TestLink - An open source test Management tool
TestLink is most widely used web based open source test management tool. It covers both requirements specification and test specification together.
It supports both automated and manual execution of Test cases.Automation execution of test cases can be achieved using XML-RPC technique.
It supports multiple user login and parallely multiple projects can run in TestLink.
Role can be created based on project and organisation requirement.Features/menu's of TestLink can be mapped to newly created role irrespective of the role.
It can be integrated with bug tracking tools like Bugzilla and Redmine.
It also supports SMTP integration.
TestLink have bunch of reports to serve project and organizational needs.
Any role of TestLink can generate report to evaluate their performance.
There is no pre-requisite for this course but prior knowledge of SDLC and STLC will be helpful
What will you learn
Multiple project creation
Test Suite creation
Requirement Spec and Test case mapping(RTM)
Build report generation
Test management process
Execution of test cases in TestLink
Creation of Testcase in TestLink
Test Plan Creation
Many institutes are having a Software Testing Training And Placement In Delhi but few of them are very great at teaching. In the event that you want to learn about software testing. We have designed this software testing training course to learn...
Many institutes are having a Software Testing Training And Placement In Delhi but few of them are very great at teaching. In the event that you want to learn about software testing. We have designed this software testing training course to learn software testing fundamentals and gently to introduce you to advanced software testing techniques. This course is designed and taught by the working testing professionals having experience. In APTRON Solutions we provide the most practical and software testing job oriented training in Delhi. There are many reasons why software testing has gained such a great amount of importance in the IT field. Firstly, software testing helps in reducing the overall cost and time of the software development project. On the off chance that testing is ignored in the initial development phases to save money, then it might turn out to be a very expensive matter later. Because when proceeding onward with the development process it becomes more difficult to trace back defects and rectifying one defect somewhere can introduce another defect in some other module.
Software testing is a sensible activity which identifies defects in the software bugs or loopholes and helps in correcting and preventing those bug and loopholes before the software get released to the end-user. In this universe of increasing addictiveness on Software, Improper performing of software can lead to serious situations, for example, injuries or might be death (airplane software failure might lead to fatalities), loss of time, loss of money and etc. Software testing field has become one of the fastest-developing industries of corporate IT expenditure. In Delhi are there were lots of opportunities for software testing. As indicated by Pierre Audoin Consultants Testing has become one of the fastest-developing segment of corporate IT sector and worldwide it is spending on testing will reach approximately €85bn in 2011, and will nearly hit the €300bn mark by 2017 meaning that is enormous growth in opportunities for Software Testers.
Software testing Institute in Delhi with 100% Job Guarantee
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Artificial Intelligence (AI) and Machine Learning( ML) is a very common and important aspect of today’s life. [AI development services](https://artificialintelligence.oodles.io "AI development services") have opened up new business opportunities...
Artificial Intelligence (AI) and Machine Learning( ML) is a very common and important aspect of today’s life. AI development services have opened up new business opportunities for the advancement in every possible human activity, be it medicine or gaming.
In such an atmosphere, it is important to discuss the importance and methods of AI and Machine Learning Testing.
How AI can optimize Testing?
1: Accelerating Timelines
As a manual tester, we have to go through thousands of lines of codes to test any functionality. Artificial Intelligence is a much better approach in this case. AI can scan codes, sort through log files and detect errors in a very short span of time. Additionally, AI is very helpful as it does not get exhausted or make human errors, so it yields more accurate results. By implementing AI into repetitive tests, Testers can focus on testing new features or pay particular emphasis to important parts of the software.
2: Better Automation
A very important part of a QA’s job is to ensure that the new code does not affect the functioning of the existing code. Since more features are developed, the amount of code to be tested expands which can give burden to the Testers.
Artificial Intelligence bots are able to evolve with change in the code. New functions can be adapted and easily identifiable by AI bots. When any modification in code has been identified by AI bots, they can be programmed in a way that it can decide if it is a new feature or there is any defect emerging from changes to the code.
3: More clarity on client requirements
The most important part of Software Testing to understand client expectations. By using Artificial Intelligence, it is possible to examine similar websites and apps to determine what contributes to success among the target audience. AI can help study a large number of competing products to identify key selling points so that both developers and tester know what users want out of a particular kind of software.
Testers can use AI to detect common flaws and errors in code that might affect the flawless functioning of software. So, by having a proper understanding of what the client wants, QAs can create test cases to ensure that the product does not break when it comes to achieving those particular goals.
It is important to remember that incorporating AI into testing processes is still a process in motion. But it is also important to keep an eye on innovations and advancements in this regard.
AI will help tester’s lives easier in aspects of greater accuracy and speed. By detecting bugs quickly, AI can provide testers with the time and mental energy to create better testing methods, write better test scripts and provide ways to the best possible user experience.
Some Artificial Intelligence/Machine Learning Test tools are as follows:
Applitools are basically used for Visual Testing.
The algorithms used in Applitools are entirely adaptive in the aspect of AI and Machine Learning.
Possible AI Type Features using Applitools:
1- Leveraging ML/AI-based for automated maintenance (being able to group together similar groups of changes from different pages/browsers/devices)
2- Modification of comparison algorithms to identify what changes are meaningful/noticeable.
3- Being able to automatically identify which changes are more likely to be bugs vs. desired changes and prioritize functionality.
Testim tries to maximize the advantage of machine learning to speed up the authoring, execution and most importantly the maintenance of automated tests.By this Testers can make sure that their test execution is accurate.
Testim focuses on reducing test maintenance, which is the most common challenge for most of the Organizations.
The main goal of Testim is to help liberate test automation from the exclusive realm of developers and make it simple enough for anyone on the team to create.
Mabl is similar to Test.AI.Mabl terminology provides an interaction between the tests and the application.The interacted tests will run at a predetermined amount of time and alert the Testers.
Three main features of Mabl are:
1- Mabl can automatically detect the changed or modified elements of the application and dynamically updates the tests to handle those changes.
2- Mabl can continuously compare test results to test history to quickly detect changes and regressions, resulting in more stable releases.
3- Mabl is helful in identifying and locating problems quickly, which is helpful in alerting the Testers to possible impacts before they affect the customers.
ReTest tries to bake AI intelligence into their tool, without having any specific programming skills.
Using ReTest tool, Testers do not need to select element IDs to work with when creating a script also. ReTest also automatically takes care of wait times.
ReportPortal provides a machine-learning algorithm which helps Testers to analyze test results automatically.
This machine learning algorithms use all the historical data that is already in the dashboard database for any project. Through which it can analyze the latest execution of test cases which gives them the confidence to the testers about the status of their test cases and execution.
The ability to analyze large amounts of data is the perfect use of machine learning.
Test.AI is an AI tool that provides cognitive abilities to Selenium and Appium. It requires no programming or coding skills and Tests are defined in a simple format that can be easily understandable.
AI can identify screens and elements dynamically in any app which can automatically drives the application to execute test cases.
Sealights is a Cloud-based platform.
With their machine learning-like technology that analyzes both the code and the tests that run against it, it lets you know exactly what your tests are covering and what they’re not. But when Sealights say “tests,” they not only mean the unit tests, the “Tests” mean here is any kind of test, from functional, manual, performance, you name it.
Sealights enable “Quality Testing” which helps in checking the exact files/methods/lines that are updated or fixed by the last build and not tested as it provides high stability. It ensures that untested code will not reach production before undergoing minimal validation.
Data Warehouse ETL Testing & Data Quality Management A-Z
Learn the essentials of ETL Data Warehouse Testing and Data Quality Management through this step-by-step tutorial. This course takes you through the basics of ETL testing, frequently used Data Quality queries, reporting and monitoring. In this tutorial we will learn how to build database views for Data Quality monitoring and build Data Quality visualizations and reports!
..Learn to build data quality dashboards from scratch!
..Learn some of the most common mistakes made when performing ETL/ELT tests..
..Forget about manual ad-hoc ETL testing, learn more about automated ETL and data quality reports
The course contains training materials, where you can practice, apply your knowledge and build an app from scratch. The training materials are provided in an Excel file that you can download to your computer.
Good luck and hope you enjoy the course.
Who should follow this course?
Students that want to learn the basics of ETL/ELT testing and Data Quality Management
Business Analysts and Data Analysts that would like to learn more about ETL/ELT testing, frequently used queries and practical examples
Software Engineers that would like to build an automated solution for ETL/ELT testing using database views/dashboards
Data Stewards and Managers considering to apply data quality standards within their organization
Basic knowledge of SQL
Some experience with Visualization tools would be helpful, but not required
Basic setup of database (PostgreSQL, Oracle) and visualization tool (Qliksense) is recommended
What will you learn
The course consists of the following modules:
What is ETL/ELT Testing and Data Quality Management?
Build database views for Data Quality Monitoring
Build dashboards for Reporting