Software reliability

In the context of software engineering, software quality refers to two related but distinct notions that exist wherever quality is defined in a business context:

Many aspects of structural quality can be evaluated only statically through the analysis of the software inner structure, its source code, at the unit level, the technology level and the system level, which is in effect how its architecture adheres to sound principles of software architecture outlined in a paper on the topic by OMG. But some structural qualities, such as usability, can be assessed only dynamically (users or others acting in their behalf interact with the software or, at least, some prototype or partial implementation; even the interaction with a mock version made in cardboard represents a dynamic test because such version can be considered a prototype). Other aspects, such as reliability, might involve not only the software but also the underlying hardware, therefore, it can be assessed both statically and dynamically (stress test).

Functional quality is typically assessed dynamically but it is also possible to use static tests (such as software reviews).

Historically, the structure, classification and terminology of attributes and metrics applicable to software quality management have been derived or extracted from the ISO 9126-3 and the subsequent ISO 25000:2005 quality model, also known as SQuaRE. Based on these models, the Consortium for IT Software Quality (CISQ) has defined five major desirable structural characteristics needed for a piece of software to provide business value: Reliability, Efficiency, Security, Maintainability and (adequate) Size.

Software quality measurement quantifies to what extent a software or system rates along each of these five dimensions. An aggregated measure of software quality can be computed through a qualitative or a quantitative scoring scheme or a mix of both and then a weighting system reflecting the priorities. This view of software quality being positioned on a linear continuum is supplemented by the analysis of "critical programming errors" that under specific circumstances can lead to catastrophic outages or performance degradations that make a given system unsuitable for use regardless of rating based on aggregated measurements. Such programming errors found at the system level represent up to 90% of production issues, whilst at the unit-level, even if far more numerous, programming errors account for less than 10% of production issues. As a consequence, code quality without the context of the whole system, as W. Edwards Deming described it, has limited value.

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