Understanding OCR

OCR is a technology used to convert scanned documents or images containing text into computer-readable text, allowing automated data extraction and analysis.

Real-life Applications of OCR in Automation Testing

Extracting Data: Extract crucial information like invoice numbers from invoices, receipts, or forms. By using this, we can perform validations, ensuring that software correctly processes and stores such information.

Test Data Generation: Reads test data from legacy systems or documents and creates test scenarios and test cases, reducing manual effort in data preparation.

Example 1: Extract product details, prices, and customer information from invoices and purchase orders. This is used to perform end-to-end testing, ensuring accurate order processing and improving customer experience.

Example 2: Digitize prescriptions and medical reports which are used in automated testing of EHR systems, guaranteeing the correct storage and recovery of patient information, medications, and treatment histories.

Introduction to NLP

NLP is a branch of artificial intelligence that helps computers understand, interpret, and generate human language. Its role is to bridge the gap between human communication and machine understanding, allowing software to process, analyze, and respond to text and speech data in a way that resembles human language comprehension.

Real-Time Examples of NLP in Automation Testing

Log Analysis: Identifies patterns and errors in log data, automates the detection of exceptions, and reduces the need for physical log inspection.

Test Case Generation: Converts natural language requirements into executable test cases. By translating textual descriptions of desired functionalities, NLP streamlines test case creation, ensuring that test cases accurately reflect intended behavior and reducing the time required for test design and scripting.

Chatbot Testing: By simulating user conversations with natural language, NLP ensures the chatbot’s understanding and ability to provide appropriate responses, improving overall functionality and user experience.

Accessibility Testing: Assesses the clarity and correctness of textual content for screen readers and visually impaired users.

Localization Testing: Automatically compares source and target language content to ensure that localized versions of software or websites accurately reflect the original text and cultural requirements for various global audiences.

Integration of OCR and NLP

Combining OCR and NLP in automation testing allows for advanced capabilities, such as extracting and comprehending text from images or documents, enabling sophisticated data validation and test case generation.

Extracting Text from Images: OCR can extract text from images, making content machine-readable. NLP can then analyze the extracted text, allowing automation scripts to validate the information in image-based UI testing.

Sentiment Analysis on User Reviews: NLP can perform sentiment analysis on user reviews, categorizing opinions as positive, negative, or neutral. Combined with OCR, you can extract textual reviews from images or unstructured data sources, enabling automation to assess user sentiment without manual data entry.

Benefits of Using OCR and NLP in Automation Testing

The integration of OCR and NLP minimizes manual effort in data entry and test case generation, allowing testing teams to focus on higher-level tasks. Additionally, these technologies excel at handling complex scenarios, such as analyzing vast amounts of textual and visual data, enhancing test coverage, and overall testing effectiveness.

Conclusion

In conclusion, the synergy of OCR and NLP in automation testing promises a transformative leap in efficiency, accuracy, and coverage, ushering in a new era of software quality assurance where intricate testing challenges can be met with ease, precision, and speed.

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In software Lifecycle Management, the test initiation phase comprises test estimation and Proposal Decks. What is Test Estimation? Why do we need to perform Estimation for all Engagements? This is the question all testers and Leaders will have in their minds. Let us discuss them in depth and the various techniques to achieve the Test Estimation appropriately.

Data In software Lifecycle Management, the test initiation phase comprises test estimation and Proposal Decks. What is Test Estimation? Why do we need to perform Estimation for all Engagements? This is the question all testers and Leaders will have in their minds. Let us discuss them in depth and the various techniques to achieve the Test Estimation appropriately.

Test Estimation plays a vital role in each engagement we work on. To find out or assess how long the tasks and testing activities will take to complete and deliver with Cost and resources, Test Estimation is more important.

What should I estimate?

Timeline: Based on the Testing Methodology or Model proposed by the business, work out the timeline required for the Project or Engagement. Deadlines and deliverables should be effectively considered while deriving the timeline for the Product Release.

Cost: Basically, all engagements will be worked out based on the Budget Planned and requested. We need to analyse and come up with a solution for how much money we need to invest to complete this Project.

Resources: To achieve the agreed Deliverables, we need Human Resources, Material Resources, facilities, and Capital on time.

Skills: Human skills play a vital role in every deliverable. Right Leadership, Knowledge in Testing areas, Experience in tools and technology with which we work, Ability and Flexibility in work, and adapting to changes and culture also matter.

Techniques to derive Estimates.

Work Breakdown Structure –

This is the common and familiar way of performing Test Estimation for a Project. As a first step, we will breakdown the Project components into small pieces / executable groups. And these groups are further drilled down to multiple sub-groups or tasks in a measurable way.
Based on the split, we will measure the resources that need to be assigned for each task. Sizing each group based on a timeline and consolidating them phase-wise should give a considerable effort estimate. Post that, include Project Management activities effort and Buffer time to complete the estimates.

3 Point Estimation:

This is a statistical method of evaluating the Project Requirements. Each Requirement is broken into multiple sub-tasks, and then a 3-point estimation is applied to each sub-task.

• Optimistic Estimates: This is nothing but assuming a requirement will never go wrong and all conditions applied to that will stay positive. All resources are highly skilled and will stay until the Project is complete. No risk or crisis will pop up during the project timeline.

• Most likely Estimates: This is a typical case where we can expect a few challenges, but most of the tasks will go as expected. We should be able to drive the Project with the best and most skilled available resources, and no major crisis will come in our way.

• Pessimistic Estimates: In this case, our crew will have limited resources and an inappropriate skill set. Most of the tasks will deviate from our plan. Downtime and stability challenges in the development and testing phases will be encountered.

Keeping these scenarios in mind, we can put the estimates for each requirement together, and we can find the Medium Person days or Man hours to derive the final figure.

Percentage Distribution:

In this method, we can evaluate based on the scope and Phases of the Project. Split the testing phases according to the Software testing lifecycle and the types of testing planned to be delivered. Then, based on your previous experience or a similar Project’s experience, you can derive the Percentage for each Phase and Type. Have the overall estimates or manpower efforts in mind and split them according to the phases.

For example, if we are testing a Web Portal application, the below Percentage may work.

This technique should be used only if you have prior experience evaluating similar Projects. Moreover, you can improvise the estimates and shuffle the percentage across phases based on your previous Project’s metrics and the SME’s discussion.

This method is easy to apply, and it doesn’t require any specific tools to complete the testing effort.

Use Case or Test Case Point Estimation

This technique is also known as the Sizing method of estimation and is an extension of the Work breakdown structure method. We have already broken down the Project Requirements into modules, functionalities, and sub-tasks. After that, calculate the complexity of the sub-tasks for each type of testing. Complexity can be defined into 3 or 4 types based on the Project scale. Size the functionality based on the operations and test steps involved in your testing. It can be grouped as below:

Simple is between 1 and 3.
Medium is between 4 and 7.
Complex is between 8 and 16.
More Complex is between >16.

Based on the functional Test Case Point size, derive the estimates for each phase and calculate the final estimates.

Sample Test Estimation and Preparation

Keeping these Use case and Test case point factors in mind, below is the template derived to perform Testing in Multiple Environments, various types of Testing techniques, Multiple Iterations, covering all Phases, critical to Low complexity requirements, Test Data Management, Quality Monitoring activities, automation and performance scope testing, and warranty support.

We can include or exclude the factors based on our Business Requirements and Scope in the Test Estimation template to achieve our numbers.

Template Workbook Contents

Cover Page: Provide Author, Document version, and Published Date details.

Requirements Sheet: Have a requirement sheet for classifying the requirements into Simple, Medium, and Complex categories.

ST/SIT/E2E/UAT: Detailed sheet for grouping the requirements into Simple, Medium, and Complex categories based on the Testing Type.

TCP Template: Jot down the types of testing (ST, SIT, E2E, etc.) along with the Size of the testable requirements (Simple, Medium, or complex) in a table format. Put down the values for each requirement based on the complexity of your application. The following is an example: more rows within each table (Interfaces, Reports, Extensions, etc.) and more tables can be added as required:

Based on the Test Case Points, calculate the efforts for each phase using productivity. For example, Test Design can take 20 minutes for each testable requirement and 30 minutes for Test Execution.

Effort Summary: A Phase-wise Effort Summary should be calculated based on Percentage distribution, whereas Test Design and Test execution phase efforts are derived from the above TCP methodology.

Assumptions: Have a worksheet for putting down the General Assumptions we considered for evaluation and the functional assumptions.

Best Practices to Follow While We Do Estimation

Remember your experience: Increase or Decrease the estimates based on the Metrics you achieved in your previous Projects. Points to consider are Productivity variations, Test Management activities, Defect rates, and Resource Skill sets.

Risk/Mitigation Plan Factor: We bumped up the number in the Design and Execution Phase considering Resource availability, Access and Environment Downtime issues, and Code Quality.

Add buffer time: have 2 to 5% extra efforts derived in Requirement gathering, Test Management Activities, and the closure phase to catch up on Domain knowledge, New Tool studies, and unexpected challenges during the project under test.

Stick to your estimation: Estimation may go in deviation when we get along with the Project. So, it is always best to keep an eye on the estimation and make modifications if required. We should not expand the values after we fix them, except when we have change requests or Minor Enhancements to the scope.

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