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Software Reliability Classes (SRCs) have been developed in order to compare the field reliability performance of a sequence of software releases for a cluster of similar hardware products. A specific cluster is characterized by the type of market the hardware supports, and the software releases for the cluster have similar functionality, complexity, size, and customer expectations. SRCs are a normalized...
Customers need to know how reliable a new release is, and whether or not the new release has substantially different, either better or worse, reliability than the one currently in production. Customers are demanding quantitative evidence, based on pre-release metrics, to help them decide whether or not to upgrade (and thereby offer new features and capabilities to their customers). Finding ways to...
Software Software Reliability Classes (SRCs) have beendeveloped in order to compare the field reliabilityperformance of a sequence of software releases for a clusterof similar hardware products. A specific cluster ischaracterized by the type of market the hardware supports,and the software releases for the cluster have similarfunctionality, complexity, size, and customer expectations
At Cisco, our primary measure of field reliability is Software Defects Per Million Hours (SWDPMH), and this metric is goaled on a yearly basis for over 120 product families. A key reason SWDPMH is considered to be of critical importance is that we see high correlation between SWDPMH and Software Customer Satisfaction (SW CSAT) over the wide spectrum of products and feature releases. Therefore, it...
The Universal Release Criteria (URC) Model has been used at Cisco for the past two years to assist test teams management in determining when adequate function testing, system testing, and bug fixing is achieved for a new release. A key URC metric is called Incoming Defect Level (IDL) — this is the percentage of the cumulative incoming bugs growth curve achieved at any week during testing. We use a...
The objective of the work described is to accurately predict, as early as possible in the software lifecycle, how reliably a new software release will behave in the field. The initiative is based on a set of innovative mathematical models that have consistently shown a high correlation between key in-process metrics and our primary customer experience metric, SWDPMH (Software Defects per Million Hours...
The objective of the work described is to accurately predict, as early as possible in the software lifecycle, how reliably a new software release will behave in the field. The initiative is based on a set of innovative mathematical models that have consistently shown a high correlation between key in-process metrics and our primary customer experience metric, SWDPMH (Software Defects per Million Hours...
Identifying correlations between in-process development and test metrics is key in anticipating subsequent reliability performance in the field. For several years now at Cisco, our primary measure of field reliability has been Software Defects Per Million Hours (SWDPMH), and this metric has been goaled on a yearly basis for over 100 product families. A key reason SWDPMH is considered to be of critical...
Since 2009, Software Defects Per Million Hours (SWDPMH) has been the primary customer experience metric used at Cisco, and is goaled on a yearly basis for about 100 product families. A key reason SWDPMH is considered to be of critical importance is that we see a high correlation between SWDPMH and Software Customer Satisfaction (SW CSAT) over a wide spectrum of products and feature releases. Therefore,...
Before a major feature release is made available to customers, it is important to be able to anticipate if the release will be of lesser quality than its predecessor release. Our research group has developed models that use development and test times, resource levels, code added, and bugs found and fixed (or not fixed) to predict whether or not a new feature release will achieve a key quality goal...
Some useful metrics (such as SWDPMH - software defects per million hours of customer usage per month) often have values that vary by several orders of magnitude, depending on the resident hardware platform, for a single software feature release. This is because different platforms use different parts of the code, have widely different performance characteristics, support widely varying numbers of...
Cisco Systems, Inc., conducts a customer satisfaction survey (CSAT) each year to gauge customer sentiment regarding Cisco products, technical support, partner- and Cisco-provided technical services, order fulfillment, and a number of other aspects of the companys business. The results of the analysis of this data are used for several purposes, including ascertaining the viability of new products,...
Software Quality has been a major challenge throughout Information Technology projects. Whether it is in software development, in software integration or whether it is in the implementation or customization of shrink-wrapped software, quality is regarded as a major issue. In the last couple of decades, much software engineering research has focused on standards, methodologies and techniques for improving...
Cost, schedule and quality are highly correlated factors in software development. They basically form three sides of the same triangle. Beyond a certain point (the "Quality is Free" point), it is difficult to increase the quality without increasing either cost or schedule or both for the software under development. As products and applications mature, users expect higher quality products...
Commmercial software product vendors such as Microsoft, IBM, and Oracle develop and manage a large portfolio of software products, which might include operating systems, middleware, firmware, and applications. Many institutions (such as banks, universities, and hospitals) also create and manage their own custom applications. Managers at these companies face an important problem: How can you manage...
This paper summarizes several classes of software cost estimation models and techniques: parametric models, expertise‐based techniques, learning‐oriented techniques, dynamics‐based models, regression‐based models, and composite‐Bayesian techniques for integrating expertise‐based and regression‐based models. Experience to date indicates that neural‐net and dynamics‐based techniques are less mature...
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