Risk-Based Testing Strategies for Software Quality Assurance

EasyChair Preprint 11362

Abstract

Software quality assurance (SQA) is an essential component of the software development lifecycle, aimed at ensuring that software products meet predefined quality standards. Within SQA, risk-based testing strategies play a pivotal role in optimizing testing efforts by identifying, prioritizing, and mitigating potential risks associated with software systems. This paper explores the fundamental concepts and methodologies of risk-based testing strategies in SQA. It delves into the significance of risk assessment and analysis in identifying critical areas within the software that require focused testing efforts. Various risk identification techniques, such as FMEA (Failure Mode and Effects Analysis) and risk matrices, are examined for their applicability in different stages of software development. Moreover, this paper investigates the integration of risk-based testing with traditional testing approaches, such as functional and regression testing, to optimize resource allocation and enhance test coverage. It explores how risk prioritization aids in the selection of test cases, enabling teams to allocate resources efficiently and effectively. Furthermore, the paper discusses the challenges and limitations of implementing risk-based testing strategies, including the subjectivity involved in risk assessment and the dynamic nature of software systems. Strategies to mitigate these challenges, such as continuous risk monitoring and adaptive testing approaches, are proposed to improve the effectiveness of risk-based testing.

Keyphrases: Automation, quality assurance, software development

@booklet{EasyChair:11362,
  author    = {Smith Milson and Guney Kadir},
  title     = {Risk-Based Testing Strategies for Software Quality Assurance},
  howpublished = {EasyChair Preprint 11362},
  year      = {EasyChair, 2023}}