Divyavani Kummari
QA Engineer
About
Motivated Computer Science & Engineering graduate with hands-on Software Testing training (SDET) from Qspiders, Basavanagudi. Skilled in Manual Testing, Selenium WebDriver automation with Java and TestNG, API testing, and Agile/Scrum methodology. Knowledge on designing test cases, test scenarios, and test plans while working with SDLC, STLC, and Defect Life Cycle concepts. Familiar in building end-to-end automation frameworks using Page Object Model (POM) with TestNG, Maven. Strong academic background with 77% in B.Tech (CSE) and 98% in 10th class, demonstrating consistent excellence and attention to detail.
Skills & Expertise (31)
Work Experience
Selenium + TestNG Automation Framework Developer
E-Commerce Web Application
Present - Present
Built an end-to-end Selenium Java automation framework from scratch following Page Object Model (POM) design pattern — separating page-level locators and actions from test logic for maintainability and reusability. Configured the project with Maven (pom.xml) for dependency management — integrated Selenium WebDriver, TestNG libraries without manual JAR additions. Automated key user workflows including User Registration, Login, Product Search, Add to Cart, Checkout, and Order History — covering positive, negative test scenarios. Implemented TestNG annotations (@Test, @BeforeMethod, @AfterMethod, @BeforeClass) and parameterized tests using testng.xml to enable data-driven execution. Integrated screenshot capture on test failure and generated ExtentReports HTML execution reports — documented 50+ automated test cases with pass/fail status and failure screenshots. Handled Selenium WebDriver challenges including dynamic elements, dropdown handling, popup/alert handling, mouse actions, scrolling, and explicit/implicit waits (Synchronization). Tracked test defects, maintained traceability between test cases and requirements, and reported bugs in JIRA with detailed steps to reproduce, severity, and priority labels.
Big Data Analytics Developer
Social Media Tweets
Present - Present
Developed a Big Data Analytics system to identify bot activity in social media tweets by analyzing large volumes of tweet data for patterns and anomalies indicative of automated accounts. Applied Machine Learning and Natural Language Processing (NLP) techniques to detect and flag suspicious accounts spreading misinformation or propaganda on social platforms. Designed data preprocessing pipelines to clean, normalize, and extract behavioral features from raw tweet datasets for model training and validation. Validated model accuracy by evaluating detection precision and recall rates against labeled bot/human tweet datasets — documented findings in a structured test/evaluation report.
Education
Bachelor of Technology — Computer Science & Engineering (CSE) - SVR Engineering College, Ananthapuramu
- 2025 · Afghanistan
Intermediate (MPC) - Sri Sri Venkateswara Junior College
- 2021 · Afghanistan
SSC (10th Class) - Excellent E.M. High School
- 2019 · Afghanistan
Certifications
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Skills (31)
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