Bending the Dynamic vs Static Language Tradeoff

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C++ Coding Standard
The test runner comes with a variety of hooks that allow you to interface into the test process in order to e. One could do this with regular static members: Many type systems have been created that are specialized for use in certain environments with certain types of data, or for out-of-band static program analysis. Anonymous July 8, at So I am wondering if my observation is correct: Please help to improve this article by introducing more precise citations. Any other time you try to use it, the compiler as already substituted your constant usage for literal usage; i.

Testing Basic Interview Questions

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Real-time software systems have strict timing constraints. To test if timing constraints are met, real-time testing is used. Usability testing is to check if the user interface is easy to use and understand. It is concerned mainly with the use of the application. Accessibility testing may include compliance with standards such as:.

Security testing is essential for software that processes confidential data to prevent system intrusion by hackers. The International Organization for Standardization ISO defines this as a "type of testing conducted to evaluate the degree to which a test item, and associated data and information, are protected so that unauthorised persons or systems cannot use, read or modify them, and authorized persons or systems are not denied access to them. Testing for internationalization and localization validates that the software can be used with different languages and geographic regions.

The process of pseudolocalization is used to test the ability of an application to be translated to another language, and make it easier to identify when the localization process may introduce new bugs into the product.

Globalization testing verifies that the software is adapted for a new culture such as different currencies or time zones. Actual translation to human languages must be tested, too.

Possible localization and globalization failures include:. Development Testing is a software development process that involves the synchronized application of a broad spectrum of defect prevention and detection strategies in order to reduce software development risks, time, and costs.

Development Testing aims to eliminate construction errors before code is promoted to other testing; this strategy is intended to increase the quality of the resulting software as well as the efficiency of the overall development process.

Depending on the organization's expectations for software development, Development Testing might include static code analysis , data flow analysis, metrics analysis, peer code reviews, unit testing, code coverage analysis, traceability, and other software testing practices.

Customers are routed to either a current version control of a feature, or to a modified version treatment and data is collected to determine which version is better at achieving the desired outcome. In concurrent testing, the focus is on the performance while continuously running with normal input and under normal operational conditions, as opposed to stress testing, or fuzz testing. Memory leak, as well as basic faults are easier to find with this method.

In software testing, conformance testing verifies that a product performs according to its specified standards. Compilers, for instance, are extensively tested to determine whether they meet the recognized standard for that language. A common practice in waterfall development is that testing is performed by an independent group of testers. However, even in the waterfall development model, unit testing is often done by the software development team even when further testing is done by a separate team.

In contrast, some emerging software disciplines such as extreme programming and the agile software development movement, adhere to a " test-driven software development " model. In this process, unit tests are written first, by the software engineers often with pair programming in the extreme programming methodology. The tests are expected to fail initially. Each failing test is followed by writing just enough code to make it pass.

This means the test suites are continuously updated as new failure conditions and corner cases are discovered, and they are integrated with any regression tests that are developed. Unit tests are maintained along with the rest of the software source code and generally integrated into the build process with inherently interactive tests being relegated to a partially manual build acceptance process.

The ultimate goals of this test process are to support continuous integration and to reduce defect rates. This methodology increases the testing effort done by development, before reaching any formal testing team. In some other development models, most of the test execution occurs after the requirements have been defined and the coding process has been completed.

Although variations exist between organizations, there is a typical cycle for testing. The same practices are commonly found in other development models, but might not be as clear or explicit. Many programming groups [ Like whom? There are many frameworks [ specify ] to write tests in, and continuous integration software will run tests automatically every time code is checked into a version control system. While automation cannot reproduce everything that a human can do and all the ways they think of doing it , it can be very useful for regression testing.

However, it does require a well-developed test suite of testing scripts in order to be truly useful. Program testing and fault detection can be aided significantly by testing tools and debuggers.

There are a number of frequently used software metrics , or measures, which are used to assist in determining the state of the software or the adequacy of the testing. Based on the amount of test cases required to construct a complete test suite in each context i. It has been proved that each class is strictly included in the next. For instance, testing when we assume that the behavior of the implementation under test can be denoted by a deterministic finite-state machine for some known finite sets of inputs and outputs and with some known number of states belongs to Class I and all subsequent classes.

However, if the number of states is not known, then it only belongs to all classes from Class II on. If the implementation under test must be a deterministic finite-state machine failing the specification for a single trace and its continuations , and its number of states is unknown, then it only belongs to classes from Class III on.

Testing temporal machines where transitions are triggered if inputs are produced within some real-bounded interval only belongs to classes from Class IV on, whereas testing many non-deterministic systems only belongs to Class V but not all, and some even belong to Class I. The inclusion into Class I does not require the simplicity of the assumed computation model, as some testing cases involving implementations written in any programming language, and testing implementations defined as machines depending on continuous magnitudes, have been proved to be in Class I.

Other elaborated cases, such as the testing framework by Matthew Hennessy under must semantics, and temporal machines with rational timeouts, belong to Class II.

A software testing process can produce several artifacts. The actual artifacts produced are a factor of the software development model used, stakeholder and organisational needs. Several certification programs exist to support the professional aspirations of software testers and quality assurance specialists. Note that a few practitioners argue that the testing field is not ready for certification, as mentioned in the Controversy section.

Some of the major software testing controversies include:. It is commonly believed that the earlier a defect is found, the cheaper it is to fix it. The following table shows the cost of fixing the defect depending on the stage it was found. With the advent of modern continuous deployment practices and cloud-based services, the cost of re-deployment and maintenance may lessen over time.

The "smaller projects" curve turns out to be from only two teams of first-year students, a sample size so small that extrapolating to "smaller projects in general" is totally indefensible. The GTE study does not explain its data, other than to say it came from two projects, one large and one small. The paper cited for the Bell Labs "Safeguard" project specifically disclaims having collected the fine-grained data that Boehm's data points suggest. The IBM study Fagan's paper contains claims that seem to contradict Boehm's graph and no numerical results that clearly correspond to his data points.

Boehm doesn't even cite a paper for the TRW data, except when writing for "Making Software" in , and there he cited the original article. There exists a large study conducted at TRW at the right time for Boehm to cite it, but that paper doesn't contain the sort of data that would support Boehm's claims.

Software testing is used in association with verification and validation: The terms verification and validation are commonly used interchangeably in the industry; it is also common to see these two terms defined with contradictory definitions.

The contradiction is caused by the use of the concepts of requirements and specified requirements but with different meanings. In the case of IEEE standards, the specified requirements, mentioned in the definition of validation, are the set of problems, needs and wants of the stakeholders that the software must solve and satisfy.

And, the products mentioned in the definition of verification, are the output artifacts of every phase of the software development process. These products are, in fact, specifications such as Architectural Design Specification, Detailed Design Specification, etc. The SRS is also a specification, but it cannot be verified at least not in the sense used here, more on this subject below.

But, for the ISO , the specified requirements are the set of specifications, as just mentioned above, that must be verified. A specification, as previously explained, is the product of a software development process phase that receives another specification as input. A specification is verified successfully when it correctly implements its input specification.

All the specifications can be verified except the SRS because it is the first one it can be validated, though. Both the SRS and the software must be validated.

The SRS can be validated statically by consulting with the stakeholders. Nevertheless, running some partial implementation of the software or a prototype of any kind dynamic testing and obtaining positive feedback from them, can further increase the certainty that the SRS is correctly formulated.

On the other hand, the software, as a final and running product not its artifacts and documents, including the source code must be validated dynamically with the stakeholders by executing the software and having them to try it.

Thinking this way is not advisable as it only causes more confusion. It is better to think of verification as a process involving a formal and technical input document. Software testing may be considered a part of a software quality assurance SQA process. They examine and change the software engineering process itself to reduce the number of faults that end up in the delivered software: What constitutes an acceptable defect rate depends on the nature of the software; A flight simulator video game would have much higher defect tolerance than software for an actual airplane.

Although there are close links with SQA, testing departments often exist independently, and there may be no SQA function in some companies. Software testing is an activity to investigate software under test in order to provide quality-related information to stakeholders. By contrast, QA quality assurance is the implementation of policies and procedures intended to prevent defects from reaching customers.

From Wikipedia, the free encyclopedia. Graphical user interface testing. Exception handling and Recovery testing. Capability Maturity Model Integration and Waterfall model. Verification and validation software and Software quality control.

Retrieved November 22, Retrieved November 21, Retrieved December 8, Testing Computer Software, 2nd Ed. New York, et al.: John Wiley and Sons, Inc. Best Practices in Software Management. International Software Testing Qualifications Board. Retrieved December 15, Principle 2, Section 1. Lessons Learned and Practical Implications. National Institute of Standards and Technology.

Retrieved December 19, CIO Review India ed. Retrieved December 20, Communications of the ACM. The Art of Software Testing. John Wiley and Sons. Foundations of Software Testing. Verification and Validation in Scientific Computing. Introduction to Software Testing. Becoming an Effective and Efficient Test Professional. Software Testing 2nd ed. Department of Computer Science, University of Sheffield. Retrieved January 2, Retrieved August 19, How to Become a Software Tester.

Retrieved January 5, Helsinki University of Technology. Retrieved January 13, Archived from the original on July 24, Software Testing and Continuous Quality Improvement 3rd ed. Security at the Source.

Retrieved December 10, Guide to the Software Engineering Body of Knowledge. Retrieved 13 July Software Development and Professional Practice. Creating a Software Engineering Culture. Testing Techniques in Software Engineering. Explicit use of et al. Objects, Patterns, and Tools. Software Testing Techniques Second ed. Retrieved January 9, Lessons Learned in Software Testing: Retrieved November 29, End of the Software Release Cycle. Retrieved January 11, Why Continuous Testing Is Essential".

Retrieved January 12, An Interview with Wayne Ariola". Retrieved January 16, Pacific Northwest Software Quality Conference. What's the real cost of quality? International Organization for Standardization.

Retrieved January 17, The World-Ready Approach to Testing. Testing Phase in Software Testing. Retrieved 17 March Classes, properties, complexity, and testing reductions" PDF.

IEEE standard for software test documentation. Retrieved 30 January American Society for Quality. Retrieved January 26, Archived from the original on August 31, Archived from the original on October 29, Archived from the original on October 2, Retrieved January 18, Code Complete 2nd ed. The Leprechauns of Software Engineering: How folklore turns into fact and what to do about it.

Retrieved August 13, Major fields of computer science. Computer architecture Embedded system Real-time computing Dependability. Network architecture Network protocol Network components Network scheduler Network performance evaluation Network service.

Interpreter Middleware Virtual machine Operating system Software quality. Programming paradigm Programming language Compiler Domain-specific language Modeling language Software framework Integrated development environment Software configuration management Software library Software repository.

Software development process Requirements analysis Software design Software construction Software deployment Software maintenance Programming team Open-source model. Model of computation Formal language Automata theory Computational complexity theory Logic Semantics. Algorithm design Analysis of algorithms Randomized algorithm Computational geometry. Discrete mathematics Probability Statistics Mathematical software Information theory Mathematical analysis Numerical analysis.

Database management system Information storage systems Enterprise information system Social information systems Geographic information system Decision support system Process control system Multimedia information system Data mining Digital library Computing platform Digital marketing World Wide Web Information retrieval. Cryptography Formal methods Security services Intrusion detection system Hardware security Network security Information security Application security.

Any calls we make using the facade will be passed to the underlying instance of Laravel's cache service. Instead, the Cache facade extends the base Facade class and defines the method getFacadeAccessor.

This method's job is to return the name of a service container binding. When a user references any static method on the Cache facade, Laravel resolves the cache binding from the service container and runs the requested method in this case, get against that object.

Using real-time facades, you may treat any class in your application as if it were a facade. To illustrate how this can be used, let's examine an alternative. For example, let's assume our Podcast model has a publish method. However, in order to publish the podcast, we need to inject a Publisher instance:. Injecting a publisher implementation into the method allows us to easily test the method in isolation since we can mock the injected publisher.

However, it requires us to always pass a publisher instance each time we call the publish method. Using real-time facades, we can maintain the same testability while not being required to explicitly pass a Publisher instance.

To generate a real-time facade, prefix the namespace of the imported class with Facades:. When the real-time facade is used, the publisher implementation will be resolved out of the service container using the portion of the interface or class name that appears after the Facades prefix. When testing, we can use Laravel's built-in facade testing helpers to mock this method call:. Below you will find every facade and its underlying class.

This is a useful tool for quickly digging into the API documentation for a given facade root. The service container binding key is also included where applicable. Laravel Nova is now available! Get your copy today! Dependency Injection Facades Vs. So, we can easily access a facade like so: When To Use Facades Facades have many benefits. Dependency Injection One of the primary benefits of dependency injection is the ability to swap implementations of the injected class.

For example, given the following route: Helper Functions In addition to facades, Laravel includes a variety of "helper" functions which can perform common tasks like generating views, firing events, dispatching jobs, or sending HTTP responses. For example, this facade call and helper call are equivalent: So, even though we are using the helper function, we can write the following test to verify that the method was called with the argument we expected: By glancing at this code, one might assume that the static method get is being called on the Cache class: Real-Time Facades Using real-time facades, you may treat any class in your application as if it were a facade.

However, in order to publish the podcast, we need to inject a Publisher instance: To generate a real-time facade, prefix the namespace of the imported class with Facades: When testing, we can use Laravel's built-in facade testing helpers to mock this method call:

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