How to Improve Software Testability

SDETs (Software Development Engineers in Test) and test automation engineers are pivotal in ensuring that applications meet all functional and non-functional requirements. One of the key factors in achieving this goal is improving software testability. 

Testability is the degree to which a software application allows for easy and effective testing. To ensure that an application is delivered to the end-user as fast as possible with little to no issues, here are four actionable strategies SDETs and test automation engineers can adopt to improve software testability. 

1. Embrace a Test-First Culture 

Adopting a test-first culture enables SDETs and test automation engineering teams to implement testing methods into the app development process as early as possible. When teams implement testing procedures early in the development process, it’s easier to ensure alignment across every team involved in the development process (SDETs, developers, and other stakeholders). 

Better alignment on the status of app development can lead to more effective collaboration — resulting in a quicker time-to-market (TTM) and fewer bugs slipping through the cracks.

Testing early in the development process allows engineers to create test cases and automation scripts before development — allowing for earlier issue detection and reduced debugging requirements.

A simple way to nurture a test-first culture is to adopt a tool that helps run tests as fast as possible. Predictive Test Selection presents teams with a machine learning (ML) approach to effectively identify failures and accelerate test times by up to 80%.

2. Prioritize Test Automation 

Automation plays a critical role in improving software testability. Automating the tedious and time-consuming tasks required for a successful testing process saves time. It gives engineers more opportunities to focus on the complex tasks that require a human to execute. 

While there are plenty of popular test automation tools available to automate parts of software testing, prioritizing test selection AND test failure triage automation enables SDETs and test automation engineers to utilize the ample test suite data to speed up testing and issue detection.

Intelligent Test Failure Diagnostics allows engineering teams to automate issue detection and creation to streamline workflows. By eliminating the need to triage individual tests one at a time, engineers can focus on the tasks that can’t be completed through automation. 

3. Implement Proper Test Data Management 

To successfully improve software testability, teams must have access to quality testing data. A comprehensive test data management strategy provides engineering teams with testing data that resembles the data used in the customer-facing software. Leveraging data that mimics what the software will look like to an end-user helps engineers affirm the software’s performance, functionality, and security capabilities.

To help you get started, here are some critical steps for a successful test data management program:

• Analyze and identify which data sets are appropriate to use in testing.

• Ensure private and sensitive information is not used for testing.

• Mirror your production scenario to check for gaps in data elements.

• Implement automation wherever relevant.

• Build and leverage a centralized data repository to ensure alignment across teams.

• Use a variety of diverse data sets to expose as many issues as possible.

One tool that can assist software testing teams in implementing a proper test data management program is Test Suite Health Intelligence and Insights feature. This tool empowers teams to easily track test suite health with key KPI trends, quickly identify and prioritize unhealthy tests by impact, and access detailed test insights and context to debug test failures faster. 

4. Foster Cross-Team Collaboration 

Collaboration is a cornerstone of improving software testability, as alignment between the teams involved in the software testing process (developers, product managers, and QA teams) is critical in avoiding confusion, obstacles, and time waste. 

Integrating software testing into the DevOps pipeline can help all teams involved in the software testing process reach a common understanding of testing objectives and requirements. As DevOps is a methodology commonly used to enhance collaboration between teams, software testing teams can leverage the methodology to achieve a faster TTM without compromising on product quality. 

Adopting the practice of continuous integration and continuous delivery (CI/CD) into the software testing process is an effective way to foster cross-team collaboration. Many CI/CD tools provide features that improve communication across teams — including alerts for test failures or successful builds. 

Intelligent Test Failure Notifications notify engineers of any build and test failures caused by them — eliminating the need to poll CI servers or wait for QA teams to notify developers if they broke the build. And with Slack integration capabilities, teams can seamlessly communicate to determine the best course of action for resolving an issue.  

Using AI to Unlock the True Potential of Software Testability 

Improving software testability is an ongoing practice — it is not a one-and-done task. To ensure that your software testability improvement efforts make an impact, you need a way to:

• Continuously nurture a test-first culture

• Prioritize test automation

• Properly manage test data

• And foster cross-team collaboration — all while executing your daily tasks already at hand. 

Launchable supports SDETs and test automation engineers in improving software testability through AI-powered solutions that help teams better understand, triage, and manage test failures. 

Launchable’s AI-backed insights help flag and quantify any friction caused by unhealthy tests to help engineers more effectively prioritize issues. 

Developers and engineers use Launchable to tackle bug triage and defect management with comprehensive summaries of long error logs, allowing teams to swiftly pinpoint the root cause of issues and accelerate your software delivery timeline.