The document discusses challenges faced by companies with both in-house and outsourced software testing. It introduces predictive analytics as a solution to address common challenges like managing multiple releases and tools, measuring productivity, and generating customized reports. Predictive analytics uses models to analyze test data and predict issues, risks, delays and determine how to optimize testing. Integrating predictive analytics into a testing framework can help reduce costs, improve quality and make better decisions.
This document discusses risk-based testing and test progress monitoring. It explains that gathering metrics on product risks, defects, test coverage, and confidence is important for monitoring test progress objectively and subjectively. Inaccurate monitoring can lead to incorrect management decisions. Risk-based testing involves identifying project and product risks, assessing their level and likelihood, and mitigating risks through techniques like testing to reduce defects before release. The test analyst's role is to implement the risk-based approach correctly by determining what to test first based on risk.
One thing which we were observing since the year 2001 was how testing activities integrate with SDLC in early stages by using methodologies such as Agile. Agile was used by many organizations for shortening their development time. Also use of virtualization, cloud computing, and service-oriented architecture also become famous.
What is the difference between manual testing and automation testing
Manual testing involves human testers executing test cases, while automation testing uses automation tools to run test cases. Manual testing is time-consuming and relies on human resources, whereas automated testing is significantly faster. While manual testing requires investment in human resources, automation testing requires investment in testing tools and automation engineers who have programming knowledge.
Kasper Hanselman - Imagination is More Important Than Knowledge
The document discusses the need for software testing to adapt to today's complex, networked world. It argues that most testing still focuses on structured functional testing as if for standalone software, rather than integrated systems. It recommends that testers specialize in areas like usability, security, and gain domain expertise. Testers need to be flexible and creative in their approaches. The testing process also needs to align more with project management methods and tools to effectively deliver results.
Negative testing is all about ensuring that a product or application under test does NOT fail when an unexpected input is being fed. The purpose of Negative testing is to break the system and to verify the application response during unintentional inputs.
The document discusses regression testing, including its definition, benefits, when it should be applied, types, techniques, challenges and best practices. Regression testing involves re-running all tests to ensure new code changes have not introduced new bugs or caused existing bugs to reappear. It helps find bugs early, increases chances of detecting bugs, ensures correctness and that fixed issues do not occur again.
This document introduces software testing. It defines software testing as executing a program to find bugs based on specifications, functionality, and performance. The goals of testing are to find as many faults as possible and ensure the software works properly. Testing should start early in the software development life cycle and continue throughout. Different types of testing exist and test plans must be carefully made and documented.
All you need to know about regression testing | David TzemachDavid Tzemach
All you need to know about Regression testing| David Tzemach
1. Overview
2. What is “Regression” testing…?
3. When should you use it..?
4. How to implement..?
5. Test Recommendations
6. Considerations when building Regression tests
As a software tester, you may often face a situation in which your customer requires completing testing faster than you can handle given your effort and the amount of test. For example, in order to complete testing 2000 test cases for a build, you need at least 10 days to complete all testing. However, your customer needs to test and release the build within 5 days. You need to make a tough decision to handle this request. This presentation offers you one of the approaches that you can pursue. The presentation discusses an approach to prioritizing test cases using the principles of value-based software engineering. The approach is based on the principle that not every test case is equally importantly, e.g., not each of the 2000 test cases has the same value. A simple Excel tool will also be provided to allow you quickly prioritize test cases and select the ones that generate best value for your customer.
This document discusses risk-based testing and test progress monitoring. It explains that gathering metrics on product risks, defects, test coverage, and confidence is important for monitoring test progress objectively and subjectively. Inaccurate monitoring can lead to incorrect management decisions. Risk-based testing involves identifying project and product risks, assessing their level and likelihood, and mitigating risks through techniques like testing to reduce defects before release. The test analyst's role is to implement the risk-based approach correctly by determining what to test first based on risk.
What will testing look like in year 2020BugRaptors
One thing which we were observing since the year 2001 was how testing activities integrate with SDLC in early stages by using methodologies such as Agile. Agile was used by many organizations for shortening their development time. Also use of virtualization, cloud computing, and service-oriented architecture also become famous.
What is the difference between manual testing and automation testingEr Mahednra Chauhan
Manual testing involves human testers executing test cases, while automation testing uses automation tools to run test cases. Manual testing is time-consuming and relies on human resources, whereas automated testing is significantly faster. While manual testing requires investment in human resources, automation testing requires investment in testing tools and automation engineers who have programming knowledge.
Kasper Hanselman - Imagination is More Important Than KnowledgeTEST Huddle
The document discusses the need for software testing to adapt to today's complex, networked world. It argues that most testing still focuses on structured functional testing as if for standalone software, rather than integrated systems. It recommends that testers specialize in areas like usability, security, and gain domain expertise. Testers need to be flexible and creative in their approaches. The testing process also needs to align more with project management methods and tools to effectively deliver results.
Negative testing is all about ensuring that a product or application under test does NOT fail when an unexpected input is being fed. The purpose of Negative testing is to break the system and to verify the application response during unintentional inputs.
The document discusses regression testing, including its definition, benefits, when it should be applied, types, techniques, challenges and best practices. Regression testing involves re-running all tests to ensure new code changes have not introduced new bugs or caused existing bugs to reappear. It helps find bugs early, increases chances of detecting bugs, ensures correctness and that fixed issues do not occur again.
The document provides an overview of software testing basics, including definitions of key terms like testing, debugging, errors, bugs, and failures. It describes different types of testing like manual testing, automation testing, unit testing, integration testing, system testing, and more. It also covers test planning, test cases, test levels, who should test, and the importance of testing in the software development life cycle.
The document discusses using artificial intelligence and mathematical models in software testing. It proposes using a neural network trained on test case data to act as an automated test oracle that classifies test results as passed or failed. A mathematical model is introduced to represent the test case execution process. An algorithm is also constructed for a comparison tool to analyze results from the neural network test oracle and the actual tested software. The approach aims to help with regression testing of software by automating some of the decision making.
This document discusses agile test automation and addresses whether it is an essential truth, oxymoron, or lie. It notes that agile emphasizes parallel teamwork between development, testing, and business. While test automation may initially require extensive ramp-up time and skills acquisition, building a library of automated scripts and using programmatic test tools can help achieve faster feedback, consistency, and avoid technical debt. The document advocates automating tests in parallel with development in each sprint to allow for easy, flexible regression testing. It argues that with an evolving approach to automation and a focus on reusing test data, process knowledge, and results, agile test automation can be an essential part of the agile process.
This document discusses agile testing methodology. It begins with general concepts of agile testing such as testing from the customer perspective as early as possible. It then discusses agile testing methodology, challenges, test levels from first to third view perspectives involving extreme testing, exploratory testing, and collaboration between development and testing. The document also covers benefits of being an agile tester such as working as one team towards a common goal. In conclusion, it states that agile testing is useful, less time consuming and effective from the customer's point of view when automated testing is performed and developers, testers and customers work together as a team.
There is no doubt about the importance of automated frameworks in the Agile environment and as part of the day-to-day testing process. These are some insights to guide any automation project.
The document discusses concepts related to agile software development including lean principles, agile testing mindset, user story creation, retrospectives, continuous integration, and release planning. It emphasizes eliminating waste, delivering working software frequently, empowering self-organizing teams, and incorporating early and frequent feedback to continually improve the development process.
This document discusses best practices and common mistakes in implementing software quality metrics programs. It emphasizes the importance of understanding why metrics are being collected, measuring the right things in the proper context, and ensuring metrics are useful to stakeholders and help answer important questions. Common mistakes discussed include measuring the wrong things, forgetting context, collecting metrics sporadically, and failing to determine what constitutes "good" or "bad" metric values. The document provides examples of useful metrics and encourages linking metrics to goals, questions, and evaluation.
Talk for the Project Quality Day at Eclipse Conference Europe 2015. A presentation on how to perform risk based testing, using Jira, Jubula and Mylyn (and Spago4Q), appplied to a real-world use case, the SpagoWorld Shop
Software testing metrics are used extensively by many organizations to determine the status of their projects and whether or not their products are ready to ship. Unfortunately most, if not all, of the metrics being used are so flawed that they are not only useless but are possibly dangerous—misleading decision makers, inadvertently encouraging unwanted behavior, or providing overly simplistic summaries out of context. Paul Holland identifies four characteristics that will enable you to recognize the bad metrics in your organization. Despite showing how the majority of metrics used today are “bad”, all is not lost as Paul shows the collection of information he has developed that is more effective. Learn how to create a status report that provides details sought after by upper management while avoiding the problems that bad metrics cause.
The complete guide for negative testing | David TzemachDavid Tzemach
OVERVIEW
SO WHAT IS “NEGATIVE” TESTING ANYWAY?
GOALS OF NEGATIVE TESTING
NEGATIVE TESTING PROCESS
ADVANTAGES OF NEGATIVE TESTING
WHEN TO STOP NEGATIVE TESTING?
Why you cannot ignore negative testing?
TestPRO is an independent testing service provider that can fulfill the majority of the test delivery work that can be carried out on-site and deliver the cost saving that only a dedicated test center can provide. We will prepare and execute the tests and reporting all results to you in a timely manner.
The document provides an overview of software testing fundamentals including definitions of testing, why testing is necessary, quality versus testing, general testing vocabulary, testing objectives, and general testing principles. It defines software testing as verifying and validating that software meets requirements, works as expected, and discusses how testing is needed because humans make mistakes and software errors can have expensive and dangerous consequences. The document also provides definitions of quality, contrasts popular versus technical views of quality, and outlines key aspects of quality like functionality, reliability, and value.
The document provides an overview of the formal technical review (FTR) process. It discusses the objectives and benefits of FTR, which include improving quality and reducing defects and costs. The document outlines the basic principles of review, including a general inspection process with phases for planning, orientation, preparation, review meeting, rework, and verification. It also discusses critical success factors for effective reviews, such as using detailed checklists to guide inspection and allocating sufficient time for preparation.
Amp Up Your Testing by Harnessing Test DataTechWell
The data tsunami is coming—or maybe it’s already here. Data science, big data, and machine learning are the buzzwords of the day. Data is changing our products and the way we build them, so we should also change the way we verify our products. In a world of increasing connectivity and accelerated deadlines, data can provide an edge. But what role should data play in assessing the quality of software? Where does it make sense to use data, and where is it inappropriate? Steve Rowe covers the history of how data fits into testing, explains why data is an important tool to have in your quality toolkit, and presents strategies for adding data to your testing plans and using it more effectively in your testing.
Learn how to establish a greater sense of confidence in your release cycle, along with the practices and processes to create a high-performing engineering culture within your team.
Things to keep in mind before starting a test planNexSoftsys
If you are going to start a test plan, then you will know that most of the time in software testing, there is more debate on its quality and plan of activities. Today many things are worth noting, but you have to pay attention to these important things before starting the test plan.
This document provides a summary of Raghavendra Ganiger's professional experience and qualifications. He has over 2.7 years of experience in software testing, working on projects in the healthcare and insurance domains using agile methodologies. His skills include manual testing, test management using HP Quality Center, database testing with Oracle SQL, and experience in the full software development and testing lifecycles. He is proficient in test planning, execution, reporting and defect tracking.
The document provides an overview of Epson's problem-solving toolkit called the Innovation Engine. It describes Epson's DMAIC problem-solving approach and provides details on the core problem-solving tools used in each phase of DMAIC. These tools include project charters, SIPOC diagrams, process maps, voice of the customer analysis, cause-and-effect diagrams, prioritization matrices, and control plans/charts. It also outlines the typical roles and responsibilities in a problem-solving project and provides links to additional learning resources. The overall toolkit is part of Epson's effort to drive innovation and performance through a structured problem-solving methodology.
The document provides a summary of Lenora Alderman's qualifications and experience as a Quality Assurance professional. She has over 15 years of experience in QA project management, testing, and leading teams. Her areas of expertise include test planning, defect tracking, and working with various development methodologies.
Test Planning and Test Estimation TechniquesMurageppa-QA
In this Quality Assurance Training session, you will learn about Types of Testing , Test Strategy and Planning, and Test Estimation Techniques. Topic covered in this session are:
• Test Planning,
• Test Estimation Techniques
For more information, about this quality assurance training, visit this link: https://www.mindsmapped.com/courses/quality-assurance/software-testing-training-with-hands-on-project-on-e-commerce-application/
Project Management Tips to Improve Test PlanningTechWell
When done right, testing is more than test plans, test scripts, and executing tests. In fact a test leader should consider testing a sub-project of the larger development project. By applying the same techniques project managers use to plan and manage the overall project, test leaders can improve testing and greatly influence the entire project’s success. Ricki Henry explores project management processes that test leaders need to master—risk management, human resources, stakeholder communications, and scope management. Even though you understand that the scope of testing cannot be “everything tested with zero defects,” the customer does not have this same understanding. To prevent this disconnect, test leaders need to determine the scope of what can be tested and then articulate that to the stakeholders. Join Ricki to learn new ways to improve testing while contributing to overall project success through project management processes that test leaders need to master.
This document provides a summary of Sudhakar's professional experience in software testing. He has over 5 years of experience in manual and automated testing using tools like QTP and Selenium. He is certified in Pega System Architect 7.1 and has experience testing various projects for clients like Telstra and GE Healthcare. His responsibilities include requirements analysis, test case development, defect tracking, and reporting. He has a background in software testing methodologies and experience across the SDLC.
The anonymised slides from an old (but hopefully still relevant) talk on the case for placing a strategic focus on design testability. The material covers the technical, process and organisational considerations arising from such a strategy and is predominantly a summary of the ideas presented in Brett Pettichord's 2001 "Design For Testability' paper available here. The presentation makes a case for why a high level of design testability can be seen as a critical success factor in achieving sustained agility.
- The document outlines Polarion's test management software capabilities including creating and managing test cases, defects, requirements and specifications with Polarion LiveDocs. It allows defining and running test runs with the Polarion Testing Framework.
- It discusses how Polarion can help integrate requirements, testing and defect management and manage activities with all stakeholders.
- The presentation then demonstrates Polarion's abilities like requirements and test traceability, test planning and execution, impact analysis and reporting across projects.
The document discusses how exhaustive testing of all possible combinations of inputs and preconditions is not feasible for all but trivial software cases. Instead of exhaustive testing, a risk-based approach is recommended to focus testing efforts. This involves identifying the highest risks and priorities to guide testing, as attempting to test all aspects of a software system would require an unrealistic number of tests. The key conclusion is that the level of testing needs to be tailored based on project risks, costs, and time constraints rather than attempting to test everything.
Sarah Geisinger - Continious Testing Metrics That Matter.pdfQA or the Highway
The document discusses the importance of tracking the right metrics in continuous testing to improve collaboration, efficiency, and impact. It recommends measuring factors that cause pain for the QA, development, and user teams, as well as metrics focused on by leadership like deployment frequency, lead time, change failure rates, restore time, and reliability. The document advocates integrating QA metrics into the development pipeline for continuous improvement, and using dashboards for transparency.
Software Project Success Through Value AssuranceValueware
Valueware Technologies provides project efficiency improvement and technology services including project reviews, deployment support, and mentoring. With over 50 years of combined experience, they help clients increase project success rates, improve developer efficiency, and ensure budget compliance. Their services involve assessing projects for challenges early and providing recommendations based on proven industry best practices to supplement internal teams.
Testing Metrics and Tools, Analyse de testsHervKoya
Fundamental test metrics include base metrics that provide raw data and calculated metrics derived from base metrics. Major base software test metrics are the total number of test cases, number passed/failed/blocked, and defects found/accepted/rejected/deferred. Major calculated software test metrics measure coverage, effectiveness, effort, quality, and efficiency. Coverage metrics indicate how much of the application or requirements are tested. Effectiveness metrics evaluate how well tests find bugs. Effort metrics assess testing time and resources. Quality metrics track passed/failed tests and defects. Efficiency metrics examine defect fixing time. Test metrics provide visibility into testing and inform decisions to improve quality.
Anton Muzhailo - Practical Test Process Improvement using ISTQBIevgenii Katsan
Here are a few potential questions from the document:
- What is the true value of ISTQB certifications beyond just checking a box for management? How can the knowledge be applied practically?
- How can metrics be designed and used effectively to assess quality and test coverage in an agile environment? What are some examples of valid and invalid metrics?
- What artifacts or information are useful to include in a test plan even for agile teams using tools like JIRA? How can a test plan provide value beyond just additional paperwork?
- What techniques can be used to effectively estimate defect severity when multiple testers with different perspectives are involved? How can consistency be achieved?
- How can root cause analysis be applied
Similar to Predictive Analytics in Software Testing (20)
Anton Muzhailo - Practical Test Process Improvement using ISTQB
Predictive Analytics in Software Testing
2. The common problem most of the companies today face sudden
increase in costs, production delays and operational risks.
Introduction
Organizations which perform
testing using its in-house testing
environment and team.
Organizations simply
outsourcing its entire testing
activities to preferred vendors.
3. Challenges with in-house Testing
• Managing testing for multiple releases of different types of applications
• Managing multiple testing tools and required infrastructure usage and
productivity
• Measuring Testing team Productivity
• Identify Right Tester for particular task
• Unable to identify issues which can lead to challenges in future
• Unable to provide different stake-holders reports in preferred view
• Measuring Test coverage and quality of work
• Timely alerts and notifications
4. Challenges with Outsourced Testing
• Identifying the right vendor who have the required competency
to deliver the output as per expectations and vendor who is
flexible enough to adapt to changes
• Managing and communication with multiple testing vendors is
a challenge
• Difficulty in Identifying the root cause at a right time
• KPI reports and SLA adherence
• Measuring Test coverage and quality of work
• Difficulty in identifying the root cause of an issue
• Implementing quick changes is a challenge
5. Common Challenges and Expectations
• Every stakeholder have different expectation in terms of KPI reports , test
results, Audit reports, Test management reports, Other metrics, etc..
• There are no standard expectation on reports. Demand of reports might
change based on that situation and Stakeholder requirements.
• Not able to produce desired analytical reports and its time taking process
to generate OnDemand Analytical reports
• Is project going in right track ?
• Who is the right tester for this assignment?
• In my testing practice where exactly I am incurring more cost ?
• With the current pace of the project will I be able to meet the deadline ?
• Project got deviated ! What measure I should take to accomplish the
project with in the set Deadline?
• Not able to generate expected report because data is residing in different
sources.
• Many more challenges..…
6. Predictive Analytics in Software Testing
Predictive Analytics is a data driven technology which can be leveraged to predict failure points in testing
activities and determine the future. It has the power to help optimize project data and make proactive
decisions.
Predictive analytics helps in predicting the present and taking
proactive measures for future.
There are 3 major techniques which can be used in Predictive Analytics
–
• Predictive model
• Descriptive model
• Decision model
Based on the KPI requirements or expectations of the clients applicable
model can be applied and expected report can be generated.
Predictive Analytical solution will helps answering many such questions
which we might not derive from existing testing tool based reports
• How will it affect my Testing project?
• How do we do things better?
• What is the best decision for a complex problem?
Predictive analytics
helps in reducing the
testing costs and
deriving to better ROI
early in the testing life
cycle.
7. Advantages of Predictive Analytics in Software Testing
• Predictive Analytics helps in identifying right tester for
particular task
• Predictive Analytics helps in monitoring overall project status
• Predictive Analytics helps in identifying issues impacting various
areas of project
• Predictive Analytics helps in proactively identifying the risks
and mitigating the risks at the earliest stage
• Predictive Analytics helps in identifying where is the delay and
what is the issue
• Predictive Analytics helps in monitoring tester and testing team
productivity
• Predictive Analytics helps in right vendor for the particular
project
• Predictive Analytics helps in Improve Planning, Quality and
Delivery
• Predictive Analytics helps in making right decisions at right
time.
8. Predictive Analytics in Integrated Approach
In a testing practice multiple testing activities performed
and multiple testing tools are leveraged to fulfill the
requirements and each testing tool works in silos and
respective testing data and logs storing in silos.
To optimize the cost, time and effort, it’s suggested
to go with new techniques and technology and
integrate predictive analytical tool into the
integration framework.
9. Conclusion
Predictive Analytics helps in increasing the efficiency and
improves the effectiveness of the testing operations
Predictive Analytics helps in Improve Planning, Quality and Delivery
10. Thank you for attending our webinar.
- K.Pavan Kumar
Editor's Notes
Typically, testing companies follow a lengthy process for any testing project in an effort to reduce operational issues and costs. However, these companies still need to encounter many issues with every new project. Lets look at some of the challenges involved with in-house testing.
The development companies that outsources all the testing activities would look forward to focus more on core business while avoiding ever increasing costs associated with testing. However, these companies still face a lot of delays for deliverables and exceeding costs. Lets look at some of the challenges involved with outsourcing testing.