Automated Acceptance Testing
Tools for Java test automation by Daniel Wildt
2. Mantis Bug Tracker
So, That’s it. These are most popular bug tracking tools used in software industry these days. Hope my efforts will help while choosing the bug/issue tracking tool. But, now it’s your turn. If you think any other tool should be listed here instead of this than please share with us in the comment section below.
Static Code Analysis is a technique which quickly and automatically scan the code line by line to find security flaws and issues that might be missed in the development process before the software or application is released. It functions by reviewing the code without actually executing the code.
0 – Manual compilation, no unit tests, manual testing by QA
Before we all recoil in horror it’s worth recalling the pure horror of how things used to be with an enormous gulf between developers and QA. Thankfully this approach is lost in the mist of time for almost everyone but if has not, you have my deepest sympathies.
1 – Automated compilation, some unit tests by dev, manual testing by QA
We start to see the process become more agile. Build scripts have made their appearance. Life is a bit easier for developers with the introduction of Continuous Integration but not much different to QA who are left out in the cold.
2 – Automated compilation, high standard unit tests by dev, automation of manual testing by QA
Build frameworks that allow failing a build process that successfully compiled but did not pass the unit tests are now used. QA are using tools which theoretically allow them to sign off individual user stories while still being able to quickly regression test the entire application to ensure that no new errors have been introduced. However, the separation of dev and QA ensures that almost every change by developers results in failing QA tests. The only way to get all the tests to pass is to either stop development or to fork the codebase so that the QA’s can work on stable code. Bugs are fed back into the development code branch and promoted to the QA branch. Congratulations for reinventing waterfall and for ensuring that the ratio between developers and QA remains 1:1.
3 – Automated compilation, high standard unit tests by dev, integration tests by dev, automated testing by QA using better tools
Some of the QA workload is taken over by developers who automate obvious integration points with the rest of the system. Some more load is taken off the QA who can re-use tests with tools like Fitnesse but the phrase “dev complete” is still heard. Developers may provide QA with test utilities and abstractions like Stubs and Fakes to make testing easier and more deterministic. It’s almost inevitable that every team’s story board will have 3 or 4 times as many stories waiting for QA than are either “In Development” or “Undergoing QA”. You can do Continuous Delivery at this stage but everyone wonders why it’s so painful and costs so much in time and effort.
For us to ship reliable quality code, we have to change not just the tooling but how the delivery organisation is structured. When manual testing was the norm, a separate QA organisation existed because it was more efficient and more effective to have non-developers test the code. With the levels of automation now available a separate QA organisation is an anachronism which should no longer exist. So what do we really need?
4 – Automated compilation, high standard unit tests by dev, integration tests by dev, agile testing by dev, sign-off by QA
The role of the QA has mutated to that of QABA (aka ‘a bloody good BA’) – domain experts that represent the business in the delivery team but who are also responsible for creating the acceptance criteria for user stories where the acceptance criteria are expressed as scenarios that can be easily converted into actual test code. Developers write the application code and the code that tests it, including creating any tooling. The QABA can then sign off the story on completion without having to go back to the business. Business still see new features and capabilities at weekly demos and show’n’tells but are rarely involved with the delivery team on a regular basis. If you are B2C, even better is where new code is released into production without being signed off but hidden behind feature throttles that stop the new functionality from being seen outside of the company network. That way the entire company gets to do UAT on new functionality before it hits the customers.
A fundamental pillar of continuous delivery is that all* your tests must be automated. To achieve this the QA organisation should be in the business of writing the test scenarios that the code needs to be evaluated against and for signing off that the code does this. Test code should be a first class citizen of the application and should be written by people who’s primary job is writing code – the developers. I will say it again – QA should not be in the business of writing test code.
Developers are responsible for quality and should act like it. Sometimes that means taking responsibility from the QA organisation that should never should have been given to them. Quality is too important to leave to QA. Developers need to take full responsibility for the quality of their code and they should be in the firing line if something is broken. The role of the QA is to keep the developers on the straight and narrow and the most effective way of doing this is to get them to apply their confrontational mindset to the code via the acceptance criteria used to sign off the new functionality. Those of you familiar with BDD are probably nodding your heads right now but I’m not sure that BDD is the answer. It’s the right approach from the perspective of test case creation but the tooling is currently a zero sum game – the effort you save by having natural language test descriptions run is equivalent to the amount of effort you have to expend in extending your tooling to support your test cases in all bar the most trivial cases.
If you take a look at a company that prioritizes the ability to ship code, e.g. Facebook, you will see the developer taking far more responsibility for QA than is seen in the rest of the industry. It’s time for the rest of us to catch up.
What is Code Coverage
Code Coverage is an important measurement in Software Quality Engineering. While Software testing ensures correctness of the applications, a metric is required to track the What is Code Coverage Code Coverage is an important measurement in Software Quality Engineering. While Software testing ensures correctness of the applications, a metric is required to track the completeness and effectiveness of the testing undertaken. Code Coverage helps achieve reliable quality through identifying untested areas of the application.
Why Code Coverage
Software testing is a challenging function. The testers need to ensure complete functional and non-functional correctness of the product. Considering the complex workflows and use cases of modern day applications, the number of unique cases that the software can be used often run into millions, which is not feasible to be covered under testing exercise. The testers thus need to
– While Planning Tests
o Ensure covering all workflows in terms of decision trees in the code
o Ensure covering all data values – by identifying patterns rather covering millions of values
– While testing
o Ensuring the testing is completely exercising the whole application with planned and exploratory tests.
At the end of testing, the decision to stop testing and release the product still remains subjective, based on the presence or absence of bugs, inflow of new bugs, success rate of each test cycle, confidence rating of the testers or users, etc. Whereas the definitive metric of quantifying how much of the application was really tested, is missed.
Code Coverage is measured as quantification of application code exercised by the testing activities. Code Coverage can be measured at various levels – in terms of programming language constructs – Packages, Classes, Methods, Branches or in terms of physical artifacts – Folders, Files and Lines. For Eg. A Line Coverage metric of 67% means the testing exercised 67% of all executable statements of the application. A Code Coverage metric usually is accompanied by Code Coverage Analysis Report – which helps identify the un-tested part of the application code, thereby giving the testers early inputs for complete testing.
Benefits of Code Coverage
Test Your Test
Typical Emotional Storyboard
Good: Write more tests
Only way to truly increase code coverage
Excluding Code to boost Coverage
Types of Coverage
How; – Coverage Tools
Hybrid testing definition. testing. A combination of top-down testing with bottom-up testing of prioritized or available components
According to Wiki:
Hybrid testing is what most frameworks evolve into over time and multiple projects. The most successful automation frameworks generally accommodate both grammar and spelling as well as information input. This allows information given to be cross checked against existing and confirmed information. This helps to prevent false or misleading information being posted. It still however allows others to post new and relevant information to existing posts and so increases the usefulness and relevance of the site. This said, no system is perfect and it may not perform to this standard on all subjects all of the time but will improve with increasing input and increasing use.
According to Tutorialspoint:
We know that Integration Testing is a phase in software testing in which standalone modules are combined and tested as a single entity. During that phase, the interface and the communication between each one of those modules are tested. There are two popular approaches for Integration testing which is Top down Integration Testing and Bottom up Integration Testing.
In Hybrid Integration Testing, we exploit the advantages of Top-down and Bottom-up approaches. As the name suggests, we make use of both the Integration techniques.
Reference/Content Source: –
in preparation for the release of Apache Maven 3.0, the Maven team is seeking your help to discover regressions since Maven 2.x. Everybody interested in taking a preview of the upcoming release for a test drive can get source and binary bundles from there portal.
Before reporting any issues found during testing, please be sure to have a close look at the compatibility notes for Maven 3.x:
If you encounter unexpected build issues, please fill a report in JIRA that provides sufficient information to reproduce and analyze the issue:
The fixes contained in this release candidate since the 3.0-beta-3 release can also be seen in JIRA:
-The Maven team