Lessons Learned from OO Projects

In process Metrics for Outage and Availability

To improve product reliability and availability, sound architecture and good designs are key. Root causes and lessons learned from customer outages in the field can be used to improve the design points for the next release of the product. In terms of in-process metrics when the product is under development, however, we don't recommend premature tracking of outages and availability during the early phases of testing. Such tracking should be done during the product-level testing or during the final system test phase in a customerlike environment. During early phases of testing, the defect arrival volume is high and the objective is to flush out the functional defects before the system stabilizes. Tracking and focus at these phases should be on testing progress, defect arrivals, and defect backlog. When the system is achieving good stability, normally during the final phase of testing, metrics for tracking system availability become meaningful. In Chapter 10, we discuss and recommend several metrics that measure outages and availability: number and trend of system crashes and hangs , CPU utilization, and Mean Time to unplanned IPL (initial program load, or reboot). While some metrics may require tools, resources, and a well-established tracking system, tracking the system crashes and hangs can be done by paper and pencil, and can be implemented easily by small teams .

For projects that have a beta program, we recommend tracking customer outages in beta, especially those customers who migrated their production runs to the new release. The same focus as the field outages should be applied to these outages during the beta program. Outages during the beta program can also be used as a predictive indicator of the system outages and availability in the field after the product is shipped. The difference is that during beta, there are still chances to take improvement actions before the product is made available to the entire customer population. We have experience in tracking system crashes during customer beta for several years . Due to small numbers , we haven't established a parametric correlation be-tween beta outages and field outages yet. But using nonparametric (rank-order) correlation methods and comparing releases, we did see a positive correlation between the two ”the more crashes during beta, the more outages and less system availability in the field.

What Is Software Quality?

Software Development Process Models

Fundamentals of Measurement Theory

Software Quality Metrics Overview

Applying the Seven Basic Quality Tools in Software Development

Defect Removal Effectiveness

The Rayleigh Model

Exponential Distribution and Reliability Growth Models

Quality Management Models

In-Process Metrics for Software Testing

Complexity Metrics and Models

Metrics and Lessons Learned for Object-Oriented Projects

Availability Metrics

Measuring and Analyzing Customer Satisfaction

Conducting In-Process Quality Assessments

Conducting Software Project Assessments

Dos and Donts of Software Process Improvement

Using Function Point Metrics to Measure Software Process Improvements

Concluding Remarks

A Project Assessment Questionnaire

show all menu

Metrics and Models in Software Quality Engineering
Metrics and Models in Software Quality Engineering (2nd Edition)
ISBN: 0201729156
EAN: 2147483647
Year: 2001
Pages: 176
Similar book on Amazon

Flylib.com © 2008-2017.
If you may any questions please contact us: flylib@qtcs.net