The Pesticide Paradox: Sustaining the Effectiveness of Testing Methods

The Pesticide Paradox: Sustaining the Effectiveness of Testing Methods.


Originally, the pesticide paradox is an intriguing term in agriculture. It says when the same pesticide is applied to crops for a more extended period, the pests develop a resistance against it. And the pesticide no longer works on them since they are immune to it.

In 1990, Boris Beizer, in his book Software Testing Techniques, Second Edition, coined the term pesticide paradox in the context of software testing. He wrote, “Every method you use to prevent or find bugs leaves a residue of subtler bugs against which those methods are ineffectual.”

This quote implies that when the same set of tests is run over a while, it may fail to uncover new defects introduced by new bug fixes or feature enhancements and eventually become ineffective. This article will review the reasons and solutions to the pesticide paradox in testing.

Why Does the Pesticide Paradox Arise?

The pesticide paradox can occur due to below significant reasons:

Growing Application

An emerging application will have continuous enhancements, bug fixes, and new feature releases. These changes will introduce new defects around them. If the tests are not updated to reflect all these changes, the newly introduced defects will seep into the application without detection.

Stale Tests and Data

Tests should evolve with the application and avoid test stagnation. The test suite needs updating whenever there are new features and bug fixes in the application. Achieve it by adding new relevant test cases, test data and updating the existing tests with changes in the application.

Insufficient Test Coverage

Limited test coverage of some regions of the application will keep on testing those functionalities only. The remaining essential features will remain untested, and the underlying defects may go undetected in the final product.

Pesticide Paradox in Test Automation

Now let us evaluate the pesticide paradox situation in test automation. The reasons for the pesticide paradox in test automation can be:

Unmaintained Test Scripts

Test automation is continuous, and the test scripts need periodic maintenance. The misconception that automated test scripts are forever can cause a pesticide paradox of everything being alright! Hence, testers should include the new features and changes in the test automation suite to avoid defect slippage.

Unmanaged Test Data

Test data is as crucial to the test cases. However, test data is an entity that gets the least attention and causes false negatives or positives in test results. For example, an identical sample data, which is repetitive and unmanaged for a long time. When used for test runs, such data causes tests to pass, hinting at a false positive.

Overlooked Regression Tests

The best use case of automation testing is your regression tests. They run every sprint to raise the alarm if anything has gone haywire. What if they do not present any warning and give a perception of things being in control? It is a usual phenomenon with regression testing when there is no update in the test cases as per the new changes in the application. And the same age-old regression scripts run in every sprint.

Learn in detail about effective regression tests here.

Test Environment Limitations

Scenarios where the test environment fails to replicate the production environment entirely, can cause test scripts to pass and create false positives. These situations can be factual for production environments that have grown from simple to complex. Now, when it is difficult to fully replicate the network, database, hardware, and software components, the tests pass quickly in a comparatively more straightforward test environment. However, they were bound to fail in reality.

Resource and Time Crunch

Agile and DevOps methodologies have faster and more compact test cycles than waterfall methodology. Creating or maintaining automation test scripts in these short sprint cycles may be more challenging due to time and resource constraints. This crunch may lead to picking a smaller subset of test suites or running tests without accommodating the recent application changes. The test coverage is impacted in both ways. The pesticide paradox may emerge because the existing test suite failed to uncover the hiding bugs and provided false stability.

Unachievable 100% Test Automation

100% test automation is a myth and impractical using traditional test automation tools.

Highly complex scenarios are inoperable use cases for automation testing.

Also, there exists room for test cases for manual execution, such as exploratory testing, usability testing, ad-hoc testing, etc. When only automation scripts are relied upon, ignoring the other manual testing requirements, the tests may pass and provide a false sense of completion.

In the absence of human intelligence-related test cases, everything will seem fine and working, while in reality, the actual users may face issues and bugs after the software release.

Best Practices to Prevent Pesticide Paradox

There are a few best practices that can help you stay away from the pesticide paradox and keep the automation test scripts in perfect shape. Though this list is not exhaustive, it covers the major attention areas.

Periodic Test Maintenance

Maintenance is the next important step after creating automated test scripts. Irrelevant and outdated test scripts will do more harm than good to the test execution. Periodic test maintenance should ideally include three actions:

  • Update the existing test scripts with enhancements, bug fixes, and new feature releases.
  • Add new test scripts based on application changes.
  • Delete test scripts that have become outdated due to the latest application changes.

Peer Review of Features

While adding new test scripts or updating existing ones, it is a good idea to have a peer review and discussion of new/existing application features with the team members. Peer review helps get different perspectives and improves the test script-creating process.

Test Coverage Expansion

We can never achieve 100% test coverage through traditional automation tools. The best practice is to achieve maximum test automation coverage diligently. Discussing new features with stakeholders can help expand the test script coverage. Do not only rely on the existing test scripts.

This test coverage expansion is also associated with test data relevance. Keep the test data diverse, updated, and complete with enough sampling to cover all real-life scenarios sufficiently.

See here how you can achieve maximum test coverage using testRigor.

Test Suite Reviews

Test scripts can be buggy too, and they can divert the focus from developing AUT(Application Under Test) to developing automation test scripts. Moreover, they can create false positives and affect the software quality negatively.

Sometimes, the test script author could not find any bug in their code due to biases and myopic vision. There is always a need for test suite review by other team members to discover potential loopholes. Retrospective analysis of the test suite to identify patterns and recurring issues will help create a better test suite.

Test Prioritization

One effective way to deal with the pesticide paradox is prioritizing the test script generation. Rate and prioritize the scenarios based on business risk, criticality, market share, impact, etc. Script the high-priority tests first with good coverage and then gradually move to the lesser-priority test scenarios.

Ad-hoc and User Interaction Based Testing

Although we are talking about test automation, the human eye of detail is needed to bypass the pesticide paradox. We can not deny the importance and effectiveness of exploratory or ad-hoc testing that does not follow any specific rule. This random testing helps uncover many defects which automation scripts may fail to detect.

Agile and DevOps Testing

Integrate the test automation scripts with CI/CD pipeline to receive fast and early feedback. Ensure that the test scripts run is triggered whenever there is a push in the code. This early feedback allows developers to make changes in the code in the early stages and reduces the cost-to-market drastically.

Find a roadmap to better Agile testing here.

Effective Bug Analysis

Bug analysis helps investigate the behavior of a bug to get to the root cause of the issue. Through bug analysis, understand the problem area and curb the potential recurrence of similar issues. The steps involved in bug analysis are as follows:

  • Reproduce the bug: Use automation scripts to recreate the bug consistently.
  • Gather relevant information: Collect context information such as environment, test data, steps to reproduce, logs, error message, etc., for analysis.
  • Root cause analysis: Analyze the bug with relevant stakeholders and find out the reason, such as issues in configuration, environment, code, data, etc.
  • Developers debug the code: With all these details, developers find it easier to fix the bug.
  • Retest after bug fix: Rerun the test scripts to verify the bug fix.
  • Retrospective analysis: Perform a retrospective analysis of the bug to derive process improvements, lessons learned, and preventive measures.

Check how to automate the process of bug reporting with simple plain English commands.


The first step to escaping the pesticide paradox is to come out of a know-it-all attitude. An application has many layers, and knowing the unknown is difficult. No automation test suite is final and complete, and the scope for improvement is always there.

Strive to maximize the coverage and write different ad-hoc tests to discover defects that may otherwise go undetected. The key is continuously monitoring and updating the test scripts to stay relevant, effective, adaptive, and valuable for ROI.

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AI Applications

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