Top 20 AWS Cloud9 Interview Questions and Answers

                AWS Cloud9 is a browser-based integrated development environment (IDE) that allows you to write, run, and debug code. A code editor, debugger, and terminal are all included. Cloud9 is pre-installed with key tools for major programming languages such as JavaScript, Python, PHP, and more, so you don't have to install files or setup your development workstation to get started. Because your Cloud9 IDE is cloud-based, you may work on your projects from any internet-connected machine, including your office, home, or anyplace else. Cloud9 also offers a smooth development experience for serverless apps, allowing you to simply define resources, debug, and switch between local and remote execution. You can share your development environment with your team fast with Cloud9, allowing you to pair programme and track each other's inputs in real time.

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Ques. 1): How can I begin using AWS Cloud9?

Answer:

You can choose AWS Cloud9 from the AWS Management Console after logging in. The console will walk you through the options for choosing a Linux server to connect to Cloud9. In a few simple steps, you may either create a new Amazon EC2 instance (AWS Cloud9 EC2 environment) or connect your current Linux server (AWS Cloud9 SSH environment). You may access your IDE and write code in a fully configured development environment once you've created a Cloud9 environment.

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Ques. 2): Who should utilise Amazon Web Services Cloud9?

Answer:

AWS Cloud9 is available to everyone who writes code. Cloud9 provides instant access to a fully configured development environment in their browsers with preloaded runtimes, package managers, and debugging tools for those developing apps in Node.js (JavaScript), Python, PHP, Ruby, Go, and C++. Cloud9 allows you to access your work environment from any internet-connected computer, removing the need for a dedicated development machine.

AWS Cloud9 provides convenient access to their AWS resources via a preset AWS Command Line Interface (AWS CLI), ready to perform commands against AWS services, for AWS developers and those assessing new AWS services. Cloud9 has built-in tools for creating, editing, running, debugging, and deploying Lambda functions for those developing serverless apps on AWS Lambda using Node.js or Python.

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Ques. 3): What kinds of AWS Cloud9 development environments are there?

Answer:

You can use one of two types of AWS Cloud9 setups.

AWS Cloud9 EC2 environment — Allows you to create a new Amazon EC2 instance with Cloud9. These instances are set to terminate 30 minutes after you close the IDE and start immediately when you open it.

SSH environment on AWS Cloud9 — Allows you to join an existing Linux server to Cloud9. On the Linux server that you intend to use with Cloud9 SSH environments, certain requirements are required.

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Ques. 4): What is AWS Cloud9, exactly?

Answer:

AWS Cloud9 is a browser-based integrated development environment (IDE) that allows you to write, run, and debug code. It combines code completion, hinting, and step-through debugging with access to a full Linux server for running and storing code.

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Ques. 5): How can I execute my code?

Answer:

The AWS Cloud9 IDE has a run button in the toolbar as well as built-in runners for over 10 languages that will immediately start your application with the most recent code modifications. You can also alter current runners, develop your own runners, or run your code from the terminal if you want complete control over how your product is run.

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Ques. 6): How much does AWS Cloud9 cost?

Answer:

AWS Cloud9 comes at no additional cost. You only pay for the compute and storage resources (i.e., an EC2 instance, an EBS volume) that are utilised to run and store your code if you use an Amazon EC2 instance for your AWS Cloud9 development environment. For no additional price, you can connect your Cloud9 development environment to an existing Linux server (e.g., on-premises server) through SSH.

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Ques. 7): What is the best way to use AWS Cloud9 with AWS CodeStar?

Answer:

You can start modifying and committing your CodeStar project code in the Cloud9 IDE right away after launching AWS Cloud9 environments from AWS CodeStar. Any code changes you commit to your project source repository from Cloud9 are compiled and deployed automatically using CodeStar's tools.

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Ques. 8): What resources does AWS Cloud9 create for Amazon EC2 environments?

Answer:

AWS Cloud9 creates the needed computation and storage resources in your AWS account when you create an Amazon EC2 environment. An Amazon EC2 instance, an Amazon Elastic Block Store (EBS) volume of 8 GB, an Amazon EC2 security group, and an AWS CloudFormation stack are among the resources. These resources are accessible through the different AWS service consoles. Cloud9 automatically deletes these resources when you erase your environment.

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Ques. 9): What is the location of my code on AWS Cloud9?

Answer:

Code files, packages, and dependencies are all kept in your resources in your AWS Cloud9 environment. Your data is stored in the appropriate Amazon Elastic Block Store (EBS) volume in your AWS account if you use an EC2 environment. Your data is saved locally on your Linux server if you use an SSH environment.

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Ques. 10): How can I use AWS Cloud9 to construct serverless applications for AWS Lambda?

Answer:

The AWS Resources panel in the IDE contains the built-in tools for AWS Lambda. These utilities can be used to import or generate Lambda functions in Node.js and Python. These routines can be quickly launched, previewed, debugged, and deployed right from the IDE. The AWS Serverless Application Model (AWS SAM) framework is also supported by AWS Cloud9. You may now handle many Lambda functions and serverless resources in your application with ease. If you used AWS CodeStar to provide your project, any changes you make to it will be built and sent to Lambda using git push.

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Ques. 11): Is it possible to modify the instance type of an Amazon EC2 environment that already exists?

Answer:

Yes. With your AWS Cloud9 environment, you can change the Amazon EC2 instance type you previously selected. To do so, go to the EC2 console and locate your instance, then follow the procedures in the Amazon EC2 documentation.

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Ques. 12): Can I use AWS Cloud9 to test my AWS Lambda functions locally?

Answer:

Yes. AWS Cloud9 can run your Node.js and Python functions locally in the IDE, simulating the AWS Lambda execution environment. This allows you to step-through debug your serverless applications without having to upload your changes to Lambda. You may also deploy your application modifications to Lambda directly from the IDE once they've been tested.

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Ques. 13): What are the supported programming languages?

Answer:

Node.js (JavaScript), Python, PHP, Ruby, Go, and C++ are among the programming languages supported by AWS Cloud9. It supports several major programming languages and offers features including syntax highlighting, outline view, code hinting, code completion, application runners, and step-through debugging.

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Ques. 14): How do I make changes to my code?

Answer:

Auto-completion, code folding, hinting, syntax highlighting, and line manipulation are all included in the AWS Cloud9 IDE's powerful code editor. You can choose from over 30 colour schemes in the code editor to manage syntax highlighting and the UI. You may also update your CSS to completely personalise the Cloud9 UI.

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Ques. 15): Is AWS Cloud9 capable of managing resources developed in Amazon EC2 environments?

Answer:

Cloud9 can not only create and delete your AWS Cloud9 EC2 environment resources on your behalf, but it can also start and stop the EC2 instances automatically to save you money. All other administration chores on these resources are your responsibility, including installing software patches on your EC2 instances and backing up your EBS volumes.

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Ques. 16): How do I access AWS services from AWS Cloud9?

Answer:

AWS Cloud9 EC2 environments come preinstalled with the AWS CLI, which is authenticated with the permissions of the logged-in AWS user automatically. This enables you to run interactive CLI commands against AWS services from the built-in terminal window in Cloud9 without any additional configuration.

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Ques. 17): In AWS Cloud9 environments, are my Amazon EC2 instances always active?

Answer:

No. For Amazon EC2 instances created with AWS Cloud9, the default auto-hibernation option is 30 minutes. Your EC2 instances will automatically halt 30 minutes after you close the IDE and resume only when you reopen it with this option. As a result, EC2 instance charges are often only incurred when you are actively working. When your instance needs to be restarted, you lose any open terminal sessions in the IDE and may have to wait a bit to open it. You can modify the auto-hibernation setting and even choose to keep your EC2 instance "always on" depending on your use case.

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Ques. 18): On AWS Cloud9 EC2 setups, what tools and packages are preinstalled?

Answer:

AWS Cloud9 EC2 setups provide popular development tools like Git and Docker preinstalled. Many popular programming languages, such as Node.js and Python, have language runtimes and package managers.

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Ques. 19): What is the best way to share my AWS Cloud9 installation with others?

Answer:

Click the Share button in the top right corner of your IDE to share your AWS Cloud9 environment. The AWS Identity and Access Management (IAM) user name and desired access levels for the individual with whom you want to collaborate are requested. Once you've entered these details, both participants can use the environment for real-time collaboration on IDE features and command line sessions.

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Ques. 20): What are the steps for connecting to source control management systems?

Answer:

You may use the same command line tools on your local PC to access your source control system by opening the terminal window within the IDE. Git is preinstalled on AWS Cloud9 EC2 environments, making it easy to retrieve your source code.

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Top 20 Amazon Athena Interview Questions and Answers

 

        Amazon Athena is an interactive query service that makes it simple to use normal SQL to evaluate data in Amazon S3. Because Athena is serverless, you don't have to worry about maintaining infrastructure, and you just pay for the queries you run.

Athena is simple to operate. Simply point to your Amazon S3 data, define the schema, and begin querying using regular SQL. The majority of results arrive in seconds. There's no need for complicated ETL procedures to prepare your data for analysis with Athena. This makes it simple for anyone with SQL expertise to study massive datasets fast.

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Ques. 1): What is Amazon Athena all about?

Answer:

Amazon Athena is an interactive query service that makes it simple to use normal SQL to evaluate data in Amazon S3. Because Athena is serverless, there is no infrastructure to set up or operate, and you can immediately begin analysing data. You don't even have to load your data into Athena; it works with S3 data immediately. Simply log into the Athena Management Console, create your schema, and begin querying. Amazon Athena works with a range of standard data formats, including CSV, JSON, ORC, Apache Parquet, and Avro, and leverages Presto with full SQL support. While Amazon Athena is great for interactive analytics and interacts with Amazon QuickSight for quick visualisation, it's not the most user-friendly platform. it can also handle complex analysis, including large joins, window functions, and arrays.

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Ques. 2): What makes Amazon Athena, Amazon EMR, and Amazon Redshift different?

Answer:

Different demands and use cases are addressed by query services like Amazon Athena, data warehouses like Amazon Redshift, and advanced data processing frameworks like Amazon EMR. All you have to do now is pick the correct tool for the job. For enterprise reporting and business intelligence workloads, Amazon Redshift provides the fastest query performance, especially for those utilising extremely sophisticated SQL with numerous joins and sub-queries. When compared to on-premises deployments, Amazon EMR makes running highly distributed processing frameworks like Hadoop, Spark, and Presto straightforward and cost effective. You can execute bespoke apps and code on Amazon EMR, as well as configure particular computing, memory, storage, and application parameters to maximise your analytic needs. Amazon Athena makes it simple to execute interactive queries over S3 data without having to set up or manage any servers.

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Ques. 3): When should I utilise Amazon EMR and when should I use Amazon Athena?

Answer:

Amazon EMR is capable of much more than just conducting SQL queries. You can use EMR to conduct a variety of scale-out data processing activities for applications like machine learning, graph analytics, data transformation, streaming data, and almost anything else you can think of. If you utilise custom code to handle and analyse extremely huge datasets with the latest big data processing frameworks like Spark, Hadoop, Presto, or Hbase, you should use Amazon EMR. Amazon EMR allows you complete control over the configuration and applications installed on your clusters.

If you want to conduct interactive SQL queries against data on Amazon S3 without having to manage any infrastructure or clusters, you should utilise Amazon Athena.

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Ques. 4): What data formats is Amazon Athena compatible with?

Answer:

Amazon Athena can handle a wide range of data formats, including CSV, TSV, JSON, and Textfiles, as well as open source columnar formats like Apache ORC and Apache Parquet. Snappy, Zlib, LZO, and GZIP compressed data formats are also supported by Athena. You can increase speed and lower costs by compressing, dividing, and adopting columnar formats.

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Ques. 5): I'm getting data from Kinesis Firehose. How can I use Athena to query it?

Answer:

You can use Amazon Athena to query your Kinesis Firehose data if it's hosted on Amazon S3. Simply construct an Athena schema for your data and begin querying. To improve efficiency, we recommend dividing the data into parts. ALTER TABLE DDL instructions can be used to add partitions produced by Kinesis Firehose. Get more information on partitions.

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Ques. 6): How can I make my query perform better?

Answer:

By compressing, splitting, or turning your data into columnar formats, you can increase the performance of your query. Apache Parquet and Apache ORC are two open source columnar data formats that Amazon Athena supports. By allowing Athena to scan less data from S3 when executing your query, converting your data into a compressed, columnar format minimizes your costs and increases query performance.

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Ques. 7): What is a federated query, exactly?

Answer:

If you have data in places other than Amazon S3, you may use Athena to query it or create pipelines to extract data from numerous sources and put it in Amazon S3. You can perform SQL queries against data stored in relational, non-relational, object, and custom data sources using Athena Federated Query.

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Ques. 8): Can I do ETL (Extract, Transform, Load) using federated queries?

Answer:

Athena stores query results in an Amazon S3 file. This means Athena may be used to make federated data accessible to other users and apps. Use Athena's CREATE TABLE AS function to perform analysis on the data without having to query the underlying source frequently. You may also query the data using Athena's UNLOAD function and save the results in a specific file format to Amazon S3.

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Ques. 9): What embedded ML use cases does Athena support?

Answer:

The following examples show how Athena can be used in a variety of sectors. What-if analysis and Monte Carlo simulations are available to financial risk data analysts. To aid in the creation of richer and forward-looking business dashboards that forecast revenues, business analysts may use linear regression or forecasting models to predict future values. K-means clustering methods could aid marketing analysts in determining their various client categories. Logical regression models could be used by security analysts to uncover abnormalities and detect security incidents in logs.

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Ques. 10): What capabilities does Athena ML have?

Answer:

Athena provides machine learning inference (prediction) capabilities using a SQL interface. You can also use an Athena UDF to perform pre- or post-processing logic on your result set. Multiple calls can be batched together for increased scalability, and inputs can be any column, record, or table. Inference can be performed during the Select or Filter phases.

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Ques. 11): Is Athena highly available?

Answer:

Yes. Amazon Athena is highly available, executing queries across many facilities and intelligently routing queries correctly if one of the facilities is unavailable. Athena's underlying data store is Amazon S3, which makes your data highly available and durable. Amazon S3 provides a reliable infrastructure for storing essential data, with 99.999999999 percent object durability. Your information is duplicated across numerous facilities and devices inside each facility.

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Ques. 12): What should I do to lower the costs?

Answer:

By compressing, splitting, and turning your data into columnar formats, you can save 30 percent to 90 percent on query costs while also improving performance. Each of these actions reduces the quantity of data that Amazon Athena must scan in order to complete a query. Apache Parquet and ORC, two of the most popular open-source columnar formats, are supported by Amazon Athena. On the Athena console, you can view how much data was scanned for each query.

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Ques. 13): Are there any other fees related with Amazon Athena?

Answer:

Your source data is invoiced at S3 rates because Amazon Athena queries data directly from Amazon S3. When you perform a query through Amazon Athena, the results are saved in an S3 bucket of your choosing, and you are charged at standard S3 rates for these result sets. We recommend that you keep an eye on these buckets and utilise lifecycle policies to limit how much data is kept.

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Ques. 14): Does the User Defined Functions (UDFs) are supported by Athena?

Answer:

User-defined functions (UDFs) in Amazon Athena allow you to create new scalar functions and utilise them in SQL queries. While Athena has built-in capabilities, UDFs allow you to conduct custom processing such as data compression and decompression, redaction of sensitive material, and bespoke decryption.

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Ques. 15): In Amazon Athena, how can I add new data to an existing table?

Answer:

If your data is partitioned, you'll need to run an ALTER TABLE ADD PARTITION metadata query to add the partition to Athena once new data is available on Amazon S3. If your data isn't partitioned, simply adding new data (or files) to an existing prefix will add them to Athena.

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Ques. 16): What exactly is a SerDe?

Answer:

Serializer/Deserializer are libraries that teach Hive how to understand different data formats. You must mention a SerDe in Hive DDL statements so that the system knows how to interpret the data you're pointing to. SerDes is used by Amazon Athena to analyse data read from Amazon S3. SerDes is the same notion in Athena as it is in Hive. The following SerDes are supported by Amazon Athena:

Apache Web Logs: "org.apache.hadoop.hive.serde2.RegexSerDe"

CSV: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe"

TSV: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe"

Custom Delimiters: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe"

Parquet: "org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe"

Orc: "org.apache.hadoop.hive.ql.io.orc.OrcSerde"

JSON: “org.apache.hive.hcatalog.data.JsonSerDe” OR org.openx.data.jsonserde.JsonSerDe

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Ques. 17): Can I query data processed with Amazon EMR using Amazon Athena?

Answer:

Yes, Amazon Athena and Amazon EMR both support many of the same data formats. The Athena data catalogue is compatible with the Hive metastore. If you're utilising EMR and already have a Hive metastore, you can query your data straight away without affecting your Amazon EMR operations by executing your DDL statements on Amazon Athena.

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Ques. 18): How are table definitions and schema stored in Amazon Athena?

Answer:

To keep information and schemas about the databases and tables you create for your data saved in Amazon S3, Amazon Athena employs a managed Data Catalog. You can use the AWS Glue Data Catalog with Amazon Athena in regions where AWS Glue is accessible. Athena uses an internal Catalog in regions where AWS Glue is not available.

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The catalogue can be modified using DDL statements or the AWS Management Console. Unless you delete them directly, any schemas you define are automatically stored. Athena leverages schema-on-read technology, which means that when queries are run, your table definitions are applied to your data on S3. There’s no data loading or transformation required. You can delete table definitions and schema without impacting the underlying data stored on Amazon S3.

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Ques. 19): Can I use Athena to run any Hive query?

Answer:

Hive is only used by Amazon Athena for DDL (Data Definition Language) and for creating, modifying, and deleting tables and partitions. For a complete list of statements that are supported, please check here. When you run SQL queries on Amazon S3, Athena uses Presto. To query your data in Amazon S3, you can use ANSI-Compliant SQL SELECT queries.

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Ques. 20): Is data partitioning possible with Amazon Athena?

Answer:

Yes. You can segment your data on any column with Amazon Athena. Partitions reduce the quantity of data scanned by each query, resulting in cost savings and faster performance. The PARTITIONED BY clause in the CREATE TABLE statement allows you to specify your partitioning plan.  

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Ques. 21): What is the purpose of data source connectors?

Answer:

A data source connector is a piece of AWS Lambda code that bridges the gap between your target data source and Athena. You can conduct SQL queries on federated data stores after using a data source connector to register a data store with Athena. When a query is conducted on a federated source, Athena invokes the Lambda function, which is tasked with executing the parts of your query that are unique to the federated source.

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Top 20 C# Language Interview Questions and Answers

  

        Microsoft's C# is an object-oriented programming language. The.NET framework uses C# to create websites, applications, and games. C# is popular for a variety of reasons. C# is described as being easier to learn than other programming languages. You're more likely to construct online applications or gaming apps with C#. Automatic garbage collection, interfaces, and other features in C# enable developers create better apps.

Collaboration with Microsoft gives C# applications an advantage since they can reach a broader audience. Because C# is such a popular programming language, many large and small businesses utilise it to build their products. So, to ace the interviews, prepare yourself with basic and advanced level C# questions.

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Ques. 1): Is it possible to run several catch blocks?

Answer:

No, you cannot execute multiple catch blocks of the same type. Control is handed to the finally block after the correct catch code has been completed, and then the code that follows the finally block is executed.

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Ques. 2): What exactly are the distinctions between public, static, and void?

Answer:

Anywhere in the application, public stated variables or methods are accessible. Without generating an instance of the class, static declared variables or methods are globally available. The type of access modification used determines whether or not static members are globally available by default. The method's address is saved as the entry point, and the compiler utilises this information to start execution before any objects are generated. And Void is a type modifier that indicates that the method or variable returns nothing.

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Ques. 3): In C#, what is garbage collection?

Answer:

Garbage collection is the process of releasing memory held by undesirable things. When you create a class object, some heap memory space is automatically allocated to the object. After you've completed all of the activities on the item, the memory space it takes up becomes wasted. Memory must be made available. Garbage collection occurs in three situations:

• If the occupied memory by the objects exceeds the pre-set threshold value.
• If the garbage collection method is called
• If your system has low physical memory

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Ques. 4): Define Constructors in  C#.

Answer:

A function Object() { [native code] } is a member function that has the same name as the class it belongs to. When an object class is created, the function Object() { [native code] } is called automatically. While initialising the class, it constructs the values of data members.

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Ques. 5): What exactly are Jagged Arrays?

Answer:

The array with array elements is known as a jagged array. The elements can be of various shapes and sizes. An Array of arrays is another name for jagged Array.

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Ques. 6): What is the difference between Custom Control and User Control?

Answer:

Custom Controls are compiled code (Dll) controls that are easier to use and may be added to the toolbox. Developers can add controls to their web forms by dragging and dropping them. At design time, attributes can be used. Custom controls can be simply added to multiple applications (If Shared Dlls). If they are private, we can copy the dll to the web application's bin directory, add a reference, and use them.

User Controls are comparable to ASP include files in that they are simple to construct. It is not possible to drag and drop user controls into the toolbox. They have their own code and design. Ascx is the file extension for user controls.

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Ques. 7): What’s the difference between the Array.CopyTo() and Array.Clone()?

Answer:

The Clone() method copies an array shallowly. A shallow copy of an Array duplicates only the elements of the Array, regardless of whether they are reference or value types, but not the objects to which the references link. The references in the new Array point to the same objects as the previous Array's references.

The Array class's CopyTo() static function copies a piece of one array to another array. The CopyTo method transfers all of an array's items to a new one-dimensional array. Listing 9 shows how to copy the contents of an integer array to an array of object types.

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Ques. 8): In C#, what are the different types  of classes?

Answer:

A class is a logical unit that contains all of the properties of its objects and instances. There are four sorts of such classes in C#:

Static type: The keyword'static' defines a class that does not allow inheritance. As a result, you won't be able to construct an object for a static class.

static class classname 

{ 

  //static data members 

  //static methods 

}

Partial class: Partially divided or shared source (.cs) files are possible with the partial class, which is defined by the term 'partial.'

Abstract class: Abstract classes are classes that cannot be instantiated and cannot be used to construct objects. Abstract classes are based on the OOPS abstraction idea. Abstraction aids in separating important details from those that aren't.

Sealed class: A sealed class is one that can't be inherited. To prevent users from inheriting that class, use the keyword sealed.

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Ques. 9): What is IEnumerable<> in C#?

Answer:

 IEnumerable is the parent interface for all non-generic collections in System.Collections namespace like ArrayList, HastTable etc. that can be enumerated. For the generic version of this interface as IEnumerable<T> which a parent interface of all generic collections class in System.Collections.Generic namespace like List<> and more.

 In System.Collections.Generic.IEnumerable<T> have only a single method which is GetEnumerator() that returns an IEnumerator. IEnumerator provides the power to iterate through the collection by exposing a Current property and Move Next and Reset methods if we don’t have this interface as a parent so we can’t use iteration by foreach loop or can’t use that class object in our LINQ query.

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Ques. 10): In C#, what are extension methods? How may extension techniques be used?

Answer:

Extension methods allow you to add methods to existing types without having to create a new derived type, recompile it, or modify it in any way.

An extension method is a form of static method that is referred to as if it were an instance method on the extended type.

A static method of a static class with the "this" modifier appended to the first parameter is called an extension method. The extended type will be the type of the first parameter.

Extension methods are only in scope if you use a using directive to explicitly import the namespace into your source code.

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Ques. 11): What makes the System.String and System.Text.StringBuilder classes different?

Answer:

System.Strings are unchangeable. When we change the value of a string variable, the existing memory allocation is released and fresh memory is allocated to the new value. System. StringBuilder was created with the idea of a mutable string that can be used for a number of operations without requiring a separate memory address for the updated string.

Ques. 12): What are Generics in C#?

Answer:

In C# collections, defining any kind of object is termed okay which compromises C#’s basic rule of type-safety. Therefore, generics were included to type-safe the code by allowing re-use of the data processing algorithms. Generics in C# mean not linked to any specific data type. Generics reduce the load of using boxing, unboxing, and typecasting objects. Generics are always defined inside angular brackets <>. To create a generic class, this syntax is used:

GenericList<float> list1 = new GenericList<float>();

GenericList<Features> list2 = new GenericList<Features>();

GenericList<Struct> list3 = new GenericList<Struct>();

Here, GenericList<float> is a generic class. In each of these instances of GenericList<T>, every occurrence of T in the class is substituted at run time with the type argument. By substituting the T, we have created three different type-safe using the same class.

 

Ques. 13): In C#, how do you tell the difference between boxing and unboxing?

Answer:

Both boxing and unboxing are used to convert types, however they have some differences:

Boxing: Boxing is the conversion of a value type data type to an object or any interface data type that this value type implements. When the CLR converts a value type to an Object Type, it wraps the value in a System.Object and stores it in the application domain's heap region.

 

Unboxing: Unboxing is a technique for determining the value type of an object or any implemented interface type. Unboxing, on the other hand, must be done explicitly via code.

 The concept of boxing and unboxing underlies the C# unified view of the type system in which a value of any type can be treated as an object.

 

Ques. 14): What is the difference between a struct and a class in C#?

Answer:

Class and struct are both user-defined data types, but have some major differences:

Struct

• The struct is a value type in C# and it inherits from System.Value Type.
• Struct is usually used for smaller amounts of data.
• Struct can’t be inherited from other types.
• A structure can't be abstract.
• No need to create an object with a new keyword.
• Do not have permission to create any default constructor.

Class

• The class is a reference type in C# and it inherits from the System.Object Type.
• Classes are usually used for large amounts of data.
• Classes can be inherited from other classes.
• A class can be an abstract type.
• We can create a default constructor.

 

Ques. 15): What is the difference between the dispose and finalize methods in C#?

Answer:

Both finalise and dispose are strategies for releasing unmanaged resources.

 Finalize: 

• Finalize is used to liberate unmanaged resources in the application domain that are no longer in use, such as files and database connections.
• These are the resources that an object has before it is destroyed. Garbage Collector calls it in the internal process, and no user code or service can call it manual.
• Finalize belongs to System.Object class.
• When your code contains unmanaged resources, use it to ensure that these resources are removed when garbage collection occurs.

Dispose: 

• Dispose can also be used to liberate unmanaged resources in the Application domain, such as files and database connections, at any time.
• Manual user code directly calls dispose.
• We must implement the disposal method via the IDisposable interface if we want to use it.
• It's a part of the IDisposable interface.
• When building a custom class that will be used by other users, remember to include this.

 

Ques. 16): In C#, what is the difference between late and early binding?

Answer:

One of the key concepts of OOPS is polymorphism, which includes late binding and early binding.

For example, one function calculateBill() will calculate premium, basic, and semi-premium clients' bills differently depending on their plans. The calculations for all of the customer objects are done differently using the same polymorphism function.

The.NET framework conducts the binding when an object is allocated to an object variable in C#.

Early binding occurs when the binding function is performed at build time. It investigates and tests the static objects' methods and properties. The amount of run-time mistakes is significantly reduced with early binding, and it executes swiftly.

Late binding, on the other hand, occurs when the binding occurs at runtime. Late binding occurs when run-time objects are dynamic (determined by the data they contain). It's slower because it's looking through during the process.

 

Ques. 17): Is it possible to utilise "this" inside a static method?

Answer:

Because the keyword 'this' returns a reference to the current instance of the class containing it, we can't use it in a static method. Static methods (or any other static element) are not associated with a specific instance. We can't use this keyword in the body of static Methods since they exist without creating an instance of the class and are called with the name of the class, not by instance. In the case of Extension Methods, however, we can use the function's parameters.

Let's take a look at the keyword "this."

The "this" keyword in C# is a particular form of reference variable that is implicitly defined as the first parameter of the type class in which it is specified within each function Object() { [native code] } and non-static function.

 

Ques. 18): What are delegates in C# and how do you utilise them?

Answer:

A Delegate is an abstraction of one or more function pointers (as in C++; a detailed explanation is beyond the scope of this article). The concept of function pointers has been implemented in the form of delegates in.NET. You can use delegates to treat a function like data. Functions can be supplied as parameters, returned as a value, and saved in an array using delegates. The following are qualities of delegates:

• Delegates are derived from the System.MulticastDelegate class.
• They have a signature and a return type. A function that is added to delegates must be compatible with this signature.
• Delegates can point to either static or instance methods.
• Once a delegate object has been created, it may dynamically invoke the methods it points to at runtime.
• Delegates can call methods synchronously and asynchronously.

There are a few useful fields in the delegate. The first has an object reference, whereas the second contains a method pointer. The instance method on the contained reference is called when you call the delegate. If the object reference is nil, however, the runtime interprets this to suggest that the method is static. Furthermore, calling a delegate is syntactically identical to calling a regular function. Delegates are thus ideal for implementing callbacks.

 

Ques. 19): In C#, describe accessibility modifiers. Why should you use access modifiers?

Answer:

Access modifiers are keywords that specify a member's or type's declared accessibility.

Access modifiers are keywords that describe the accessibility of a type member or the type itself. A public class, for example, is open to the entire world, whereas an internal class is only open to the assembly.

Object-oriented programming relies heavily on access modifiers. To implement OOP encapsulation, access modifiers are utilised. You can use access modifiers to control who has and doesn't have access to particular functionalities.

In C# there are 6 different types of Access Modifiers:

public:    There are no restrictions on accessing public members.

Private:    Access is limited to within the class definition. This is the default access modifier type if none is formally specified

protected:    Access is limited to within the class definition and any class that inherits from the class

internal:    Access is limited exclusively to classes defined within the current project assembly

protected internal:    Access is limited to the current assembly and types derived from the containing class. All members in the current project and all members in derived class can access the variables.

private protected:    Access is limited to the containing class or types derived from the containing class within the current assembly.

 

Ques. 20): In C#, how do you use the using statement?

Answer:

The using keyword in C# can be used in two ways. One is in the form of a mandate, while the other is in the form of a statement. Let me clarify!

using Directive:

In code-behind and class files, we usually utilise the using keyword to add namespaces. Then it makes all the classes, interfaces, and abstract classes on the current page, as well as their methods and properties, available.

Using Statement :

Another approach to utilise the using keyword in C# is as follows. It is critical to enhance garbage collection performance.