Error Guessing

Error Guessing

"A test design technique where the experience of the tester is used to anticipate what defects might be present in the component or system under test as a result of errors made, and to design tests specifically to expose them", per ISTQB.

Error guessing technique involves the tester making guesses about mistakes (errors) that a developer might make and then designing tests for them. Error guessing requires the tester to have knowledge and experience of common programming errors and their impact on code produced, the nature of bugs that can be introduced and how those may be reproduced. The tester needs to have some experience with programming and the technologies used by development. This enables the tester to make guesses about potential errors that may be introduced and create tests to find bugs associated with those errors. Error guessing may be used as a standalone technique or to complement other techniques. Error guessing can be applied at any stage of testing and may be used to even identify potential risks.

The effectiveness of using the Error guessing technique lay on the creativity and ability of the tester to guess errors and find bugs. Each tester is unique in this case and likely to approach this technique distinctly. Error guessing may also be used as a means to perform a quick smoke test. Trying to lay down guidelines and documentation requirements for this technique may constrain the tester's freedom and creativity which are important for Error guessing to be effective.

Needless to state it, error guessing is normally used as an additional test technique and not the sole or primary testing technique. Error guessing can help find bugs that may be missed by other techniques. Once tests are executed, it is recommended to capture them and automate as much as possible.

As you may have realized by now, the success of this technique to a certain extent is dependent on both the developer making similar mistakes as in the past and the tester having some experience with finding bugs that are similar to the ones that are in the current system-under-test.

Software Testing Types: A Practical Map for Risk-Based Coverage

A list of software testing types is useful only when it helps a team choose the right evidence for the risk in front of them. Memorizing names does not improve quality; matching risks to effective test approaches does.

This is the distinction senior QA professionals need to make. The question is not how many types of testing a team can name. The question is which failure modes matter, where those failures are most likely to appear, and what kind of testing will expose them early enough to influence the release decision.

Start with the quality risk

Functional testing checks whether the system does what it is supposed to do. Integration testing checks whether boundaries between components behave correctly. Performance testing checks whether the system holds up under realistic load. Security testing looks for misuse, exposure, and abuse paths. Accessibility testing checks whether people with different abilities can use the product effectively.

Each type answers a different question. Treating them as interchangeable creates gaps. A strong regression suite will not prove scalability. A penetration test will not prove workflow correctness. A usability session will not prove data integrity.

A practical map

• Business workflow risk: acceptance, exploratory, workflow, and end-to-end testing.
• Service behavior risk: unit, component, API, contract, and integration testing.
• Change regression risk: automated checks at the cheapest reliable level.
• Operational risk: performance, reliability, observability, backup, recovery, and deployment testing.
• Trust and compliance risk: security, privacy, accessibility, audit, and data-quality testing.

The best teams do not run every test type with equal weight. They build a portfolio. The portfolio changes when architecture, customer usage, compliance obligations, or defect history changes.

What this means for QA leadership

A QA leader should be able to explain why a release needs certain evidence and why other evidence is intentionally lighter. That explanation is much more credible than saying the team completed a standard checklist.

Testing types are not bureaucracy. They are choices about where confidence will come from. The craft is in choosing deliberately.

How to use this as a working habit

The practical value of this topic is in daily test design. Use it when reviewing a requirement, creating examples, selecting data, choosing boundaries, or explaining why a particular test matters.

Fundamentals are not junior concepts. Senior testers use them with more judgment: less ceremony where risk is low, more discipline where ambiguity, impact, or repeatability matter.

A useful habit is to ask what decision this concept supports. If the answer is unclear, the testing activity may need refinement. Good fundamentals should make the work sharper: clearer scope, better examples, stronger evidence, and more honest communication about what remains unknown.

Non-Functional And Risk-Focused Testing: The Quality Attributes Users Notice

Functional correctness is necessary, but not sufficient. Users also experience performance, reliability, security, accessibility, usability, recoverability, and trust.

Many teams test whether the feature works and treat non-functional testing as a late activity. That is risky. A product can pass functional tests and still be too slow, insecure, inaccessible, unreliable, difficult to recover, or impossible to diagnose.

Performance, Load, Stress, And Soak Testing

Performance testing evaluates responsiveness, throughput, resource usage, and scalability. Load testing checks expected usage. Stress testing explores behavior beyond expected limits. Soak testing reveals long-duration degradation such as memory leaks, queue buildup, or connection exhaustion.

The best performance testing starts with workload modeling and observability, not tool selection.

Security Testing

Security testing examines authentication, authorization, input validation, sensitive data handling, session behavior, configuration, dependency risk, and abuse cases. It should not be left only to a late penetration test.

Quality engineers do not need to replace security specialists, but they must understand enough security risk to include negative, misuse, and access-control scenarios in everyday testing.

Accessibility And Usability Testing

Accessibility testing verifies whether people with different abilities can use the product effectively. Usability testing evaluates whether intended users can complete meaningful tasks with clarity and confidence.

Automated accessibility checks are useful but incomplete. Keyboard navigation, focus management, labels, error messages, screen-reader behavior, and workflow clarity require human judgment.

Reliability And Recovery Testing

Reliability testing asks whether the system can perform consistently over time and under imperfect conditions. Recovery testing asks what happens after failure: can the system restore state, prevent data loss, avoid duplicate actions, and give users truthful status?

In distributed systems, retries, idempotency, timeouts, circuit breakers, and compensation logic are quality concerns.

Compliance And Standards Testing

Compliance testing verifies whether the system meets required legal, regulatory, contractual, or industry standards. The risk is not only failing an audit; it is creating customer, legal, financial, or reputational harm.

Non-functional testing is not secondary testing. It is often where user trust is won or lost. A mature QA strategy treats quality attributes as first-class requirements, not optional checks if time remains.