Test development software

Means it is an IT professional who can work effectively in development and testing roles. SDETs are able to understand software development as well as software testing. They want more work with less people. As they are the only professional who take part in development as well as at the same time they can handle testing of the developed software.

There is a trend in companies to hire multi skill IT professionals. So SDET software professionals are highly on demand.

Skip to content. Change Language. Related Articles. In TDD more focus is on production code that verifies whether testing will work properly. In traditional testing, more focus is on test case design. Every single line of code is tested, unlike traditional testing. The combination of both traditional testing and TDD leads to the importance of testing the system rather than perfection of the system.

You should know why you are testing something and what level its need to be tested. Developers test their code but in the database world, this often consists of manual tests or one-off scripts. Using TDD you build up, over time, a suite of automated tests that you and any other developer can rerun at will.

Better Designed, cleaner and more extensible code. It helps to understand how the code will be used and how it interacts with other modules. It results in better design decision and more maintainable code. TDD allows writing smaller code having single responsibility rather than monolithic procedures with multiple responsibilities.

This makes the code simpler to understand. TDD also forces to write only production code to pass tests based on user requirements. Confidence to Refactor If you refactor code, there can be possibilities of breaks in the code. So having a set of automated tests you can fix those breaks before release.

Proper warning will be given if breaks found when automated tests are used. Using TDD, should results in faster, more extensible code with fewer bugs that can be updated with minimal risks. Good for teamwork In the absence of any team member, other team members can easily pick up and work on the code. It also aids knowledge sharing, thereby making the team more effective overall.

Good for Developers Though developers have to spend more time in writing TDD test cases, it takes a lot less time for debugging and developing new features. You will write cleaner, less complicated code.

Report a Bug. Previous Prev. Testing can serve as metrics. Testers can make claims based on interpretations of the testing results, which either the product works under certain situations, or it does not work. We can also compare the quality among different products under the same specification, based on results from the same test.

We can not test quality directly, but we can test related factors to make quality visible. Quality has three sets of factors -- functionality, engineering, and adaptability.

These three sets of factors can be thought of as dimensions in the software quality space. Each dimension may be broken down into its component factors and considerations at successively lower levels of detail.

Table 1 illustrates some of the most frequently cited quality considerations. Good testing provides measures for all relevant factors.

The importance of any particular factor varies from application to application. Any system where human lives are at stake must place extreme emphasis on reliability and integrity. In the typical business system usability and maintainability are the key factors, while for a one-time scientific program neither may be significant.

Our testing, to be fully effective, must be geared to measuring each relevant factor and thus forcing quality to become tangible and visible. Tests with the purpose of validating the product works are named clean tests, or positive tests. The drawbacks are that it can only validate that the software works for the specified test cases. A finite number of tests can not validate that the software works for all situations.

On the contrary, only one failed test is sufficient enough to show that the software does not work. Dirty tests, or negative tests, refers to the tests aiming at breaking the software, or showing that it does not work. A piece of software must have sufficient exception handling capabilities to survive a significant level of dirty tests. A testable design is a design that can be easily validated, falsified and maintained.

Because testing is a rigorous effort and requires significant time and cost, design for testability is also an important design rule for software development.

Software reliability has important relations with many aspects of software, including the structure, and the amount of testing it has been subjected to. Based on an operational profile an estimate of the relative frequency of use of various inputs to the program [Lyu95] , testing can serve as a statistical sampling method to gain failure data for reliability estimation. Software testing is not mature. It still remains an art, because we still cannot make it a science.

We are still using the same testing techniques invented years ago, some of which are crafted methods or heuristics rather than good engineering methods. Software testing can be costly, but not testing software is even more expensive, especially in places that human lives are at stake.

Solving the software-testing problem is no easier than solving the Turing halting problem. We can never be sure that a piece of software is correct. We can never be sure that the specifications are correct.

No verification system can verify every correct program. We can never be certain that a verification system is correct either. There is a plethora of testing methods and testing techniques, serving multiple purposes in different life cycle phases. Classified by purpose, software testing can be divided into: correctness testing, performance testing, reliability testing and security testing.

Classified by life-cycle phase, software testing can be classified into the following categories: requirements phase testing, design phase testing, program phase testing, evaluating test results, installation phase testing, acceptance testing and maintenance testing. By scope, software testing can be categorized as follows: unit testing, component testing, integration testing, and system testing.

Correctness is the minimum requirement of software, the essential purpose of testing. Correctness testing will need some type of oracle, to tell the right behavior from the wrong one.

The tester may or may not know the inside details of the software module under test, e. Therefore, either a white-box point of view or black-box point of view can be taken in testing software. We must note that the black-box and white-box ideas are not limited in correctness testing only.

The black-box approach is a testing method in which test data are derived from the specified functional requirements without regard to the final program structure.

Because only the functionality of the software module is of concern, black-box testing also mainly refers to functional testing -- a testing method emphasized on executing the functions and examination of their input and output data.

In testing, various inputs are exercised and the outputs are compared against specification to validate the correctness. All test cases are derived from the specification. No implementation details of the code are considered. It is obvious that the more we have covered in the input space, the more problems we will find and therefore we will be more confident about the quality of the software.

Ideally we would be tempted to exhaustively test the input space. But as stated above, exhaustively testing the combinations of valid inputs will be impossible for most of the programs, let alone considering invalid inputs, timing, sequence, and resource variables. Combinatorial explosion is the major roadblock in functional testing. To make things worse, we can never be sure whether the specification is either correct or complete.

Due to limitations of the language used in the specifications usually natural language , ambiguity is often inevitable. Even if we use some type of formal or restricted language, we may still fail to write down all the possible cases in the specification. Sometimes, the specification itself becomes an intractable problem: it is not possible to specify precisely every situation that can be encountered using limited words.

And people can seldom specify clearly what they want -- they usually can tell whether a prototype is, or is not, what they want after they have been finished. Specification problems contributes approximately 30 percent of all bugs in software. The research in black-box testing mainly focuses on how to maximize the effectiveness of testing with minimum cost, usually the number of test cases.

It is not possible to exhaust the input space, but it is possible to exhaustively test a subset of the input space. Partitioning is one of the common techniques.

If we have partitioned the input space and assume all the input values in a partition is equivalent, then we only need to test one representative value in each partition to sufficiently cover the whole input space.

Domain testing [Beizer95] partitions the input domain into regions, and consider the input values in each domain an equivalent class. Domains can be exhaustively tested and covered by selecting a representative value s in each domain. Boundary values are of special interest. Experience shows that test cases that explore boundary conditions have a higher payoff than test cases that do not.

Boundary value analysis [Myers79] requires one or more boundary values selected as representative test cases. The difficulties with domain testing are that incorrect domain definitions in the specification can not be efficiently discovered.

Good partitioning requires knowledge of the software structure. A good testing plan will not only contain black-box testing, but also white-box approaches, and combinations of the two. Contrary to black-box testing, software is viewed as a white-box, or glass-box in white-box testing, as the structure and flow of the software under test are visible to the tester. Testing plans are made according to the details of the software implementation, such as programming language, logic, and styles.

Test cases are derived from the program structure. White-box testing is also called glass-box testing, logic-driven testing [Myers79] or design-based testing [Hetzel88]. There are many techniques available in white-box testing, because the problem of intractability is eased by specific knowledge and attention on the structure of the software under test.

The intention of exhausting some aspect of the software is still strong in white-box testing, and some degree of exhaustion can be achieved, such as executing each line of code at least once statement coverage , traverse every branch statements branch coverage , or cover all the possible combinations of true and false condition predicates Multiple condition coverage.

Control-flow testing, loop testing, and data-flow testing, all maps the corresponding flow structure of the software into a directed graph. Test cases are carefully selected based on the criterion that all the nodes or paths are covered or traversed at least once. By doing so we may discover unnecessary "dead" code -- code that is of no use, or never get executed at all, which can not be discovered by functional testing.

In mutation testing, the original program code is perturbed and many mutated programs are created, each contains one fault. Each faulty version of the program is called a mutant. Test data are selected based on the effectiveness of failing the mutants. The more mutants a test case can kill, the better the test case is considered. The problem with mutation testing is that it is too computationally expensive to use.

The boundary between black-box approach and white-box approach is not clear-cut. Many testing strategies mentioned above, may not be safely classified into black-box testing or white-box testing.