Knot Solutions Interview Questions, Process, and Tips

SDLC stands for Software Development Life Cycle, which is a process used by software development teams to design, develop, and test high-quality software products.

• SDLC is a structured process that consists of several phases such as planning, analysis, design, implementation, testing, and maintenance.

• Each phase of the SDLC has specific goals and deliverables that must be completed before moving on to the next phase.

• Exam...read more

Defect life cycle is the process of identifying, reporting, fixing, and verifying defects in software development.

• Defect identification: Defects are identified through testing or user feedback.

• Defect reporting: Defects are reported in a defect tracking system with details like severity and priority.

• Defect fixing: Developers fix the reported defects based on priority.

• Defect verification: Testers verify that the defects ...read more

I expect to contribute to quality assurance, enhance testing processes, and collaborate effectively with the development team.

• I expect to ensure software quality by identifying bugs early in the development cycle, similar to how I found critical issues in my previous projects.

• I look forward to collaborating with developers to understand requirements better, which can lead to more effective test cases.

• I aim to continuou...read more

Testing is the process of evaluating a system or its components to ensure they meet specified requirements and function correctly.

• Verifies that software meets requirements: For example, checking if a login feature works as intended.

• Identifies defects or bugs: For instance, finding an error that causes the application to crash.

• Ensures quality and performance: Testing the load capacity of a web application under heavy tr...read more

Implementation of pipeline involves creating a series of data processing steps to move and transform data from source to destination.

• Define the data sources and destinations

• Design the data processing steps

• Implement data transformation and cleaning

• Automate the pipeline for regular data updates

• Monitor and optimize the pipeline performance