Quality engineering


Quality engineering is the discipline of engineering concerned with the principles and practice of product and service quality assurance and control. In the software development, it is the management, development, operation and maintenance of IT systems and enterprise architectures with a high quality standard.

Description

Quality engineering is the discipline of engineering that creates and implements strategies for quality assurance in product development and production as well as software development.
Quality Engineers focus on optimizing product quality which W. Edwards Deming defined as:
Quality engineering body of knowledge includes:
Auditor: Quality engineers may be responsible for auditing their own companies or their suppliers for compliance to international quality standards such as ISO9000 and AS9100. They may also be independent auditors under an auditing body.
Process quality: Quality engineers may be tasked with value stream mapping and statistical process control to determine if a process is likely to produce defective product. They may create inspection plans and criteria to ensure defective parts are detected prior to completion.
Supplier quality: Quality engineers may be responsible for auditing suppliers or performing root cause and corrective action at their facility or overseeing such activity to prevent the delivery of defective product.

Software

IT services are increasingly interlinked in workflows across platform boundaries, device and organisational boundaries, for example in cyber-physical systems, business-to-business workflows or when using cloud services. In such contexts, quality engineering facilitates the necessary all-embracing consideration of quality attributes.
In such contexts an "end-to-end" view of quality from management to operation is vital. Quality engineering integrates methods and tools from enterprise architecture-management, Software product management, IT service management, software engineering and systems engineering, and from software quality management and information security management. This means that quality engineering goes beyond the classic disciplines of software engineering, information security management or software product management since it integrates management issues, design considerations and operative considerations. In many of the fields where it is used, quality engineering is closely linked to compliance with legal and business requirements, contractual obligations and standards. As far as quality attributes are concerned, reliability, security and safety of IT services play a predominant role.
In quality engineering, quality objectives are implemented in a collaborative process. This process requires the interaction of largely independent actors whose knowledge is based on different sources of information.

Quality objectives

describe basic requirements for software quality. In quality engineering they often address the quality attributes of availability, security, safety, reliability and performance. With the help of quality models like ISO/IEC 25000 and methods like the Goal Question Metric approach it is possible to attribute metrics to quality objectives. This allows measuring the degree of attainment of quality objectives. This is a key component of the quality engineering process and, at the same time, is a prerequisite for its continuous monitoring and control. To ensure effective and efficient measuring of quality objectives the integration of core numbers, which were identified manually, and automatically identified metrics as a basis for decision-making is favourable.

Actors

The end-to-end quality management approach to quality engineering requires numerous actors with different responsibilities and tasks, different expertise and involvement in the organisation.
Different roles involved in quality engineering:
Typically, these roles are distributed over geographic and organisational boundaries. Therefore, appropriate measures need to be taken to coordinate the heterogeneous tasks of the various roles in quality engineering and to consolidate and synchronize the data and information necessary in fulfilling the tasks, and to make them available to each actor in an appropriate form.

Knowledge management

plays an important part in quality engineering. The quality engineering knowledge base comprises manifold structured and unstructured data, ranging from code repositories via requirements specifications, standards, test reports, enterprise architecture models to system configurations and runtime logs. Software and system models play an important role in mapping this knowledge. The data of the quality engineering knowledge base are generated, processed and made available both manually as well as tool-based in a geographically, organisationally and technically distributed context. Of prime importance is the focus on quality assurance tasks, early recognition of risks, and appropriate support for the collaboration of actors.
This results in the following requirements for a quality engineering knowledge base:
The quality engineering process comprises all tasks carried out manually and in a automated way to identify, fulfil and measure any quality features in a chosen context. The process is a highly collaborative one in the sense that it requires interaction of actors, widely acting independently from each other.
The quality engineering process has to integrate any existing sub-processes that may comprise highly structured processes such as IT service management and processes with limited structure such as agile software development. Another important aspect is change-driven procedure, where change events, such as changed requirements are dealt with in the local context of information and actors affected by such change. A pre-requisite for this is methods and tools, which support change propagation and change handling.
The objective of an efficient quality engineering process is the coordination of automated and manual quality assurance tasks. Code review or elicitation of quality objectives are examples of manual tasks, while regression tests and the collection of code metrics are examples for automatically performed tasks. The quality engineering process can be supported by tools such as ticketing systems or security management tools.