Praduman

Oh, yeah. Uh, I'm Pratuman Praswaha from Gorakpur. I have completed my BTech in computer science from conference to dev technology. Um, Overall, I have a three year success in the full stack development, and, uh, I have developed for, like, multiple CRMs, so multiple, uh, client website. My major, uh, fields of working, like, uh, I have developed multiple project in the fintech industry, ecommerce. And, uh, currently, I'm working at with our skin care technology. And, uh, here I have developed multiple CRMs, multiple, uh, client website. And I have also included many thought about API here, like, uh, payment gateway with Razorpay, Joho, LeadSquared, and other, uh, many more. And, uh, previously, I were I were working at the Kabil Finance private template, and, uh, there was also I developed some, uh, dashboards and some systems, like a ledger management system for tracking overall payment history, gold management system for tracking overall gold history. And but technically, skill includes like React JS, Next JS, JavaScript, SQL, NoSQL, and, uh, I'm also familiar with the AWS deployment and the CICD. Yeah. It's all about me.

So, basically, in this, we are finding intersection. Oh, let's suppose we have two array. So, basically, we are finding, uh, city. So, basically, our time complexity analysis is outer loop runs like, uh, error length times, like, big of n. And, uh, inner loop also will or, like, uh, array to that array to length to length. Like, we go off, I can say, yam. And the intersection includes like, uh, it's run, uh, Vivo of k. That's okay. Where k will be the, like, uh, side of the intersection. So in the I can say in the worst case, uh, basically time, uh, complexity will be like we go up n. So let's suppose we talk about the, like, improve the time complexity, then we can use, like, a set, uh, to reduce lookup from the big o op n to big o op one. So, basically, I can, uh, improve, like, time time complexity in this. Like, we can, uh, just create a set, and, uh, in the set, we can, uh, like like, I will create the setup like a array a second array, like array of two. And, uh, basically, we will check, like, if array of two has, like, a area of one, uh, value, Then we will, uh, add, like, a week. We will also create an, uh, new set, and in that set, we can add. Yeah. By this, we can, uh, improve the time complexity. So building set to, like, will be a big o of n and looping through area of one and checking basically so at least set will be, like, big o of n. So in that case, like, uh, time complexity will be a big o of n plus m. Yeah.

This query. For the query optimization. So, basically, for audiences, uh, if there is no any proper, uh, indexes, then MongoDB will, like, perform collaging, like, call scan, basically, or that will be scan, like, overall. So I can say, let's suppose, uh, we have not, like, proper indexes. So first of all, we are querrings, then in that case, uh, that query will be scanned over all our table. That's what we will, uh, create indexes. So, basically, uh, we we can create, uh, further improving, uh, query performance. We can, uh, create indexes on the customer ID, and we can also create index for the status and the total amount. So, uh, basically, by using, uh, indexes, we can improve the query performance. And, uh, we sort of avoid, like, a large sort in the memory. If we sorting, uh, without any index, then MongoDB MongoDB basically, uh, much load result in the memory. Then after that, there will be sort.

The following the component. Yes. So I can identify I can identify the issue. So, basically, there are some issue. Uh, basically, use this effect or missing dependency area. So we should use, like, uh, dependency area in the use effect. So, basically, that will run on every render without, like, urgency. So, basically, we sort of use, like, uh, dependency area for and we can pass the pound. And then there's also, like, uh, fetch option is the wrong. Data AG here not, like, not validating. And, also, in the face, like, uh, content type is missing. And we are also, uh, um, some issue in the, like, increment. Uh, we are incrementing, uh, twice. Yeah. Yeah. These are the basically, in this company.

So, basically, uh, in this time complexity, we'll be like Vivo of n square, and, uh, it's phase complexity. Basically, we go up one. Basically, in the outer loop runs like n times and the inner loop runs like n minus I time. So total of present basically, uh, so, basically, overall, like, time complexity will be go up n square. And the further improving this, we can use like. So we can improve, uh, we can reduce, like, time complexity to, uh, Vivo of n by sorting visited. So in that case, like, time complexity will be also like Vivo of n and, uh, time complexity will be Vivo of n and, uh, also, space complexity will be of Vivo of n squared. We go no. His face complexity will be also like big open in that case. And, uh, using our two pointer, we can also do or, like, uh, if a array is sorted in that case. So in that case, like, also time complexity will be, like, we go up n and, uh, it says complexity will be, like, we go up one.

So, basically, uh, boxing this function, like, uh, everything like global, uh, variable is misused. And this, like, global count is particular outside. And, uh, global global count is particular outside too. For system, like, multiple function calls. Like, uh, so each each call will accumulate, like, result incorrectly. And we are we can I can say even this also we are, uh, doing unnecessary check, like, if, uh, there is the, like, loss loss equality in this also? And, uh, so, uh, best practice in this weekend, uh, follow, like, uh, no global variable, no global state in this function. We should create, like, pure functions. And we we should do, like, a strip equality, not, like, lose equality. And we should be doing, like, a local variable, like, Latin forms, mister top, like, where.

So, basically, our line one and line two, we need to check if, like, overlap. So, basically, two line segment do not overlap. Only if one ends before the other start. Like, uh, like, if integrated than start two or in the two, like, uh, no. No. In the in the one like which, uh, less than start two or in the two less than start one. Otherwise, this will overlap.

Give me no privacy. In that case, several services one and service two. Each time counting affect. So key accept. So the only key accept from the code. Basically, service one is the, like, fast tender premium service, and, obviously, service two is Oslo and a non premium service. And and this, like, something which service to use text in the two parameters, like is premium, which is light consuming, and for preferred service. So it will be checked like a service down. So, basically, it will be checked like if serving down, then two return service two. If I do service, like, exist return, uh, mhmm. So in this, the possible test cases, basically, test when the service is down. So, basically, if service down, then we should return, like, pro and accept the result will be like service two. And, uh, basically, second and secondly, when our preferred service is provided, preferred service will be set like service one or two. So in that case, accepted result will be like preferred service. So, basically, I let you know the, like, uh, summary of this.