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DateDec 20, 2016
ISTQB CTFL Practice Test Questions, Exam Dumps
ISTQB CTFL ISTQB - Certified Tester Foundation Level exam dumps vce, practice test questions, study guide & video training course to study and pass quickly and easily. ISTQB CTFL ISTQB - Certified Tester Foundation Level exam dumps & practice test questions and answers. You need avanset vce exam simulator in order to study the ISTQB CTFL certification exam dumps & ISTQB CTFL practice test questions in vce format.
If a financial system has a miscalculation in one of its features, we call that a functional defect, which is of course unacceptable. Some systems might not have obvious functionality problems but still be unusable. Consider a system that is slow or a system that cannot accept more than 1000 users at a specific time. This is still unacceptable. We call those kinds of problems non-functional defects. One role of testing is to ensure that thekey functional and non functional requirements are examined beforethe system is released for operation and any defectsare reported to the development team to fix. We use testing to help us measure the quality of the software in terms of the number of defects found from the tests run and the systems covered. by the tests saying that, do you think that testing increases the quality of the software? The answer is no. Testing cannot directly remove defects, but it just reboots them. Hence, testing cannot directly enhance quality. Testing can give confidence in the quality of the software if it finds few or no defects. A properly designed test that passes reduces the overall level of risk in our system. By reporting defects, it makes the removal possible, and the quality of the software increases when those defects are fixed. Lessons should be learned from previous projects. By understanding the root causes of defects found in other projects, bosses can be bribed, which in turn should prevent those defects from recurring and therefore improve the quality of the mutual systems. This is an aspect of quality assurance. Therefore, testing is one component in the overall quality assurance activity that seeks to ensure that systems enter service without defects that can lead to serious failures. So why is testing necessary? It is possible that it will return a false yes due to software. How do I learn about the quality of the software? Yes. to fill the time between delivery and the release date? I don't think so. To prove that the software has no false positives? Well, we can never prove that the software has no errors. So the answer is no because testing is included in the budget plan? No, because failures can be very expensive? Sure. Yes, to avoid being sued by customers? Yes. to stay in business? Sure. Thank you.
So we have learned why software testing is necessary. So what exactly is software testing? Different viewpoints in testing take different objectives into account. For example, testing while developing the software. The main objective may be to cause as many failures as possible so that defects in the software are identified and can be fixed while delivering the software for acceptance. The main objective may be to confirm that the system works as expected and to gain confidence that it has met the requirements. In some cases, the main objective of testing may be to assess the quality of the software with no intention of finding or fixing defects and to give information to stakeholders so they can make decisions about this information. Some other testing activities are there to prevent bugs from being introduced to the software. This is very important to understand the real objectives of testing activities. Testing the software for the purpose of finding a fix might be completely different from testing the same software to gain confidence about the level of quality. Any activity that will help achieve the testing objective is considered a testing activity. Static testing and dynamic testing We already knew that failures often begin with a human error, namely an error in a document such as a specification. We need to test these documents because it's much cheaperto fix those mistakes now than wait and try tofix them when they became defects or failures. Aesthetic testing is the term used for testing where the code is not exercised. That's why testing should start as early as possible. Static testing involves techniques such as reviews of documents, for example, requirements, design documents, and the source code, which can be effective in preventing the effects from being introduced into the code by removing ambiguities and errors from the specification documents. This topic is covered in detail in another section. On the other hand, dynamic testing is the kind that executes the programme under test with some test data. The discipline of software testing encompasses both static and dynamic testing. Notice again that both static testing and dynamic testing can be done by anyone in the software lifecycle, including developers, customers, and system testers. Both dynamic testing and static testing can be used as a means for achieving similar objectives and will provide information that can be used to improve both the system being tested and the development and testing processes. testing and debugging Some might confuse testing with debugging. Testing is a systematic exploration of acomponent or system with the main aimof finding and rebooting defects. Testing doesn't include corrections of those defects; these are passed on to the developers to correct. Debugging is the development activity that analyses and removes the cause of the failure. Subsequent retesting by a tester ensures that the fix does indeed resolve the failure. Testing does, however, ensure that changes and corrections are checked for their effect on other parts of the component or system. The responsibility for each of those activities is usually the tester's. tests, and developers debug. The final challenge is to ensure that the testing we do is effective. A good test is one that detects any defects that may exist. A test that finds no defects has consumed resources but added no value. Well, maybe just increase the confidence in the software. A test that finds a defect has created an opportunity to improve the quality of the product. How do we design tests that find effects? We should first increase the effectiveness of the test, and that's by using proven test design techniques, as we will describe in a later section of this course. Second, we should increase the efficiency of those tests, meaning we can find the defects with the least effort, time, cost, and resources.
A number of testing principles have been suggested over the past 40 years and offer general guidelines for all testing. Testing shows the presence of bugs. The cost of testing is impossible early testing The absence of errors in defect clustering specified paradox testing is context-dependent. false principle numberone testing shows the presence of bugs. When you test a software, youmay or may not find effects. If you find a fixed, then that'sa proof of the presence of bugs. But on the other hand, if your test didn't find any effects, that's not a proof that the software is error free.There's a great probability that you didn't find effects because your test doesn't cover the breadth and width of the software. Maybe you didn't select the right test data to exercise the software. Maybe the defect is waiting for a very special circumstance to fail the software. Remember the Y2K problems, where many software solutions fail because they only consider the year as a two-digit number, assuming it will always add up to 1900? If you think about those software solutions, theyused to work perfectly in the but theycouldn't operate starting the 1 January 2000. Therefore, those solutions contain defects that were waiting for a special date to show up. So we can't call those solutions "batteries," even though they were working perfectly for ages. So there's nothing like bug-free software. There is no way we can prove that. We simply need to design as many tests as possible to find as many effects as possible. Principle number two: exhaustive testing is impossible. Imagine if we have a web page where you need to enter the age of the employee, which should be in the range of 20 to 50. To test this field, you truly need to enter all the possible values in that field, both valid and invalid ones. So if this field accepts an integer that ranges from -32,767 to 32,767, then we have 65,535 possible values. Add to it a bunch of combinations of text values and special characters. Well, the user might type text by mistake, and you want your software to behave decently in all cases without crashing. We may also need to test the cases where we based numbers rather than typing them. I can drop the values and maybe try some special circumstances when entering the values, like booking spaces, deleting characters, and so on. Then say we have a total of 70,000 in value. If each value needs 1 minute to be tested—and that's very short by the way—then we would need 70,000 minutes to test this field alone. 70,000 minutes is 1167 hours, which is 49 days. testing a single field day and night. Unless the application under test is extremely simple, it's not possible to test all possible combinations of data input and circumstances. We call it reconditioning. Testing all possible data combinations is called exhaustive testing. Hence, exhaustive testing is impossible. For this reason, risk and biotech are used to concentrate on the most important aspects to test their use. It is important to ensure that the most important parts are tested. Principle number three is early Testing many software systems reveals that many problems can be traced back to missing or incorrect requirements. In early testing, we are trying to find errors and effects before they are passed to the next stage of the development process. From the shown graph, when a bug in the requirement is discovered during the requirement phase, the cost of fixing this bug is very low. The longer we wait to fix this bug, the more costly it will be. Why? because now we might have built some of our designs based on this fault requirement. When a bug is introduced during the design phase, it is less expensive to fix it then than to wait until later stages, and so on. A bug in the requirement would create the wrong design, which in turn would create buggy code, and the final result would be buggy software. From the shown graph, we see that if a customer discovered the bug after driving the software, it would cost 1000 times more than what we would pay if we discovered and fixed the bug in the requirement phase. In addition, the time and effort required to fix a requirement bug during the system testing phase could be 500 times higher than if we would have discovered and fixed the bug in the requirement phase. What we are trying to achieve here is to break the error-defect failure cycle we mentioned earlier. We can do that by trying to find effects. Early testing activities shall be started as early as possible in the software or system development lifecycle. Testers should join the software lifecycle as soon as the documents are in draught mode. For example, are individual requirements testable? Can we find ambiguous or missing requirements? If we wait until the last minute to introduce the tester's time, pressure can increase dramatically. As a result, the longer the lapse time available, the more likely it is that testing will squeeze the area where the testing activity began. Testers do not have to wait until software is available to test. Principle number four: defect clustering If we have a software system with ten modules or components, imagine that our first cycle of testing exposed $100. You won't find that each module has exactly $10, but rather that a small number of modules exhibit the majority of the problems. This can happen for a variety of reasons, some of which are that the system is very complex in this module's volatile code, the effects of a change upon a change on this module, or the development staff. In my experience, this phenomenon is closely related to the Parvito principle, which is called the 80/20 rule. It says that approximately 80% of the problems are found in about 20% of the modules. So if you want to uncover a higher number of defects, it's useful to employ these principles and target areas of the applications under test where a high proportion of defects can be found. However, it must be remembered that testing should not concentrate exclusively on those parts. There may be fewer defects in the remaining code, but testers still need to search for them. Principle number five specifies a paradox If the same tests are repeated over and over again, eventually the same set of test cases will no longer find any new defects. To overcome these paradoxes and find new defects, test cases need to be regularly reviewed and revised, and new and different tests need to be written to exercise different parts of the software or system to find potentially more defects. Sixth principle testing is context dependent. Different testing is necessary in different circumstances. A game software that uses graphics heavily will be tested differently than a medical software that also uses graphics heavily. A simple static website will be tested differently than a dynamic e-commerce site where goods can be built using credit and debit cards. Software used in an aeroplane will be tested differently than a flight simulator. This can be a larger factor in determining the type of testing that is needed. The higher the possibility of loss, the more we need to invest in testing the software before it's implemented. Last principle. Principle number seven: absence of errors False software with no known errors is not necessarily ready to be shipped. Does the application under test fulfil the user's needs of it?The fact that node effects are outstanding is not a good reason to ship the software before dynamic testing has begun. There are no defects reported against the software. Does this mean that software that has not been tested at all can be shipped? I don't think so. Okay, now to the good part of this lecture: What kinds of questions can you get on the exam regarding this lecture? Well, for one, they can list four options. Three of them are principals, and the fourth is not a principle. And they ask you to pick the non-principled among us. Of course, they will make the principle a confusing one. Something like testing helps gain confidence in the software. Well, it's a true sentence, but it's not a principle. In addition, they can give you a situation and ask you, which brain bell did the situation describe? Or, say the situation is like this: for example, a customer gets the software, but he's upset because the software doesn't meet his needs. Which principal are we talking about? absence of illness, faulty A team wants to discover as many defects as possible. Which principle should we follow? defective, clustering, and so on. If testing reveals only the presence of defects and exhaustive testing is impossible, as well as the best sidebar documents, a good question may arise. Now, how much testing is enough? The answer is: it depends on the risk. The risk of missing on both true and false the risk of failure the risk of releasing untested or undertested software the risk of losing credibility and market share the risk of missing a market window the risk of overtesting ineffective tests every time We should evaluate the risk of the current situation of the software and decide whether the risk is high or low, if the risk is low and acceptable. Then we can stop testing and shape the software; otherwise we should continue testing Testing should provide sufficient information to stakeholders to make informed decisions about the release of the software being tested for the next development step or handover to customers, and then we use the stress information to determine what to test first. what to test most. how slowly to test each item. What not to test: allocate testing time by battery testing; we will discuss risk and testing further in a later section.
Testing software is not a random blame game with the software until we find a bug, but rather it supports us to ensure we achieve the most effective and efficient testing. Before test execution, there is some preparatory work to do. We are deciding what we are trying to achieve with the testing and setting clear objectives. Then we design the tests and set them up. During test execution, there is some work needed to record the results and check whether the tests are complete. A test designed to ensure that a programme follows a specification, for example, will be quite different from another. To find as many defects as possible, we define a test process to ensure that we don't miss critical steps and that we do things in the right order. Test activities exist before and after test execution. The fundamental test process consists of the following activities: planning and control, analysis and design, implementation and execution, evaluating execution criteria, and reporting test disclosure activities. Exam questions in this topic are merely either asking about the order of the activities in the test process or providing you with a testing task and asking during which testing activity this task takes place. So keep good notes about what tasks happen during which activity. Let's look at each one of those activities in detail.
first activity planning and control test. The activity of planning is the activity of defining the objectives of testing and defining the specification of test activities in order to meet the objectives and mission. This control is the ongoing activity of comparing actual progress against the plan and rebooting the status, including deviations from the plan and taking necessary action to stay on track or adjusting blends to meet the targets. Therefore, we need to undertake post-planning and control activities throughout the testing activities. We will talk more about test planning and control in the test management section, but for now we need to know what to test, who will do the testing, how they will do the testing, for how long, and define the test completion criteria, which is called the exit criteria, which we will talk about later. This is when we will stop testing to raise our report with stakeholders to decide if testing was enough or not.
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