In recent time in dynamic field of software testing and quality assurance, the key role of test automation in expanding test coverage, improving overall product quality, and increasing tester productivity is widely recognized.
However, realizing these benefits depends on the reliability and robustness of the automation code to ensure that bugs are consistently identified and resolved in the product.
Table of Contents
The Essence of Reliable Automation Code
Before we move on to look at best practices for testing code, it’s important to recognize the potential pitfalls of inadequate automation.
When automated code fails to catch bugs or generates false negatives due to problems with the test code, it leads to a whole bunch of problems, including wasted test automation efforts, increased time to fix bugs, increased resource consumption, and potential damage to the reputation of the testing team.
Wasted Effort Breakdown:
A. Diminished ROI in Test Automation Effort
The complex process of code development, deployment and maintenance is the foundation of effective test automation. If this process is broken, it not only wastes time, money, and human resources. It fundamentally reduces the return on investment that organizations expect from their test automation efforts.
B. Extended Triage Time and Its Far-reaching Ramifications
The collateral damage of false negatives extends beyond the mere identification of bugs. It triggers an extended triage time, as the product team is compelled to delve into invalid bug reports. This not only consumes additional time and resources but also jeopardizes the standing of the test team within the broader product landscape.
C. Amplified Resource Usage and Its Hidden Costs
The utilization of machine, infrastructure, and software resources for automation execution is not a trivial matter. Inefficiencies in the automation code lead to a disproportionate drain on resources, with reverberations felt across the entire testing ecosystem. This amplified resource usage poses an insidious threat to the overall efficiency and sustainability of the testing process.
A Glimpse into Real-world Impacts
In a comprehensive study across diverse industries, the correlation between the reliability of automation code and tangible business outcomes became evident. Companies that invested in meticulous automation testing services reported a significant reduction in the overall cost of test automation efforts. These organizations not only witnessed streamlined processes but also reported a marked increase in the accuracy of bug identification, preventing potential false negatives that could have derailed product development timelines.
1. Enhanced Productivity Through Code Review Emphasis:
Companies that prioritize static testing in code reviews have seen a significant reduction in defects after implementation. Highlighting coding standards in these reviews not only simplified automated maintenance, but also fostered a culture of clean and easily modifiable code.
2. Accelerated Time-to-Market with Streamlined Triage:
Quickly identifying and resolving build errors caused by automation has become one of the key factors in reducing the time to fix bugs. Companies that have implemented robust build testing have seen not only a reduction in time to fix errors, but also a reduction in time to market.
3. Sustainable Resource Utilization for Long-term Success:
The impact of effective testing prior to active deployment of automated code was evident in the rational use of resources. In organizations where testing was performed consistently across multiple builds, there was a noticeable reduction in resource overhead.
The Path Forward
Along with learning code testing best practices, it is critical to bring this knowledge to the complex process of software testing. Investing in reliable and robust automated code is not just a technical necessity, but a strategic decision on which the success and efficiency of the entire product development lifecycle depends.
The Imperative of Testing Your Test Code
Traditional approaches to solving these problems include treating the test code as carefully as the product code. However, the question is whether all teams strictly adhere to this principle. In addition, it is crucial to understand the extent to which test code should be tested, as overzealous efforts in this area can lead to wasted resources without significantly adding value. Let’s take a look at some best practices for testing test code.
Best Practices for Testing a Test Code:
1. Static Tests and Code Reviews
Enforce coding standards during code analysis and minimize future maintenance automation. Emphasize modular test design and incorporation of reusable techniques to ensure clean and manageable code.
2. Prioritize Functional Testing of Your Test Code
a. Emphasize unit testing: emphasize unit testing using simple tools such as NUnit or JUnit, supplemented by manual work with checklists. This approach ensures that the functionality of the test code is fit for purpose.
b. Detailed build verification: pay special attention to testing the code intended to verify the build. Comprehensive verification in this area is critical because build-related issues that occur in the test code can result in significant overhead and negatively impact the test team’s credibility with the product team.
3. Trial Runs Before Deployment
Before deploying your test automation code, conduct trial runs on a few builds, even local ones if necessary. This step ensures consistent results and provides an opportunity to evaluate the type of failures returned, ensuring they are genuine product bugs.
4. Sequential Unattended Runs
Schedule multiple runs of your code in an unattended mode to identify built-in dependencies affecting test runs. Transition from local environments to the actual test environment to reveal deployment and cross-module dependencies.
5. Code Coverage Analysis
Code coverage tracking is used to evaluate the effectiveness of test code. This objective assessment not only determines the coverage achieved, but also serves as a valuable tool to measure the return on investment in test automation.
6. Focus on Functional Aspects
Prioritizing functional aspects of test automation code over non-functional areas such as performance, security, user interface, usability, globalization, and compatibility. Narrowing the focus allows for more effective evaluation of the core functionality of the test code.
7. Tool & Framework Limitations
Be aware of the potential limitations of tools and frameworks to prevent test results from degrading. Familiarize yourself with support provisions to build automation on a resilient platform and minimize unforeseen failures.
8. Evaluate Reporting Capabilities
Given that code test results are communicated to various levels of management, it is critical to evaluate reporting capabilities. Test the reporting module code for accuracy, level of detail, archiving capabilities, and usability, focusing on user interface and ease of use to improve the overall user experience.
9. Establish Clear Exit Criteria
As with product testing, clear completion criteria must be established before moving test automation code into the production environment. Strict criteria are necessary to ensure that the test code is reliable when applied in actual product testing. If some scenarios or tests are delaying the process, temporarily disable them and move them to the queue for later analysis.
Striking the Right Balance
Despite the importance of testing test code, it is important to keep perspective. The team has to realize that these activities are ancillary and that the focus is on using test code to improve the quality of the final product. Balancing the time and effort required to test and improve test code with the priority of actually testing the product is key to overall success.
Code testing is a critical step in ensuring the effectiveness of test automation. By adopting these best practices, testing team will be able to improve the automated code, avoid potential bugs, and focus their efforts on building a quality product. It’s important to remember that successful test automation is not just about finding bugs, but also about enabling teams to make informed decisions, which ultimately contributes to a better end-user experience.