In the last couple of years, software development underwent many evolutions in terms of new methodologies, approaches, development tools, and even the mindset of the people using the tools. Due to new efficient approaches to development and users’ uncompromising expectations to quality assurance, testing also gained almost equal importance as development.

When it comes to software testing, there has been a significant increase in the number and variety of testing tools with multiple features and functionalities, which include both open source and proprietary tools. Due to the change, or rather ‘advancements’, in testing trends, testers are now considered as information brokers. They also have to be updated on emerging as well as modern mainstream technologies to design effective test strategies.

All of these facts emphasize the influence of technologies on various industries, and the influence will persist as long as there are advancements in technologies. If you look at a big-picture view, you would notice new technologies gradually shaping up the future of software testing. Here are 4 such technologies that will impact software testing and transform it in the near future.
 

Artificial Intelligence

 
AI, being the new buzzword, is at the top of almost every list of influential modern-day technologies. Thanks to AI, self-driving cars and intelligent digital home assistants are not sci-fi concepts anymore. They are today’s reality. AI’s influence spread across several sectors including finance, health care, travel & transport, and, of course, software testing.

However, as of now, the AI in software testing is still in its infancy. Only a very few tools that use AI/Machine Learning technologies are considered reliable for authoring and executing functional testing, end-to-end testing, and regression testing. AI finds its use primarily in test automation associated with UI. The algorithm evolves by learning from the test cases created by users, eventually becoming capable of creating test cases on its own adhering to specific preset conditions. AI algorithms can also track changes in the code made by developers which may affect test cases that were already performed prior to the changes. This means the tester won’t have to spend maintenance time on test scripts.
 

DevOps

 
The DevOps approach promoted collaboration between the software development and operations team, thus ensuring constant automation and monitoring throughout the software development lifecycle (SDLC). DevOps is likely to bring major changes to software testing in the coming days.

For instance, DevOps may require the QA tasks to be aligned to ensure a hassle-free Continuous Integration/Continuous Delivery cycle. We can also expect QA environments to be standardized in a DevOps ecosystem. However, for DevOps to truly make a difference in testing, automation is the key. Automation and DevOps are quite dependent on each other as one cannot be effective without the other. Considering that fact, we can safely assume that automation will have great value in the future of software testing, more than it has now.
 

IoT

 
Another technology that shares the same spotlight as AI, IoT at present is considered to be very promising. The advent of smart wearables and the concept of smart homes and connected devices give IoT a lot of hype, garnering it major investments from tech behemoths. However, behind the flashy concept lies the sophisticated reality of multiple communications and integrations taking place every second.

The data that IoT devices share are transmitted through the cloud seamlessly in real-time across multiple connected devices and apps. The notification should reach the right user at the right time as well. Testing such sophisticated functionalities can be very challenging for testers. Because IoT introduces such complexity, it’s expected that software testing will adapt to meet the challenges with further evolutions that focus more on integration testing.
 

QAaaS

 
QA as a Service is not anything new, and has been around for the past couple of years, enabling companies (medium-large sized businesses) to meet their software testing needs effectively. Not all companies that provide enterprise application services offer QAaaS solutions. But those that do can make various aspects of the testing process much easier.

QAaaS providers offer in-depth test reporting features with logs, screenshots, and even video logs. They also facilitate easier integration with Continuous Integration systems and provide automation tools to reduce coding time. QAaaS providers can also handle the maintenance of servers that run automated tests so that team members would be able to focus more on critical testing tasks.

Owing to the many benefits of the service, QAaaS could be standardized very soon. The service is not yet accessible to businesses of all sizes. However, we can expect it to be much more affordable and refined with better offerings in the near future.
 

Conclusion

 
Software testing is expected to get big changes starting this year. It’s just a matter of time as other technologies advance to being more affordable and accessible to all kinds of businesses. Even under such positive conditions, the mindset of the testers need to change as well, in order to accept and adapt to using better technologies to ensure quality.

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Complete testing of a software or mobile app ensures that it serves the purpose it was built for, while meeting all requirements without compromising quality or functionality. For this, testers perform a variety of feasible tests based on pre-determined testing strategies and the availability of resources. The entire software testing process provides an overview of the quality of the software and its risk of failure to end-users and stakeholders.

Among the many types of testing employed, black box and white box testing are typically the most common in almost all software development projects. Let’s explore what it is that both these testing types are for, and their key differences.
 

Black box testing

 
Testers perform black box testing when they don’t have any information about how the software works internally. The high level testing technique tests the behavior of the software when it’s subjected to various conditions. The tests are conducted from an end-user or external user’s perspective. Black box testing can be performed on virtually every aspect of software testing including unit and integration testing, system testing, and acceptance testing. It’s also known as box testing or functional testing.
 

White box testing

 
White box testing is generally considered as low-level testing. It tests the internal functioning of the software, and is based on coverage of code statements, branches, paths, conditions etc. White box testing is also known as glass box, transparent box, or code base testing. Inputs are chosen to exercise paths through the software’s code to get desired outputs. It’s usually done at the unit level though in some cases, it’s also applied at integration and system levels.
 

Key differences between the two

 
Internal & External

Black box testing tests the external behavior of the software while the testers have no knowledge of the internal structure or behavior of the product. Testers who know the internal structure of the product performs white box testing.

Programming & implementation knowledge

Testers performing black box testing need not possess programming knowledge or implementation knowledge to do so. However, to perform white box testing, programming knowledge and implementation knowledge are mandatory.

Automation prospects

Black box testing is considered as an advanced testing technique where programmers and testers need to be involved directly. This makes it challenging to automate black box testing. White box testing, on the other hand, can be automated and is quite easy to do so as well.

Major techniques

Black box testing can generally use one of the three following techniques:

• Boundary Value Analysis: Focus on testing the input boundaries that are most likely to end up giving erroneous outputs.
• Equivalence Class Partitioning: Focus on identifying and classifying errors so as to reduce test cases.
• Error Guessing: Focus on finding defects first and developing corresponding test cases.

When it comes to white box testing, the tester’s knowledge about the system allows him to develop test cases to discover internal defects. The techniques involved include:

• Statement Tests: Every statement within the code should have a test associated to it, and each statement must be executed in a test cycle.
• Decision Tests: All decision directions should be executed in a test cycle.
• Branch Condition Tests: The conditions associated with a specific decision should be tested to see if they are working properly.
• Data Flow Tests: All variables and data within the system are tested.
• Multiple Condition Tests: Each point of entry within the code is tested in a test cycle.

Conclusion

 
Many software development companies tend to not completely perform black box testing especially when there are time constraints. They instead do some quick tests to see if the software’s core features are functional. Some companies perform neither black box nor white box testing but instead implements grey box testing – a combination of black box and white box testing done only at the interface level.

In this age, product quality and usability are more important than ever which demands great effort from testers into ensuring that the end-product was built the right way, with the right functionalities, and without defects.

Pair testing, often referred to as Buddy testing, is a software testing technique where two people from the project team test the same feature in parallel under the same conditions while exchanging ideas. Contrary to how it appears, pair testing does speed up test assignments while delivering more quality results.

This guide serves to introduce beginners in software testing to the concept, and where and when they can adopt the technique to maximize its benefits.
 

Pair testing buddies

 
Pair testing is generally done by a developer and a tester. However this isn’t the only way to do pair testing. A technical writer and a tester can be paired up to document how the software would be in the next release. A tester and the client can be paired up to recreate an error scenario that the client identified, and fix it. A solution architect and a tester can also be buddies in pair testing, which could lead to exploratory testing with respect to what if scenarios. A tester and a developer can team up to investigate odd bugs.

So basically, pair testing can be done with almost anybody in the project team, especially if it’s a Scrum project.
 

Where you can apply pair testing

 
In a Scrum project, pair testing can be done throughout the software development cycle – in one sprint or many. It can be a good learning experience for junior testers. If the business analyst needs to see how a particular feature works and identify possibilities for further enhancements, he can do pair testing.

A tester or developer who wants to investigate an odd bug or look into some issue with the application that’s becoming a problem for the client, can speed things up with pair testing. In addition, almost every task directly associated to testing done by a pair from the project team may fall under pair testing even if it’s noticed to be so.
 

Basics of doing pair testing

 
Pair testing can either happen spontaneously or it can be executed with a predefined approach. For the latter, testers should begin by defining the preparation for the tests they will be doing and then plan the execution. Both parties should agree upon a time period and actively make an effort to finish testing as planned.

Spontaneous pair testing can happen in many scenarios, a common example of which would be when a tester gets stuck while looking into a problem and seeks aid from a colleague. While the partnership works with different test data, shares ideas, and explores new aspects to test, they’d also find the cause of the problem that had been bugging the tester at the beginning. This can be considered as unplanned pair testing.

Another situation is when the tester explains how a feature would work to a colleague. The colleague might have questions that didn’t occur to the tester. This is also unplanned pair testing.
 

Conclusion

 
The bottomline is that pair testing is a beneficial practice for any software development company, provided they have replaced traditional development methodologies with Agile. Making an execution plan, setting up the test environment, and ensuring that your testing buddy bought into the concept of what it is that you are testing – this is how you do pair testing. Give it a go once and see how it can speed up application testing.

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APIs have always been a vital part when it comes to software development and how the software serves its purpose. Web-based applications are too common now, and are heavily relied on by organizations and individuals alike. This makes proper API testing more crucial than ever.

In this post, we will be sharing 6 great API testing tools that would come in handy for software testing efforts this year.
 

Soap UI

 
Soap UI is a popular open source testing tool used primarily for web services testing and API testing. Its functionality is useful for invoking, development, simulation, web service checks, load testing, functional testing etc. to name a few.
 

Frisby.js

 
An open source JavaScript library, Frisby is built on NodeJS and Jasmine (a Behavior-driven development style test runner). The community considers it a great REST API testing framework facilitating simpler and faster testing of API endpoints.

Frisby.js 2.0 is coming out soon with further improvements making the underlying Jasmine structure more extensible and exposed. The Jasmine node test runner makes it possible to run Frisby tests in a continuous integration ecosystem.
 

Karate DSL

 
Karate DSL is an open source command-line testing framework that uses BDD to define API tests. The framework is more familiar to people who use Cucumber JVM for BDD tests, as it’s built on Cucumber JVM. Like Frisby, Karate DSL also supports seamless integration and continuous delivery pipelines.

It also supports testing live environments, in addition to providing comprehensive support for common HTTP calls that use HTTPS, HTTP proxies, SOAP/XML etc.
 

Postman

 
Unlike its other counterparts mentioned above, Postman is a hosted GUI API Testing client used for exploratory testing primarily. It features documentation, sharing, and monitoring support in addition. Its broad set of features make it a very useful API testing tool.

Another advantage is that Postman runs on local machine, giving control of data. However, not all software testing companies prefer using Postman, and it’s not because of a lack of features. Many companies would have security restrictions due to which they won’t be able to use a fully hosted option. Like most other tools in this list, Postman also supports testing in a continuous integration pipeline.
 

Assertible

 
Assertible is more popular and preferred compared to Postman as it focusses more on automation and reliability. The tool also features HTTP response validation with turnkey assertions.

Its greatest advantage is the fact that it allows automation of API tests through every step of a continuous integration/delivery pipeline, making things much easier for smaller groups of testers.  It can integrate with tools like GitHub, Slack, and Zapier, and supports running API tests post deployment.
 

Apigee API Studio

 
Testers can use the API Studio from Apigee to build APIs. The Studio also facilitates easier and effective API testing thanks to its many features designed specifically to simplify testing. One of the major use cases is for API Response Simulation with mock HTTP responses. However, it is still in its beta but the community expects many updates this year which will add more features to the already useful tool.
 

Conclusion

 
There are a great number of useful tools for thorough API testing, but the ones listed above are quite unique. Most of them are still rising among the ranks but handy nonetheless. This list should be helpful for testers who would like to explore tools that can make their work easy. It’s a new year, and introducing yourself to new testing tools might be the change you are looking for. Try them out.

Without adequate QA & testing, no software product can actually serve its purpose or do what it was designed to do effectively. Experienced developers will always have their QA & testing teams caught up on the latest trends in the dynamically evolving testing sector, particularly at present times when new technologies are coming into the frame.

To keep up with competition in an evolving industry, analyzing and even foreseeing the trends could make all the difference. When it comes to mobile app and software testing, knowledge on the trends beforehand could get you great leverage when the time comes.

That said, here are a few of the most noteworthy emerging trends that will make big waves in 2018’s technology arena.
 

The progress of IoT

 
The Internet of Things is a relatively new technology, but its growth in a short span of time is nothing but astonishing. Its potential is amazing as well. The rapid growth of such a revolutionary technology forecasts big changes in 2018. This means testers have their work cut out for them.

They will have to deal with software and applications that connect devices with each other and with the internet. This brings concern as much as excitement for QA and testing professionals primarily because it’s hard to determine and establish security policies, and define testing tools, for a new technology like IoT. Nevertheless, IoT products will have to be tested for their functionality, effectiveness, and reliability. And there’s still time to prepare.
 

The much anticipated merging of Agile & DevOps

 
The general idea behind DevOps is to facilitate seamless collaboration between various departments in an IT company. Agile teams today have already started including test automation professionals. The present shift in software and mobile app development trends call for more progressive and iterative testing operations, and this is what a DevOps ecosystem essentially demands as well though continuous testing is more commonly used.

Today’s DevOps environment can benefit from test automation on every level. Testers will have more responsibilities – from verification of requirements and configuring integration toolsets to creating DevOps-compatible automation frameworks.

From what the experts are predicting, we can expect the merging of QA testers and developers very soon. This would subsequently result in faster delivery and QA, and in turn a higher ROI.
 

Open source tools will dominate

 
Technically, open source tools already have great authority in the testing industry today. This year, we witnessed a surge in the adoption of open source tools and services by companies for executing test automation and management. This could be a foreshadowing of further expansion of open source next year.

We might likely get introduced to advanced open source testing tools with reliable community support. To conclude, 2018 could very well be the year when open source finally dominates the testing sector across the globe. It’d be wise to prepare for it beforehand.
 

Performance engineering

 
This relates to mobile app development, and is one of the most anticipated trends in the digital realm. The success of a mobile app also depends on the app’s user experience. With the best UX starting to become the norm, it’s no surprise that Software/System Performance Engineering (SPE) has started replacing conventional performance testing.

This new systematic approach will be focusing on the architecture, design and implementation. This subsequently cuts the development costs while ensuring that the product meets performance requirements before its release.
 

Conclusion

 
The software development and testing industries are in for some major changes next year. Software has now more priority across the world, and the number of mobile devices keep increasing tremendously. These shifts in culture brought forth many challenges to both testers and developers to deliver tested applications that provide great user experience and functionality.

The trends mentioned above is a wake-up call for developers and testers to add to their knowledge and enhance their skill sets.