Validation of Ultrahigh Dependability for Software-Based Systems

Modern society depends on computers for a number of critical tasks in which failure can have very high costs. As a consequence, high levels of dependability (reliability, safety, etc.) are required from such computers, including their software. Whenever a quantitative approach to risk is adopted, these requirements must be stated in quantitative terms, and a rigorous demonstration of their being attained is necessary. For software used in the most critical roles, such demonstrations are not usually supplied. The fact is that the dependability requirements often lie near the limit of the current state of the art, or beyond, in terms not only of the ability to satisfy them, but also, and more often, of the ability to demonstrate that they are satisfied in the individual operational products (validation). We discuss reasons why such demonstrations cannot usually be provided with the means available: reliability growth models, testing with stable reliability, structural dependability modelling, as well as more informal arguments based on good engineering practice. We state some rigorous arguments about the limits of what can be validated with each of such means. Combining evidence from these different sources would seem to raise the levels that can be validated; yet this improvement is not such as to solve the problem. It appears that engineering practice must take into account the fact that no solution exists, at present, for the validation of ultra-high dependability in systems relying on complex software

Experimental control in software reliability certification

There is growing interest in software 'certification', i.e., confirmation that software has performed satisfactorily under a defined certification protocol. Regulatory agencies, customers, and prospective reusers all want assurance that a defined product standard has been met. In other industries, products are typically certified under protocols in which random samples of the product are drawn, tests characteristic of operational use are applied, analytical or statistical inferences are made, and products meeting a standard are 'certified' as fit for use. A warranty statement is often issued upon satisfactory completion of a certification protocol. This paper outlines specific engineering practices that must be used to preserve the validity of the statistical certification testing protocol. The assumptions associated with a statistical experiment are given, and their implications for statistical testing of software are described

A Novel Approach for Cleanroom Software Testing

The Cleanroom method of Software Engineering ensures high-quality software with certified reliability, which is an important aspect of every software product. The certification process needs a reasonable statistical user testing strategy to measure the software reliability. We propose a mechanism to reduce testing time as well as effort while performing statistical user testing so that software quality is not diluted as well as maintaining a high degree of software reliability. We also cover a brief history of cleanroom software engineering approach

Statistical modelling of software reliability

During the six-month period from 1 April 1991 to 30 September 1991 the following research papers in statistical modeling of software reliability appeared: (1) A Nonparametric Software Reliability Growth Model; (2) On the Use and the Performance of Software Reliability Growth Models; (3) Research and Development Issues in Software Reliability Engineering; (4) Special Issues on Software; and (5) Software Reliability and Safety

Quality in software development : a pragmatic approach using metrics

As long as software has been produced, there have been e orts to strive for quality in software products. In order to understand quality in software products, researchers have built models of software quality that rely on metrics in an attempt to provide a quantitative view of software quality. The aim of these models is to provide software producers with the capability to de ne and evaluate metrics related to quality and use these metrics to improve the quality of the software they produce over time. The main disadvantage of these models is that they require e ort and resources to de ne and evaluate metrics from software projects. This article brie y describes some prominent models of software quality in the literature and continues to describe a new approach to gaining insight into quality in software development projects. A case study based on this new approach is described and results from the case study are discussed.http://www.journals.co.za/ej/ejour_comp.htmlam201