Software testing has undergone dramatic change. From the adoption of agile methodologies to DevOps delivery, the IT industry is looking for fast implementation cycles with high-quality results. While CTOs want to avoid problems that could surface after the release, the Project Management Office (PMO) is looking for ways to get things moving quickly. This becomes a challenge for testing teams: get development into production with minimal defects.
For business stakeholders, the priority is to identify and manage risk before testing begins. Risks like short timelines, inadequate resources, volatile requirements – or even an unexpected situation like COVID-19 – need a forward-thinking approach. Advanced planning and better mitigation strategies ensure all risks are addressed well in advance. To achieve delivery targets, it’s critical to select the right testing strategy.
Improve Quality with Testing Best Practices
There is no doubt that testing is a pivotal element in the software-delivery process. In fact, it already costs businesses a fortune: one study from Cambridge University found that software bugs cost the economy more than $300 billion per year. While there is no “golden rule” to follow, there are a few software testing best practices that could ease testing and help organizations deliver defect-free output within reasonable timeframes.
For instance, a context-driven testing approach could help testing teams prioritize testing order, make the testing process easier, and deter pushing testing to the last minute. The testing team could follow these best practices to improve the software testing process and increase the quality of software products:
Larger risks could sabotage long-term projects and therefore require immediate attention. A risk-based testing approach could help find and prevent defects early in the software delivery process. It allows quality improvement by moving high-risk tasks to the “left” so they can be planned early in the lifecycle.
Use Risk-Based Testing to Identify, Prioritize and Manage Testing Risks
One test principle that encompasses the above best practices is risk-based testing (RBT). RBT assesses the probability of risk based on the complexity, criticality, usage frequency, defect prone areas, and more. It prioritizes testing particular features, modules, or functions based on the impact and likelihood of failure. This helps plan for the biggest risks.
RBT can identify big risks well in advance; for example, identifying the failure risk of a particular functionality in production and its impact on the business by using a prioritization technique for test cases. RBT is a proven method of identifying crucial and important tests from both the customer and business perspective through a “Risk Analysis” procedure. RBT also helps plan high-priority items and catch failure early (fail fast).
Risk-based testing is beneficial for time and resource constraints. Risk identification can be conducted by getting all stakeholders to assess:
Where the likelihood of failure and business risk are high, the derived priority is marked as “3” representing the highest category (Fig 1). Concentrated efforts and thorough testing of category 3 can help identify critical issues of priority – planning big risks early. Derived priority items in “2” and “1” can be taken up subsequently in that order.
Once the risk categories are defined, risk options can be determined. Stakeholder involvement in risk options is an essential step in gaining customer confidence. Risk options can range from contingency planning to mitigate the risk, take an informed decision to postpone, or ignore the risk at the current time.
Resource allocation based on business impact and options can increase testing efficiency. The level of testing for each of the priorities can be agreed upon based on these suggestions:
Testing the high risk of failure for business early can help the project move into a live environment with low-risk issues, creating a system that can still be used. Identifying and resolving issues early also leads to a higher confidence in the solution and happier customers. Without a risk-assessment plan, the average project goes live with unknown issues and has a higher risk of failure post release.
Risk-based Testing Improves Testing Efficiency and Quality
Advanced planning and better mitigation strategies help address risks early where they are easier to resolve, less impactful to the customer, and improve delivery targets. But selecting the right strategy for testing is a challenge. The goal is to use a strategy that improves the quality of testing, identifies the critical functions to test, and improves customer confidence.
Risk-based testing is a collaborative effort for testing teams and business stakeholders to identify and prioritize high-risk items and provide a framework for setting priorities. Involving the business in risk assessment also brings increased confidence in the solution being delivered. This combination of collaboration, planning, and proactive testing ultimately leads to improvements in quality and success.
PDEng Managing Consultant, Data Analytics & AI Consulting
Saurabh is a data scientist involved in driving business value by using AI/ML techniques in diverse industry use cases. He is passionate about solving real business problems using cutting edge technologies. Saurabh holds PDEng (Professional Doctorate in Engineering) from TU/e, Netherlands and Master of Technology from IIT Kanpur, India.
Managing Consultant, Data Analytics & AI Consulting
Priya is a techno functional consultant with over 15 years of analytics experience across industries such as banking, asset management, insurance consumer electronics etc. Priya holds a MBA in finance from the Indian Institute of Management, Bangalore (IIMB).