3 ways to optimize regression testing


No doubt in the fact that regression testing has helped in making things easy for people and teams indulged in testing, but what about optimizing regression testing? Well, there are certain ways that can be used in order to get a better optimization of regression testing. Testing was once considered one of the not-so-interesting things at the end of the project before delivering the product into production. Whereas with the inception of agile testing management platforms, it can be said that testing has become one of the crucial steps in the software development process. And this is where regression testing comes into play.

Since we are looking forward to the ways of optimizing regression testing, let us also talk about the Headspin platform that has been helping businesses better their digital experience. Headspin regression testing basically focuses on three step process when it comes to delivering best to the customers, the process works under a three-steps which include building, running tests and the last one with the delivery (ship); Headpsin has been focusing on some of the important aspects of “run test” which includes:

  • Implementing Headpin’s Regression Intelligence
  • Intelligence analyze degradation
  • Getting aggregation and regression insights

It is worth mentioning that the regression tests have made quite a positive impact on the stage, where a whole bunch of testers were stuck upon testing all those codes before delivering the end product to the production team. Well, regression testing has helped in a lot of ways by decreasing the time where an individual or a whole team might be stuck upon.

Before we dig a bit deeper into the ways of optimizing regression testing, let’s have a quick look around what is regression testing? Later, we’ll also get along with some other ways of optimizing regression testing.

What is Regression Testing?

As previously mentioned, testing was considered one of the not-so-interesting tasks while getting along with the overall software development process; however, after getting along with agile test management, it can be said that the testing has taken quite an important place in the ecosystem. But having an error while testing is performed over the whole process can be a challenging task overall; I mean, think about retesting the whole thing just after an update, or any changes around a patch; well, this is where regression testing has helped on delivering the overall stability while getting along with the functionality of the existing features.

In simple words, regression testing is a testing type that enables you to verify that the changes made in the collection of source code, not impacting the software functionality.

Since we are all done with the overview part of what regtest is? Let’s hop over to the next section, which involves some of the ways which can be used for the optimization of regression testing.

3 Ways to Optimize Regression Testing

There are some steps that can help you in optimizing the process of regression testing; this basically involves some steps, which include regression test selection, code review, and metric monitoring.

So, let’s have a good look around how these ways can be used in order to optimize the process of regression testing. When talking about the regression intelligence, Headspin offers some excellent features, the Headspin platform can be helpful in making things work in aspects of monitoring, analyzing your mobile and browser user experiences. Well, build-over-build regression and location-to-location comparison are some of the primary aspects that are offered by Headspin in terms of regression intelligence.

Regression Test Selection:

Well, this can be considered as one of the best ways to optimize your regression testing operations, having an indexed selection of text cases (standard) the best lead-in to regression test coverage. It is worth mentioning that the standardized level of test cases should allow for version updates; another major factor worth considering is the automated tests that look after different parameters like timing and perimeter requirements. As a result, the well-selected standard test cases offer a logical platform for the effective search for bugs; in simple words, the well-standardized selection of test cases can help in better bug detection. Therefore, performing regression test selection can be considered as an optimized way of performing regtest.

Now, since we are now versed with the first way of optimizing test selection for regression testing, let’s get along with the second way, which is code review.

So, let’s take a look at that!!

Code Review

But before we take a deeper dive into code review as an optimization step, let’s take a quick overview of what code review is and why it is considered an essential step in software development.

Code review, which is also called Peer Code Review, is basically a checking activity that can help get along with a better correction process for the codes; this, as a result, helps accelerate and filter the process in software development. The code review is an activity that works upon looking after the code of another fellow programmer, which focuses on consciously and systematically looking for any mistakes that might not exist in the code. 

Basically, the code review focuses on four primary areas, which are:

  • Formatting consistency in overall software designing
  • Getting along with consistency as per the project requirements and coding standards
  • Code Issues
  • Overall Quality of documentation

In addition to all this, it is worth considering that the Code review can help in multiple aspects, including:

  • Quality Assurance (QA) testing: The Quality assurance testing can be considered as one of the primary key features that make the source code easier to understand for testers and specialists; if looking forward to what makes QA testing an important aspect is its identification of issues in the that might be leading to poor quality of codes, this not only focuses on making things easy for specialists and testers but also focuses on checking the quality of the code.
  • Code Quality Improvement: If we look forward to another benefit of code review is the improvement of code quality, this, as a result, helps in getting known to any errors that might get along the way before the code starts to get indulged into more significant issues in terms of errors which might result into the delay in getting along with the end product.
  • Knowledge transfer: Another great benefit of using code review is the knowledge transfer as reviewing other developers’ code can help in learning more and more in terms of coding; therefore, Code review can work as a great knowledge source for developers.
  • Better documentation: It is pretty evident that the code review can help in making things better in terms of documentation, which as a result, can help you, developers, to easily add or improve features across software development.

All these benefits, as a result, can help in making things easier for developers as code review can help identify bigger errors and issues that might occur in the future. In addition to that, code reviewing can also help in making things good in avoiding delay, which might be getting along its way for testing and reworking on the code in software development.

After getting done with the code review, let’s take a look around the 3rd way of optimizing regression testing: Metrics Monitoring.

Metrics Monitoring

Metrics are considered as one of the most basic but crucial parameters in software development, and having a complete overlook of metrics can help in getting along with a better end product. Software metrics do speak a lot in terms of software characteristics, and this is why performing metrics monitoring can be considered as one of the important activities in the software development process.

As I have already mentioned that metrics monitoring can be considered as an excellent thing overall in terms of software development. Having an overview of all the metrics might not be necessary, and this is where KPIs (Key performance indicators) are considered. Having an overview around KPIs can help in making things for:

  • Controlling the project progress
  • Increasing the ROI
  • Correct distribution of tasks
  • Reducing the cost of the project

Since we are looking from the testing perspective, let’s have a glance around how KPIs can make some difference in terms of testing quality. Basically, the testing quality KPIs can help in measuring different aspects, which include productivity, quality and progress of the software testing. Here are some of the metrics that can be used for determining the degree of the QA team’s testing quality which include:

  • Test Efforts: TE is considered as the number of tests that were conducted under a certain time period. Therefore, it can be expressed as:

Number of tests under a certain period = Number of test runs/ Total time taken.

  • Test Coverage: Well, this test coverage is the percentage of software requirements covered with the test cases; the test coverage can be expressed as:

Test coverage % = (Number of test performed/ Number of tests to be run) x 100

  • Test team: There is no doubt that the team members with proper work allocation are quite an important aspect overall. In simple words test team measures the work allocation for each team member; the test team metric includes:
  • No. of defects returned per member
  • No. of test cases allocated to each member in the team
  • No. of test cases which are executed by each member
  • No. of open bugs to be retested by each member

All these KPI group measures can help in getting along with better output in terms of your testing strategy and testing quality.

How can Headspin help in regression testing/regression intelligence?

Headspin’s regression intelligence can be really excellent in different aspects for implementation of Headspin’s regression intelligence with analysis of degradation and getting aggregation and regression insights.

Getting back into optimization, we are now all done with 3 ways of optimizing the testing process on the basis of regression testing, let’s have a brief about how these simple ways can help you in getting better end products.

Talking about the first way, which is regression test selection, can help in delivering an indexed selection of text cases (standard), which as a result can help in a number of factors, including better bug detection, therefore making it an excellent way of optimizing alongside the regression testing process.

Now comes the second part, which is code review; the code review can be considered as my personal favorite as it involves a number of benefits which include Quality assurance testing, better documentation and knowledge transfer, as testers can learn a lot just by reviewing one code of the fellow testers. All these aspects can help in making things easier for developers as code review can help in identifying bigger errors and issues that might occur in the near future while getting along with the last steps of software development.

Metrics monitoring is the 3rd way of optimizing regression testing; well, there is no doubt that metrics work as one of the crucial factors in development; and performing complete monitoring around these metrics can help in testing quality, performing correct distribution of tasks, and increasing the overall productivity, performance and quality of the software program.

All these steps can help in increasing the efficacy of regression testing and offering improved product quality. Basically, all these practices and ways of optimizing regression testing can help in better identification of bugs and in a more efficient manner in terms of time, productivity, etc. So these were some of the activities that can be used by development teams for getting better results in manual testing (regression testing). 

Since you are now well-versed with what are the features and how optimization can be performed in regression testing, let’s take a look at the another aspect as well, it’s also worth mentioning that Headspin also works upon some of the different aspects of build-over-build regression and location-to-location comparison. The build over build regression by Headspin’s AI-powered regression intelligence integrates CI/CD processes, so that degradation issues can be automatically detected for every build of your app. Whereas if you look forward to Location-to-location comparison, Headspin’s regression intelligence lets you compare user experience KPIs across real devices in over a hundred global locations to identify network, API, cloud or even edge-based issues.

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