What are the Most Effective Assessment Methods for QA Engineers

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The process of software development has an integral ask for Quality Assurance (QA), i.e. also better known as software testing. This testing is undertaken to assure that the product or software being developed is market-fit and free of any bugs, malfunctioning, or errors. QA in today’s time has become a necessary skillset in the life of developers and testers combined. Over the years websites and software have become more complex and intertwined with a lot more features and functionalities, which makes QA an important aspect to look out for. Before market launch developers aim to resolve most of the bugs or complexities in the applications or software being developed.

Naturally, QA processes should be well planned with precision and be monitored to be made adequately successful. One of the many successful ways of tracking the efficacy of QA activities is by using correct metrics across bug potting and resolution and using automation testing. Overall QA will involve extensive testing and verification to ensure that all under developments products or services are working as expected.

What is QA Skill Assessment Criteria?

To evaluate a QA person’s skillset, it requires assessing the individual’s knowledge of QA practices and ability to perform QA related tasks. We will delve deeper into QA related tasks below, but, overall, these tasks help evaluate the candidate based on his/her technical competency, analytical understanding, leadership, ability communicate and share his/her findings easily, yet most importantly being able to a pro-problem solver with a high assessment of detecting errors in early stage and resolving them effectively.

Based on the high aptitude and problem finding and solving ability of QA professionals, companies in the wider market use QA skills assessments for a broader evaluation across several job roles, but most importantly QA engineers are assessed for software teasing engineer roles. This is primarily to test their knowledge on QA methods, project management, communications, problem solving ability, diagnosis, etc.

Overall, QA skills assessments not only help find the best software testing professionals, but also filter out several potential professionals with strong aptitude and problem-solving ability.

Why are QA Skills Important?

There are several characteristics that make an effective QA tester, let us understand a few of these in detail below.

Effective communication: The work of a QA professional is to identify errors and issues through repetitive product testing. Whilst these errors are identified, it is also important to log and document these, while effectively communicating and explaining to fellow testers for quick resolution. For this it is essential that QA teams regularly make their teammates aware of any mistakes made previously, or bugs found earlier. Effective communication comes as an added advantage in tactfully explaining any persisting issues. Overall, clear and crisp communication helps in avoiding any work conflicts and missing out on any progress or problems.
Active listening: Another important aspect of a QA’s role is active listening. In the work to constantly test underdevelopment applications, it is equally important to be actively listening and taking inputs. As part of active listening, a professional is expected to engage in fruitful discussions by not just agreeing but also understanding and sharing valuable inputs. In total, this means being able to ask and gather required information from a pool of open-ended questions and scenarios.
Attention to detail: Whilst professional as QAs might be able to communicate and listen actively, it is also important to have very high attention to detail. As the work revolves around finding unknown errors, there needs to be high attention to detail to observe, recall (previous instances), and spot what is not visible in general working scenario. Over and beyond this, QA professionals are also required to handle and process large volumes of data and information and constantly discover aspects that might have missed general attention of peers and other testers.
Time management: Another important quality trait is effective prioritization and time management. Since the work majorly revolves around working on unlisted bugs, and constantly identifying new problems – the priorities of which majorly depend on the impact that it is creating. Sometimes a small feature malfunction can have a deeper impact than most seemingly bigger errors. Also, effective time management ensures that you are in-line with your timelines and projects.

How do QA metrics improve Test Processes

QA metrics in the field of software testing allow for constantly tracking and updating the work status of undergoing activities and overall progress. These moreover help in assessing the end-to-end effectiveness of the team’s projects and overall software quality. Further, test analytics help in determining the scope of capacity to undertake new projects, development, etc.

QA metrics also help in deriving an estimation of the time required for any test approach such as – regression testing by tracking the number of test cases undertaken or ongoing. These metrics help in estimating the time that the test processes will require in effective completion. Moreover, QA metrics help make the overall process more efficient and quality-driven.

QA metrics also offer insights to the behaviour and functions of the software application. The deep understanding based on case-to-case scenario and data driven insights also help in identifying and fixing bugs quickly.

In the wider scope of things, it is easier to implement software testing methods with QA metrics. As a result, it helps the QA team to better equip and effectively scale the overall Software Development Life Cycle (SDLC).

Types of QA Metrics

Since there are several QA metrics available in the wider software testing domain. Thus, these are further classified into three distinct groups for better understanding, as following:

Process Metrics: These set of metrics help in defining the features and performance of the software application, and further used in improving the overall process efficiency for SDLC. A better example to understand this metrics would be test cycle time, density of defects, and test case execution rate.
Product Metrics: Such a metrics helps in delineating the software application’s overall design, quality, performance. To better understand it we can say, relatable examples include code complexity and coverage, and severity of defects.
Project Metrics: This metrics helps in effectively measuring the efficiency of software testing, development team, and the tools implemented for QA processes. In general, this metrics helps in measuring the generic quality of projects whilst estimating the overall productivity of the team, its running costs of testing, and any possible flaws in operations. Good examples to consider include – cost variance and estimations, and requirement gathering.

Type of Manual QA Metrics

Manual QA metrics help in assessing the overall quality and effectiveness of manual software testing procedures. These are helpful in evaluating the effectiveness of manual software testing process, including but not restricted to test case design, test execution, defect management. There are basically two types of manual QA metrics, these are:

Base or Absolute Metrics

Such metrics in software testing are examples of quantitative measures derived from raw data that is generally collected during test case development and execution. The data is further tracked throughout the Software Testing Life Cycle (STLC) and is used to generate essential information about the testing process. These include information and statistics on the number of test cases executed, their outcomes weather passed or failed.

A common term across these metrics is defect density, i.e., the number of defects per code unit. This is mainly used to exemplify an absolute metric that accurately reflects the testing progress and its time to completion. More examples include the total test cases, passed and failed test numbers, and blocked test cases. In addition, several base QA metrics help in assessing different aspects of testing. These include several categories of test cases, such as: total number of test cases, number of test cases passed, failed test cases, blocked test cases, bugs identified, critical bugs found, determined and actual test hours, bugs detected post-release, etc.

Overall, these metrics help in providing valuable insights into the effectiveness of testing process and the overall quality of the software.

Calculated or Derivative Metrics

In software testing, calculated or derivative metrics come from base metrics derived through rigorous mathematical calculations. These offer deeper insights into the overall testing process undertaken within an organisation or by QA team. A few common examples of these include test case execution rate, defect density, and effectiveness of test cases recorded.

On the other hand, derivative metric is also the percentage of defects found per test case. These are calculated by dividing the total number of defects found by the total number of test cases executed over a period. Derivative metrics facilitate detailed analysis and thus also allow identification of trends, correlations, and areas for improvement in the assessment process.

For the derivative metrics to accurately reflect the intended aspect of the software application or process being measured it is important to choose the appropriate combination of metrics. Overall, understanding various types of calculated QA metrics is indeed essential for effective measurement and evaluation.

How to Calculate QA metrics?

There are several steps to calculate QA metrics. These particularly depend on the specific metric that you are interested in measuring. Below is a detailed guideline on how to calculate QA metrics:

Define Metrics: Begin by clearly defining the metrics you want to measure. These can be defect density, test case effectiveness, or any other aspect of quality. Be sure that you have a clear understanding of what you are measuring and why is it required.
Gather Data: Begin by collecting the necessary data required to calculate your preferred metrics. This can include the overall number of test cases executed, defects found, time taken in testing, etc. be watchful to gather accurate data.
Perform Calculations: next, make use of appropriate formulas and calculations to seek help in deriving the desired metrics from the data collected. Across different scenarios, different metrics may require different formulas.
Interpret Results: Once the metrics are calculated, you can interpret the results in the context of your testing objectives. It is now helpful to analyze the metrics to gain insights into the quality of the software, and identify areas for improvement to help make informed decisions.
Take Action: Next, use the insights gained from the metrics to drive improvements in the testing process.
Monitor Trends: Now, continuously monitor and track the metrics over time to identify trends and patterns.

Testing Using Real Cloud Devices for Free

Whilst there are several testing tools and devices, one prominent platform for QA testing is LambdaTest. You can leverage LambdaTest’s cloud Selenium grid, that features over 3000 real browsers and devices, to conduct all necessary tests in authentic user conditions. It is also a reliable platform for effortlessly conducting manual testing on the cloud.