Technical Interview Questions

Tej prakash V. - "DNS is a service for resolving hostname and provide fully qualified domain name of the host."See full answer

T I. - "Idempotence refers to the property that the same request multiple times produces the same result on the server side. No matter how many times I repeat the request, the server state does not change after the first request. This concept is important to ensure consistency, especially in systems where requests may be repeated due to network failures or other problems. Let's take a look at different HTTP methods for a clearer understanding. GET: By definition, GET requests must be powerless. Execut"See full answer

Joohi M. - "Drew the following framework - Maturity of the tech (if it is too mature then consider buying), Competitors (how many, when are they launching this new tech etc.), Market Share of competitors, Financial considerations (build vs buy NVP), Collaborators for this tech, Economic Climate (Anti-trust, crisis etc.)"See full answer

Divya R. - "public Double calculateRatio(String source, String destination) { Double ratio=1.0; while(graph.containsKey(source) && !visited.contains(source)) { visited.add(source); Map valueMap=graph.get(source); if(valueMap.containsKey(destination)) { return ratio*=valueMap.get(destination); } Map.Entry firstEntry=valueMap.entrySet().iterator().next(); source=firstEntry.getKey(); ratio*=firstEntry.getValue(); System.out.println("Entered"); } return null; }"See full answer

Exponent - "This is a Technical question. It tests your ability to understand high level technical concepts. Even though your job won't have any coding involved, you'll still need to understand these concepts. Being able to cover all these topics with clarity communicates confidence in your interviewer. Unfortunately, there's no formula for technical questions, but some general tips are: Use analogies when you can Break your solution into clear, bite-size steps Don't be afraid to use examples to b"See full answer

Surbhi G. - "When we collect too much user data or survey responses, we risk creating data overload, which can hinder data analysis by clouding important insights with excessive, unnecessary information. This could make it more difficult to discern meaningful patterns or trends from the data, adding complexity to our data processing tasks and potentially leading to incorrect conclusions or strategies. Furthermore, over-collecting data may compromise users' privacy and trust. If users find out that a company"See full answer

Anonymous Stork - "AWS"See full answer

Anonymous Panda - "SDLC stands for Software Development Life Cycle, which is a process used by software development teams to design, develop, test, and deploy high-quality software products. There are several SDLC models, including the Waterfall model, Agile model, and DevOps model. Here's an overview of each model and how I would implement it: Waterfall Model: This model is a linear sequential approach, where each stage of the software development process must be completed before moving on to the next stage. T"See full answer

Anonymous Muskox - "An operating system like Android Go for low-powered devices. Slimming of application like Google Go or Gmail Go which is focused on the emerging markets. Strategic partnership with local telecom companies to provide free wifi to emerging or markets with low data. For example -> Facebook partnered with JIO in India to make the internet penetration more deep. "See full answer

Vishal T. - "Go has simpler syntax than Java. It is light weight. It is not Object Oriented. It does not support function overloading and function overriding. But these are small technical differences. Both are similar when it comes to testing. You have to create a mock object and implement an interface. Functionally, I did not feel any major difference."See full answer

Anonymous Muskox - "So Machine learning provides the ability to machines to learn patterns from large data. So applying the same when needed. So the type of algorithm depends on the requirement/use case or the data. For example, if we have data that is labeled and we need to do classification then we will go and perform logistic regression but if we want prediction instead of classification, then we will go and build a regression model. In case the data is not labeled, then we can go ahead and build a model usin"See full answer

Anonymous Muskox - "Metrics which Youtube Consider before building a recommender system Number of likes on a video by user The watch time of a video by the user The video disklied by the user The video share by a user The video skipped or churn with 20-30 seconds. Depending on this Youtube build a recommender system. The video suggestion feature in youtube works based on the recommender system. It may use a hybrid of batch prediction and online prediction. So depending on the above metrics, the youtube p"See full answer