Software Quality Assurance Concepts

Flashcards covering key concepts from the Software Quality Assurance lecture notes.

Pragmatic Views of Software Quality

Emphasizes practicality, focusing on what stakeholders value in software, while recognizing constraints and using risk to guide quality decisions.

Defining Software Quality Advantages

Provides a shared language for stakeholders, makes quality measurable, guides trade-offs, and supports contracts/SLA.

Quality in Use

Perspective based on the user's experience and satisfaction with the software.

Types of Quality Concepts

1. Transcendental - recognized when seen. 2. User-based - fitness for use. 3. Manufacturer-based - conformance to specs. 4. Product-based - measurable attributes. 5. Value-based - trade-off between quality and cost.

Quality of Design vs. Quality of Conformance

Quality of design is how well requirements are translated into solutions; quality of conformance is how well the product adheres to its design.

Software Quality Factors

Factors including functionality, reliability, usability, efficiency, maintainability, and portability that contribute to the overall quality of software.

Cost of Quality

Includes prevention costs, appraisal costs, and failure costs; investing upfront can reduce later failures.

Defect Amplification and Removal

The process where one defect may lead to multiple downstream defects, emphasizing the need for early detection and removal.

Review Types

Different types of reviews include informal peer reviews, walkthroughs, formal technical reviews, inspections, and management reviews.

Roles in Software Reviews

Key roles include author, moderator, reviewer(s), and recorder, each with specific responsibilities during the review process.

SQA Goals

Prevent defects, ensure compliance, provide visibility into quality status, and support continuous improvement.

SQA vs. Quality Control vs. Quality Management

SQA focuses on process assurance, quality control focuses on product testing, and quality management encompasses overall planning and control.

DMAIC Cycle

A data-driven quality strategy used for process improvement: Define, Measure, Analyze, Improve, Control.

AI Reliability Models

Use machine learning to predict failure behavior and assist in planning testing efforts based on historical data.

Quality Management Integration

Integrates SQA, risk management, and configuration management to ensure quality is maintained throughout software lifecycle.