Mohd imad

Could you help me understand more about your background by giving a brief introduction? Of course. So, uh, my name is Mohammed, and I am having, uh, 3.5 years of experience. And I'm currently working in Antenno Labs as a Java developer. And, uh, prior to my, uh, work experience, I have completed a 3 years of diploma in production engineering. And after that, I have worked 2 years in big events, like HCL Technologies and Bracklin Pix Private Limited. And after that, I have completed my graduation b tech in mechanical engineering, which is, uh, about, uh, 3 years. And after that, I have joined variable softwares for 1 year. And then, again, I have moved to another company, which we named Olean Consulting Private Limited. So if I talk about my, uh, uh, these, uh, two experiences are as of Java developer only. And I did not, uh, move into any front end or any other technologies. I'm a whole and sole pure back end Java developer. And in this, uh, and after ring consulting, I have, uh, joined this startup, uh, Antio Labs in Gurgaon. And in this, uh, company, I have, uh, almost completed, uh, 7 months. And right now, I'm looking for a great more great opportunity and more stable job where where I can learn more and explore. So that is the only reason I'm switching. And, uh, yeah, just to, uh, get more, uh, great, uh, opportunities to enhance myself better. Thank you so much.

Propose a method to handle exceptions globally in a spring boot application while aligning with restful standards. Alright. So, basically, uh, what happened is to handle exceptions globally in spring boot applications while aligning with the restful standards, you can reuse springs at the rate controller advice annotations along with at the rate exceptional handler methods. Like, uh, we first, we can create a global exceptional handler like for an example Steps create a class annotated with add the rate controller advice define methods within this class annotated with alternate exceptional handler handler to handle different types of exceptions. Secondly, define exception handling logic in each at the rate exceptional exception handler method define the logic to handle the specific exceptions. This can include returning an appropriate HTTP status code error message and any Additional information Ensure that the response body adheres to restful standards providing clear and meaningful error messages. Handling handle specific exceptions like handle common exceptions such as illegal argument exception, no such element exception, s HTTP client error exceptions, HTTP server error exceptions, etcetera. Customized error responses based on the exception type provided relevant information. We can provide it to the client. Moreover, we can return standardized error responses like return standardized error responses in JSON format following restful conventions. Typically, this includes an error code error message and optional details. We can use response entity for flexibility, test exceptional handling, and much more.

Suggest techniques to secure a Spring Boot application against SQL injection attacks when integrating with a SQL database, all right. So to secure a Spring Boot application against SQL injection attacks when integrating with a SQL database, we can employ techniques like prepared statement, like use parameterized queries or parameterized prepared statements when interacting with database, prepared statements separate SQL code from user input, preventing malicious SQL injections attack, and we can follow ORM frameworks like Utilized Object Relational Mapping frameworks like Hibernate or Java Persistence API provided by Spring Data. So these frameworks automatically handle SQL generation's parameter binding, reducing the risk of SQL injections. We can also validate inputs like sanitize user input before using it in SQL queries. We can use libraries like Hibernate, Validator, or Spring's Address Validation Annotation to enforce validation rules on user input. And we can also put a whitelist input validations which implement whitelist input validations to restrict the user input to expected values or patterns, reject any inputs that does not adhere to the whitelist preventing attackers from injecting malicious SQL code. Database access control enforce principle of least privilege by ensuring that database user have only the necessary permissions required for this specific task, avoid, we can avoid using accounts for application access. Database configuration, connection pool to use appropriate connections, setting and connection pooling mechanisms, escape special characters, we must concatenate user input into SQL queries which is not recommended, use proper escaping mechanism to escape special characters. Security audits and code reviews we can also perform, we can perform database firewalls and intrusive detection system IDS. And we can use Spring Data JPA query methods as well, like we can leverage data JPA query methods and query derivations capability to define queries using method names.

How would you configure secondary level caching in a hibernate powered Spring Boot application? Okay. So, uh, we can, uh, what we can do, is to configure secondary level caching in a hybrid powered spring boot application. We can follow such steps like uh, we can choose a caching provider. Hibernate supports various caching providers such as a cache in in Finnish span, Hazelcast, and Redis. Choose, uh, we can choose a caching provider based on the requirement and the infrastructures indeed. And we can add caching dependencies. Like, we can include the required caching dependencies in form.xml or build out detail file. For example, if we are using any cache and the encaching dependencies, we can, uh, enable caching hibernating configuration, configure hibernate to use the chosen caching provider with specifying the appropriate properties in the application or properties or application or volume and files. We can you also go with entity caching and enable caching for specific entities by annotating them with accurate cacheable and specifying the caching strategies. Whereas, we can also perform query caching. We can enable caching for specific queries by using the query at the rate query in annotation. Configure cache regimes. Optionally, we can configure cache regions to customize caching behavior for different entities or queries. This allows us to fine tune caching settings based on specific requirement. We can also perform test and monitor for our application to ensure that caching, uh, is working as expected, Monitor cache using and performance usage performance to identify any potential issues or important links.

How do you architect a scalable database schema that supports Hibernate's lazy loading and eager fetching strategies? Okay, so to architect a scalable database schema that supports Hibernate's lazy loading and eager fetching strategies, we need to carefully design our database schema, which can optimize performance while minimizing unnecessary data retrievals, right? So on the first line, we can normalize our schema, like we can follow normalization principles to reduce redundancy and maintain data integrity. We can split our data into logical tables to avoid data duplications and anomalies. We can also use identify relationships between entities and define them using foreign keys. We can use one-to-one, one-to-many, and many-to-many relationships as appropriate based on our application requirements. We can also, under use lazy loading and eager fetching appropriately, we can decide when to use lazy loading and eager fetching based on the access patterns and performance requirement of our applications. Similarly, lazy loading should be used for associations that are not always needed and may result in a performance overhead if eagerly fetched every time. Eager fetching should be used for associations that are frequently accessed together and can benefit from being fetched in a single query to avoid n plus 1 query problems. We can optimize fetching strategies as well. We can use batch fetching to reduce the number of database round trips when fetching multiple entities. Hibernates at the rate batch size annotation can be used to configure batch fetching for associations. Consider, we can use also at the rate fetch, fetch mode, subselect, or collection to fetch them in a single query with subselects, which can be more efficient than individual query for each collective element. We can also denormalization, denormalize our schema when necessary to improve query performance and reduce the need for joints, especially for read heavy operations. We can use caching mechanism to store denormalized data for, or frequently access data to further improve performance. There are more points which we can also do. We can optimize indexing. We can partition and sharding. We can testing and performance tuning as well. Consider partitioning and sharding your database to distribute data across multiple services and improve, which will improve scalability, which we can use horizontally, partioning based on key ranges, hash values, or other criteria to distribute data evenly and minimize hotspots.

How do you ensure the transactions in a Spring Boot application are handled correctly using ACID properties with an SQL database? So, to ensure transactions in a Spring Boot applications are handled correctly using ACID properties Automaticity, Consistency, Isolation, Durability So, we can use Declarative Transactions Management, Leveraging Spring's Declarative Transaction Management capabilities which allow us to define transactional behavior using annotations such as AddTheRateTransactional Similarly, we can annotate service method or controller method with AddTheRateTransactional to specify transactional boundaries We can configure a Transactional Manager in our Spring Boot application to manage transactions with the underlying SQL database Spring Boot auto-configures a Transaction Manager if it detects the presence of a data source being in the application context We can also explicitly configure a Transaction Manager by extending org.springframework.transaction.annotation.enableTransactionManagement We can understand ACID properties as well which can ensure a clear understanding of ACID properties and their implications when designing and implementing transactions Automaticity means transactions should be atomic meaning they are either complete successfully or rolled back entirely or in case of failure Consistency, transactions should leave the database in a consistent state adhering to all defined constraints and integrity rules Isolation means transactions should be isolated from each other to prevent interference and maintain data integrity We can use appropriate isolation levels such as read committed or serializable Durability means committed transactions should be durable and persist even in the event of system failures We have to handle exceptions properly as well We need to optimize transaction scope as well and test the transactions where we can write comprehensive tests to validate transactional behavior under different scenarios

Reviewing the following Java snippet with spring annotations explained by this code might lead to a runtime issue when using that great auto wide and how do you solve it? So the code is at the rate service public class user service at the rate auto wide private user repository user repository public user, find user, pass string username, which return user repository dot find by the username. Under bracket, we are passing username. K. So, uh, in this, uh, seems to have syntax and logical issues, which we can adhere. Like, uh, the potential issues with the code is auto wiring AdWords. They seem to be an attempt to auto wire our object name object name, like, which might be intending to be. Alright. Okay. Method naming conventions also is there. Like, method implementations, uh, are also And there are there is a constructor injection is used to inject dependencies into user service. This is a good practice and it's made dependent to explicit and promise an easier testing. So, basically, uh, in this summary, the potential runtime issue may arise from misconfigured or missing beans for auto wiring incorrect method names or missing method implementations in the user repository. To solve these issues, ensure that the dependency are properly configured following name convention and implement required methods in the user repository.

In the given hibernate entity snippet, identify and explain what is incorrect in regards to the JPA entity specifications. So the code here is written like at the rate entity public class product. Curly brace open. Inside it, it's written at the rate ID, at the rate generated value strategies. It was a generation type dot auto. Private long ID at the rate column name is equals to name, public string name, column name is equals to price, public big decimal price, getters and settings. And in the in the provided hibernate entities, there are several issues regarding adherence to JP entity specifications. Incorrect annotations, the an uh, annotation add the rate add the rate entity seems to be a placeholder or typo. No. That is not correct. The correct annotation should be added to it entity, which has already been here. Missing annotations is not here. Okay. Okay. Naming dimension is also there are missing imports. I'm not able to see any imports. So add the identity. Column name should be, like, uh, without the oblique part. Oblique is not there should not be there, but it's written. And and and there is there are no, uh, at the rate, uh, getters and at the rate setters annotations. So I'll explain each entity what it does. Add the rate entity marks the class as a JP entity. Add the rate ID marks the ID field as the primary key. At the red generated value specifies how the primary key is generated. At the red column specifies the mapping of database column for the name and price fields.

How would you design a Hibernate-based persistence layer that enforces strong consistency and isolation levels in concurrent transactions? To design a Hibernate-based persistence layer that enforces strong consistency and isolation levels in concurrent transactions, we can follow the following steps which I will be providing you. First step, we can choose proper isolations level, like we can select an appropriate isolation level for transaction based on your application requirement, like common isolations level include read underscore committed, repeatable underscore read, and serializable. Higher isolation levels provide stronger consistency guarantees but may impact performance due to increased blocking. And secondly, we can perform, we can use optimistic concurrency control, which implement optimistic concurrency control to handle concurrent transaction without blocking. So this approach allows multiple transactions to proceed concurrently and detects conflicts at the time of commit. We can use versioning or time-stamping to track changes to entities and detect conflicts during updates. We can handle transactions explicitly, like we can explicitly manage transactions using springs at the rate transactional annotations, annotation or Hibernate's transactional API. We can ensure the transactions are properly committed or rolled back to maintain consistency. We can avoid long running transactions, we need to keep transactions short-lived to minimize the risk of conflicts and improve concurrency, avoid holding database locks for extending periods to prevent blocking other transactions. We can optimize fetching strategies, like we can use appropriate fetching strategies to minimize the duration of database locks, fetch only the necessary data within the transaction to reduce contention and improve concurrency, consider lazy loading for associations that are not immediately needed to avoid unnecessary data retrieval. We can implement data validations and integrity constraints, enforce data validation rules, integrity constraints at the application level to ensure consistent data storage, leverage Hibernate's validations, annotations at the right north null, at the right sides, etc. and database constraints, like primary key, foreign key, unique constraints and enforce data consistency. We can use database locking appropriately, use primistic locking when necessary to enforce strict consistency requirements, however, be cautious as it may lead to contention and reduce concurrency. Consider using selective locking to minimize the scope of locks and avoid unnecessary contentions and we can handle exceptions gracefully, implement error handling, we can implement error handling and retry mechanism to handle transactional failures gracefully, roll back transactions in case of errors to maintain consistency and integrity. We can test concurrency and consistency, we can write comprehensive tests to validate the behavior of concurrent transactions. We can use tools like springs, add delay, dirties, context to simulate concurrent access and verify consistency and isolation levels.

How would you apply HTML 5 semantic elements to enhance the structure and accessibility of a spring MVC web application? How would you apply HTML 5 semantic elements to enhance the structure and accessibility of a spring and you see web application? Okay Uh, to and, uh, to enhance structure and accessibility of a spaCymbic web application using the stream of 5 semantic elements, uh, we can use, uh, we can replace directives and spans with domestic stream of 5 elements such as header, nav, main article section, side, footer, etcetera. Semantic elements provide meaningful structure to your web pages, making it easier to screen readers and search engines to understand content. We can structure layout with selections. We can use header for the top sections of your page containing logo site navigations and other introduced content. We can utilize now for navigations menu. We can use main to inspect, like, the main content of the page, etcetera etcetera. We can utilize article for self contained content that could be distributed and reused independently, such as blog posts and comments.

What approaches can you use to optimize JavaScript execution in a spring boot application serving dynamic web content. So to optimize JavaScript execution in a spring boot application serving dynamic web content, we can use magnification. We can minify JavaScript files to reduce their size by removing white space, comments, and unnecessary characters, which can reduce the amount of data transferred over the network improvement improve improving page load times. We can use tool like Ubify JS, Tercer, or Google Closure Compiler to minify JavaScript's files as part of your or our build process. We can concatenate multiple JavaScript files into a single file reduced to the number of HTTP requests required to fetch resources. This can improve, uh, loading time by reducing overhead associated with multiple requests. We can use build tools like the background or gulp to concatenate JavaScript style into bundles. There are many other in in like, an asynchronous loading, caching, optimized frameworks, and libraries, code optimizations, tree shaking, server side rendering SSR.