in 150 - 200 words summarize and rephrase this article, and write one sentence the most takeaway and one-sentence criticism from this article (An intelligent early warning system for software quality improvement and project management)

Abstract

There are three major problems with software projects: over budget, behind schedule, and poor quality. It is often too late to correct these problems by the time they are detected in failed software projects. In this paper, we discuss design, implementation, and evaluation of an experimental intelligent software early warning system based on fuzzy logic using an integrated set of software metrics. It consists of the following components: software metrics database, risk knowledge base, intelligent risk assessment, and risk tracing. It helps to assess risks associated with the three problems from perspectives of product, process, and organization in the early phases of the software development process. It is capable of aggregating various partial risk assessment results into an overall risk indicator even if they may be conflicting. In addition, it can be used to analyze a risk by identifying its root causes through its risk tracing utility.

Introduction

Lots of efforts and money is wasted on unfruitful software development projects. One of the main reasons behind failed software projects is that it is often too late to correct the problems by the time they are detected. It clearly indicates the need for early warning about the potential risks. In practice, one of main causes behind the inability for early warning in a software project is its lack of important data about many software artifacts, software development process elements, and organization units, and lack of tools for analyzing available software metrics, and lack of tools for visualizing problems of development. Not only is the measurement of software entities difficult, but also the way to analyze these measurements. It is even more difficult to assess risks based on these software metrics. Many software metrics have been proposed and used to measure the software entities at different stages of software development. How to make a systematic use of these metrics to identify future risks in software development remains challenging. Very few methods and tools are developed to address the issue while most of existing risk assessment methods or tools are focused on only a particular aspect of software development. In practice, software risk assessment is often done by experts subjectively. It is not only necessary to identify risks in early development phases, but also important to quantify the risks in order to prioritize them during assessment. Furthermore, it is important to be able to identify the causes of risks so that they can be eliminated.

Conclusions

This research is a successful attempt to design a system to assess risks at the early phases of a software development. Three types of risks are assessed: quality risks, schedule risks, and budget risks. The vague nature of software metrics in software development and the lack of exact software measurements are handled by fuzzy logic. The system collects and analyses the metrics from three perspectives of the software development: product, process, and organization. The risks can be assessed