Common problems in software testing

The desire to offer competitive software solutions to the market instigates the optimization of the work cycle, in which testing plays a crucial role. With a limited budget, most issues related to product adaptation and its further development are solved through testing. Why? See here:

Depending on the type of software, the technical base and testing methodology are selected. It is worth considering that software applications make up a significant market share, but are by no means the only ones. Along with native and desktop applications, there are embedded software, machine learning and AI technologies.

At the same time, any software product is subject to testing, regardless of the purpose and scale. In practice, it does not matter how the developer treats testing, whether it is neutral or with increased attention. Only after a successful test, the product can be placed on the seller’s site. These requirements are not uncommon in any product niches – economy or premium.

Developers identify five main obstacles due to which the testing process can be accompanied by difficulties:

1. Lack of clear indicators in quality standards

The requirement for quality is a mandatory condition for any large platform. At the same time, each system (IOS, Android) sets individual quality requirements. This is quite logical, because the target audience of operating systems is significantly different.

While for IOS users, buying an application seems like a common thing, Android fans usually do not have enough financial resources to buy software. In this regard, developers get at least two hard opposites: for IOS, you can practice desktop products, and for Android, only native ones.

As a result, the difference in the software environment cannot but affect the requirements. The developer will need to look for solutions that will function equally well under the guidance of any operating system, and the only optimal way to do this is through complex testing.

2. Limited test environment

When using automated systems for testing, a pre-written script and settings are used. Of course, the moderator can correct the process in the right direction, but the system will only test the product in the specified settings of a particular software environment. Under operational conditions, the environment changes very often as browsers are updated, platform rules change, security requirements change. As a result, it is difficult for a developer to compile an optimal set of conditions, because many values ​​are simply unknown.

Large companies can afford to keep testers on staff, whose task is to regularly test updates for compatibility with the changed software environment. At the same time, small players are left to be content with the “reconnaissance in force” tactics, in which most possible errors are determined only during operation.

3. Hardware dependency

Automated systems cost decent money. Perhaps this is the main problem that testers face. Most often, testing occurs using software solutions based on cloud technologies. That is, the moderator simply does not have the opportunity to directly use the necessary technologies. Conditions imposed by cloud sites include payment for the use of technologies and imply costs in case of overspending of approved resources.

4. Impossible requirements

The conditional “conflict of goals” on the issue of requirements arises as a result of inflated expectations on the part of users. The fact is that to test a software product, knowledge of programming is not necessary. As a result, the tester determines a set of requirements without much reference to complexity. The programming team, in turn, cannot make edits, since recommendations from testers require a significant change in concept or complex workflows.

Requirements gathering has a direct impact on complexity, as it forms the basis of the test specification. Therefore, it is important to prescribe the functions that the program should perform and determine the ultimate goal of testing.