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Get New Content Update. Popular Posts. Test harnesses in automation testing will use test scripts commonly written in JAVA , Python and Ruby to automate the software testing process. A test strategy is an outline that describes the testing approach of the software development cycle. The purpose of a test strategy is to provide a rational deduction from organizational, high-level objectives to actual test activities to meet those objectives from a quality assurance perspective.
Tests are frequently grouped by where they are added in the software development process, or by the level of specificity of the test. Definition: Requirements Traceability Matrix RTM is a document used to ensure that the requirements defined for a system are linked at every point during the verification process. It also ensures that they are duly tested with respect to test parameters and protocols. Test cases are challenging to design without having clear functional specifications.
It is difficult to identify tricky inputs if the test cases are not developed based on specifications. It is difficult to identify all possible inputs in limited testing time. The black box testing is also known as an opaque, closed box, function-centric testing.
It emphasizes on the behavior of the software. Black box testing checks scenarios where the system can break. In a comprehensive software development environment, bottom-up testing is usually done first, followed by top-down testing.
Error Guessing is a Software Testing technique on guessing the error which can prevail in the code. This technique necessarily requires skilled and experienced testers. From functional testing, to penetration testing, error detection, fuzz testing, and beyond, there are many ways to validate API performance and security.
Skip to content What is test harness in manual testing? Is Selenium a test harness? What is test harness means? What is test strategy? What is test comparator tool? What is black box and white box testing? If it is an Exception, that exception is raised. This case study consisted on the development and testing of a subsystem that was part of a financial system. The subsystem was being developed by a Brazilian company specialized in banking automation.
The subsystem that we used has the responsibility for: i handling requests, deliveries and cancellations of checkbooks; ii handling account contracts and iii including additional credit limits.
Two MSc students for the development and testing process, respectively and two company employees composed the team. An IFTC is a component in which the normal and abnormal activities are implemented as separate components which communicate with each other during error situations; connectors can be used to link both parts.
The goal of an IFTC is to provide a means to structure fault-tolerant systems, so that the exception handling mechanisms used to achieve fault-tolerance do not cause a great impact on system complexity. Eight IFTCs were developed; four of them to implement system use cases, called system components [13]; and another four to implement data storage services, designated business components.
For testing purposes, only system components were chosen as they implement system functionalities. These components are listed in Table 2. If different system or business components can raise similar exceptions, their handlers can be grouped in a single abnormal component. An example is the agencyHandler component, which groups all the exceptions related to the agency data type, raised either by business or system components.
Using this approach, system components were constructed by combining normal components a total of four and exception handlers a total of nine ; these components are listed in Table 3. Table 2 summarizes our main test results. The number of nodes and edges shows the complexity of each component's ICFG.
The number of generated test cases is also presented, together with the number of failures that occurred during test execution.
The number of failures detected by each oracle mechanism, described in Section 4. Both mechanisms detected the same failures, except in one case, where the expected result in the test cases detected one more failure. The reason is that the built-in assertions are not good in detecting whether a specific output is produced for a given input, which justifies the verification step in a test case c.
We also measured the code coverage achieved by the test cases. The results are presented on Table 3. Notice that, although our approach does not consider the source code for test case generation, the code coverage achieved was high. For normal components, the code that was not covered corresponds to metadata operations used to define component interfaces, for example.
For the testing of exceptional components, the code not covered comprised handlers for exceptions only raised by business components.
This way, they were considered as being part only of business IFTCs and, consequently, out of test scope. AgencyHandler , for example, groups three exceptions: i agencyIsClosed and ii agencyNotRegistered , which may be thrown by all system components except suspendCheckOperations ; and iii invalidAgency , which is only thrown by the business component AgencyManager.
As AgencyManager is out of testing scope, the handler for the invalidAgency exception was not covered during the tests. In this section, we present related work on test case generation from behavior models, and on stub generation. Of course, we are far from being exhaustive. Our intent is to present the work that in some sense served as a basis for the approach presented here.
Edwards [14] proposes a method using both built-in BIT mechanisms and test case generation. BIT mechanisms are embedded code used for testability improvement. Test cases are derived from flow graphs, which model component behavior.
This work is very similar to ours, although they do not consider test of isolated components, only integrated ones. In this case, BIT mechanisms are included in all the involved components to facilitate fault locations. However, they do not present guidelines for stubs generation.
Also, the graph is not obtained from UML models in our method. Many different models created by development teams are used for test case generation: use cases, interaction diagrams sequence or collaboration and class diagrams. Test cases are generated from activity and interaction diagrams, characterizing a gray box testing method, as the class structure of the system must be known.
This is the main limitation of TOTEM for component testing, as it cannot always be assumed that a component's internal structure is available. Our approach, instead, is completely black box, and needs no information about a component's internal details. Bundell et al. This tool offers an editor where a tester can code test cases using a format based on XML. Functionalities like oracle generation and test coverage are also provided. However, test case generation facilities are not offered, nor component specification is available to the client.
In our case, component specification is packed together with the component, according to the testable component architecture [30].
Besides contributing for client understanding, the specifications are also used for test case generation. Another difference between our approach and the ones previously mentioned is that ours explicitly considers the testing of exception handling mechanisms.
Kaiser et. Infuse supports testing of systems implemented in procedural languages such as C. Headers in C parlance for the stubs are automatically generated but their contents must be created by hand or by some external mechanism.
The main differences from our approach are that our test cases and stubs are automatically generated from a behavior model, and not from the code, and our test cases and stubs are language independent. Although we present an object-oriented design for test harness, tests are generated in XML and can be converted to any language. Drivers are produced automatically from SDs representing the behavior of the program under test.
Test stubs for selected classes are generated independently of test cases; the stubs communicate with the driver at runtime to know what they are supposed to do. The advantage is that the stubs are regenerated only when the interface of the stubbed class changes. The stub behaves as specified in the SD. In our case, the stubs are test case specific, hence we do not need a behavior model for the component being stubbed. Lloyd and Malloy [23] present a study for testing objects in the presence of stubs.
Their work describes how to construct minimal implementations for stubs, in order to reduce the generation effort. Test cases for a class are obtained from a Method Sequence Graph, which allows the generation of the sequence of method invocations to test a class. However, they do not describe how to produce stubs automatically. Besides, since the stubs cannot throw exceptions, this poses a problem to test exceptionhandling mechanisms.
Bertolino et al. Their method provides tools for the automatic generation of a test bed, based on QoS specifications of both the service under test and the interacting services. Stubs are generated in order to replace required services; their generation is based on service description in WSDL, a standard in WS communities, and in service agreements specification.
The former is used to generate the stub skeleton, whereas the latter is used to obtain the parameterizable code that simulates the QoS constraints. They also transform XML definitions into Java code. Stubs generation is mostly automatic, however data values are generated randomly.
The main difference is that Puppet considers only non functional scenarios as latency, delay, reliability , and our method exercises functional implementation. Also, the tool is based on WSDL, which constrains the tools to the WS domain, whereas in our case, we are based on a higher level description, which allows our approach to be applied in other domains. There are also various tools that support test case implementation and execution.
JUnit [26] is an example. However, it is not concerned with test case generation. There are also tools to support the creation of mock objects, which may be useful for stub implementation, but generally they have some limitations, as discussed in Section 2.
They are generally implementation language dependent, which can be a problem for components that can be written in different programming languages, and whose source code may not be available. In this paper we presented a method to generate a test harness from UML models.
The approach can be useful in situations where stubs are unavoidable, like test driven programming and testing of exception handling mechanisms. The method considers UML activity diagrams, which models component behavior.
The component is considered black box, since only its provided and required interfaces are considered. In this way, test cases generated from this model contain information to exercise the component through its provided interfaces, as well as to prepare the stubs replacing the external components required for test case execution.
As both normal and exceptional behaviors were considered, test cases could exercise exception-handling code. For exception handling mechanisms, high code coverage was achieved mainly because of stubs, allowing the simulation of required components failures.
The code not covered, both in normal and abnormal scenarios, were relative to parts not related to the functional behavior e. For a large set of components, it is not possible to create test artifacts for all. We recommended prioritizing the components according to criticality, possibility of reuse, and requirement stability. Components with less priority will be tested during integration and system testing phases.
Large components can be treated similarly: only the most critical parts are modeled and tested individually. This should include exception handlers, which usually handles critical functions that are not easily simulated without stubs. The main advantage of our method is test case generation in a language independent way including exceptional behavior coverage.
The method also presents the possibility of stubs creation. The stubs are synchronized with the test cases from UML models, allowing both test cases and stubs to be built early in the development process.
In the future, we intend to address some of the method's limitations, especially those related to automation. For example, concurrency is an aspect that can be represented in UML Activity diagrams but is not yet addressed, due to the difficulty to generate test paths to cover these situations. Another important aspect is the generation of test data. It is our intent to provide automated support to the whole process, that is, from building a testable component through test case generation and execution as well as results analysis.
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