment if enough activities are represented as objective activities. For example, if subjective activities total 80 % and objective activities total 20 %, then the accuracy of Objective CMM assessment is not reliable. It would be reliable if the objective activity is increased up to 80% from 20%. This dissertation presents how to change from Subjective CMM assessment to Objective CMM assessment, and we will prove that Objective CMM Assessment is effective

A model for enhancing software project management using software agent technology

The present study has originated from the realisation that numerous software development projects either do not live up to expectations or fail outright. The scope, environment and implementation of traditional software projects have changed due to various reasons such as globalisation, advances in computing technologies and, last but not least, the development and deployment of software projects in distributed, collaborative and virtual environments. As a result, traditional project management methods cannot and do not address the added complexities found in this ever-changing environment. In this study the processes and procedures associated with software project management (SPM) were explored. SPM can be defined as the process of planning, organising, staffing, monitoring, controlling and leading a software project. The current study is principally aimed at making a contribution to enhancing and supporting SPM. A thorough investigation into software agent computing resulted in the realisation that software agent technology can be regarded as a new paradigm that may be used to support the SPM processes. A software agent is an autonomous system that forms part of an environment, can sense the environment and act on it over a period of time, in pursuit of its own agenda. The software agent can also perceive, reason and act by selecting and executing an appropriate action. The unique requirements of SPM and the ways in which agent technology may address these were subsequently identified. It was concluded that agent technology is specifically suited to geographically distributed systems, large network systems and mobile devices. Agents provide a natural metaphor for support in a team environment where cooperation and the coordination of actions toward a common goal, as well as the monitoring and controlling of actions are strongly supported. Although it became evident that agent technology is indeed being applied to areas and sections of the SPM environment, it is not being applied to the whole spectrum, i.e. to all core and facilitating functions of SPM. If software agents were to be used across the whole spectrum of SPM processes, this could provide a significant advantage to software project managers who are currently using other contemporary methods. The "SPMSA" model (Software Project Management supported by Software Agents) was therefore proposed. This model aims to enhance SPM by taking into account the unique nature and changing environment of software projects. The SPMSA model is unique as it supports the entire spectrum of SPM functionality, thus supporting and enhancing each key function with a team of software agents. Both the project manager and individual team members will be supported during software project management processes to simplify their tasks, eliminate the complexities, automate actions and enhance coordination and communication. Virtual teamwork, knowledge management, automated workflow management and process and task coordination will also be supported. A prototype of a section of the risk management key function of the SPMSA model was implemented as `proof of concept'. This prototype may be expanded to include the entire SPMSA model and cover all areas of SPM. Finally, the SPMSA model was verified by comparing the SPM phases of the model to the Plan-Do-Check-Act (PDCA) cycle. These phases of the SPMSA model were furthermore compared to the basic phases of software development as prescribed by the ISO 10006:2003 standard for projects. In both cases the SPMSA model compared favourably. Hence it can be concluded that the SPMSA model makes a fresh contribution to the enhancement of SPM by utilising software agent technology.School of ComputingPh. D. (Computer Science