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Black box testing implies an infinitesimally large source of software testing techniques which would help achieve excellent test coverage and saves time. Read the blog thoroughly to have a better understanding of what black box testing is all about and the underlying techniques one must use to impact your subsequent cycle of test.
Black Box Testing can be defined as a type of Software testing that the internal working structure (the source code) is unknown. The testers tend to validate all the functional aspects of the requirements without reviewing the source code. Presume that the code as being hidden inside a black box. For all sets of inputs, the tester compares the corresponding expected outputs with the actual outputs. Here, testers won’t review the internal code structure and don’t necessarily have to have knowledge of its structure or internal paths. Instead, they rely on the in depth knowledge of the software requirements to draw up test cases.
Black Box versus White Box Testing If you consider Black box testing as a type of software testing that denotes “unknown” internal software, then think of white box testing as “known” and transparent.White box testing mandates the tester to have expert level knowledge of the programming language and the corresponding system structure being used. Unlike black box testing, whose dependency is majorly on the end users’ perspective, white box testing on the contrary includes techniques that an end user need not have to simulate because software testers role is limited in only reviewing the code in finding issues pertaining to security, information flow and speed of execution.
Black Box Testing Techniques The following black box testing techniques aims to cover strategically the product while reducing the total count of test cases:
Equivalence partitioningThis black box testing intents to reduce loads of rework. Here test conditions are grouped together in each group, as a result of that only one test condition requires testing. If that condition is found to be true or if it works fine, then all of that group’s conditions must work too. Take for instance, with an uploader, this technique is used efficiently to test file types and sizes without having to overlap each and every test conditions and combination.
Boundary value analysis is a concept where you test the boundaries of what range of values are permitted. For instance, if you need the system to accept a number between 1 and 100, you may have to test those boundaries, as well as just over and just under ie (0 and 101) by effectively employing this method you save lot of time by not testing the numbers in between.
Decision table testing This method is employed for complex combinations, where varied inputs lead to different decisions (unlike the earlier two types equivalence partitioning and boundary value analysis). Popularly known as cause and effect tables, decision tables will help us clarify expected outputs and make sure that no combinations are missed while formulating test cases
State transition testing A system which gives different outputs for the same combination of inputs depending on external conditions requires state transition testing. For example: an ATM machine which dispenses the tester 80 USD initially and then later doesn’t give the tester 80 USD (Reason: account has dipped down below the set amount); or a traffic light which turns to green when the sensor is triggered, but later gives a different result (because someone else was there first and is allowed to turn left before you go straight). These examples clearly illustrate the fact that for the same set of inputs there is different outputs, because the system has “transitioned” to a new state.
Exploratory testing In this type of Software testing, the tester simulates user behaviour and subsequently ensuring system to maximize test coverage. This is almost on par with a black box technique because here no knowledge of the internal code is required. Instead, testers are aware of the software requirements and its expected behaviour. From there, they can behave like users—but always retain their testers mindset.
Error guessing The term error guessing is self-explanatory. A tester “guesses” wildly where errors are most likely to occur. The testers’ own experience, knowledge of the software application, results from earlier test cycles, customer issue tickets, previous release issue, and risk reports are taken in to due consideration. When we try to choose which module of the application will receive the most thorough testing, error guessing is a must.
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