47 Back-End Developer Interview Questions (ANSWERED) To Focus On

The CAP Theorem for distributed computing was published by Eric Brewer. This states that it is not possible for a distributed computer system to simultaneously provide all three of the following guarantees:

1. Consistency (all nodes see the same data even at the same time with concurrent updates )
2. Availability (a guarantee that every request receives a response about whether it was successful or failed)
3. Partition tolerance (the system continues to operate despite arbitrary message loss or failure of part of the system)

The CAP acronym corresponds to these three guarantees. This theorem has created the base for modern distributed computing approaches. Worlds most high volume traffic companies (e.g. Amazon, Google, Facebook) use this as basis for deciding their application architecture. It's important to understand that only two of these three conditions can be guaranteed to be met by a system.

REST stands for REpresentational State Transfer. REST is web standards based architecture and uses HTTP Protocol for data communication. It revolves around resource where every component is a resource and a resource is accessed by a common interface using HTTP standard methods. REST was first introduced by Roy Fielding in 2000.

In REST architecture, a REST Server simply provides access to resources and REST client accesses and presents the resources. Here each resource is identified by URIs/ global IDs. REST uses various representations to represent a resource like text, JSON and XML. Now a days JSON is the most popular format being used in web services.

A NoSQL database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases (like SQL, Oracle, etc.).

Types of NoSQL databases:

• Document Oriented
• Key Value
• Graph
• Column Oriented

At the present time, the internet is loaded with big data, big users, big complexity etc. and also becoming more complex day by day. NoSQL is answer of all these problems; It is not a traditional database management system, not even a relational database management system (RDBMS). NoSQL stands for “Not Only SQL”. NoSQL is a type of database that can handle and sort all type of unstructured, messy and complicated data. It is just a new way to think about the database.

Injection attacks stem from a lack of strict separation between program instructions (i.e., code) and user-provided (or external) input. This allows an attacker to inject malicious code into a data snippet.

SQL injection is one of the most common types of injection attack. To carry it out, an attacker provides malicious SQL statements through the application.

How to prevent:

• Prepared statements with parameterized queries
• Stored procedures
• Input validation - blacklist validation and whitelist validation
• Principle of least privilege - Application accounts shouldn’t assign DBA or admin type access onto the database server. This ensures that if an application is compromised, an attacker won’t have the rights to the database through the compromised application.

Continuous Integration (CI) is a development practice that requires developers to integrate code into a shared repository several times a day. Each check-in is then verified by an automated build, allowing teams to detect problems early.

To mitigate SQL injection:

• Prepared Statements with Parameterized Queries: Always ensure that your SQL interpreter always able to differentiate between code and data. Never use dynamic queries which fail to find the difference between code and data. Instead, use static SQL query and then pass in the external input as a parameter to query.  Use of Prepared Statements (with Parameterized Queries) force developer to first define all the SQL code, and then pass in each parameter to the query later.
• Use of Stored Procedures: Stored Procedure is like a function in C where database administrator call it whenever he/she need it. It is not completely mitigated SQL injection but definitely helps in reducing risks of SQL injection by avoiding dynamic SQL generation inside.
• White List Input Validation: Always use white list input validation and allow only preapproved input by the developer. Never use blacklist approach as it is less secure than whitelist approach.
• Escaping All User Supplied Input
• Enforcing Least Privilege

Some of the performance testing steps are:

• Identify the testing environment
• Identify performance metrics
• Plan and design performance tests
• Configure the test environment
• Implement your test design
• Execute tests
• Analyze, report, retest

• Functional testing: This is a verification activity; did we build a correctly working product? Does the software meet the business requirements? A functional test verifies that the product actually works as you (the developer) think it does.

• Acceptance testing: This is a validation activity; did we build the right thing? Is this what the customer really needs? Acceptance tests verify the product actually solves the problem it was made to solve. This can best be done by the user (customer), for instance performing his/her tasks that the software assists with.

Go is an attempt to introduce a new, concurrent, garbage-collected language with fast compilation and the following benefits:

• It is possible to compile a large Go program in a few seconds on a single computer.
• Go provides a model for software construction that makes dependency analysis easy and avoids much of the overhead of C-style include files and libraries.
• Go's type system has no hierarchy, so no time is spent defining the relationships between types. Also, although Go has static types, the language attempts to make types feel lighter weight than in typical OO languages.
• Go is fully garbage-collected and provides fundamental support for concurrent execution and communication.
• By its design, Go proposes an approach for the construction of system software on multicore machines.

Some of the advantages of web services are:

• Interoperability: Web services are accessible over network and runs on HTTP/SOAP protocol and uses XML/JSON to transport data, hence it can be developed in any programming language. Web service can be written in java programming and client can be PHP and vice versa.
• Reusability: One web service can be used by many client applications at the same time.
• Loose Coupling: Web services client code is totally independent with server code, so we have achieved loose coupling in our application.
• Easy to deploy and integrate, just like web applications.
• Multiple service versions can be running at same time.

Following are the benefits of using Go programming:

• Support for environment adopting patterns similar to dynamic languages. For example type inference (x := 0 is valid declaration of a variable x of type int).
• Compilation time is fast.
• In built concurrency support: light-weight processes (via goroutines), channels, select statement.
• Conciseness, Simplicity, and Safety.
• Support for Interfaces and Type embedding.
• The go compiler supports static linking. All the go code can be statically linked into one big fat binary and it can be deployed in cloud servers easily without worrying about dependencies.

Containerisation is a type of virtualization strategy that emerged as an alternative to traditional hypervisor-based virtualization.

In containerization, the operating system is shared by the different containers rather than cloned for each virtual machine. For example Docker provides a container virtualization platform that serves as a good alternative to hypervisor-based arrangements.

There are plenty of pros that are offered by Microservices architecture. Here are a few of them:

• Microservices can adapt easily to other frameworks or technologies.
• Failure of a single process does not affect the entire system.
• Provides support to big enterprises as well as small teams.
• Can be deployed independently and in relatively less time.

• Test as early as possible in development.
• Conduct multiple performance tests to ensure consistent findings and determine metrics averages.
• Test the individual software units separately as well as together
• Baseline measurements provide a starting point for determining success or failure
• Performance tests are best conducted in test environments that are as close to the production systems as possible
• Isolate the performance test environment from the environment used for quality assurance testing
• Keep the test environment as consistent as possible
• Calculating averages will deliver actionable metrics. There is value in tracking outliers also. Those extreme measurements could reveal possible failures.

Availability means the ability of the application user to access the system, If a user cannot access the application, it is assumed unavailable. High Availability means the application will be available, without interruption. Using redundant server nodes with clustering is a common way to achieve higher level of availability in web applications.

Availability is commonly expressed as a percentage of uptime in a given year.

ACID is a acronym which is commonly used to define the properties of a relational database system, it stand for following terms

• Atomicity - This property guarantees that if one part of the transaction fails, the entire transaction will fail, and the database state will be left unchanged.
• Consistency - This property ensures that any transaction will bring the database from one valid state to another.
• Isolation - This property ensures that the concurrent execution of transactions results in a system state that would be obtained if transactions were executed serially.
• Durable - means that once a transaction has been committed, it will remain so, even in the event of power loss.

Sticky session or a session affinity technique is another popular load balancing technique that requires a user session to be always served by an allocated machine.

In a load balanced server application where user information is stored in session it will be required to keep the session data available to all machines. This can be avoided by always serving a particular user session request from one machine. The machine is associated with a session as soon as the session is created. All the requests in a particular session are always redirected to the associated machine. This ensures the user data is only at one machine and load is also shared.

This is typically done by using SessionId cookie. The cookie is sent to the client for the first request and every subsequent request by client must be containing that same cookie to identify the session.

What Are The Issues With Sticky Session?

There are few issues that you may face with this approach

• The client browser may not support cookies, and your load balancer will not be able to identify if a request belongs to a session. This may cause strange behavior for the users who use no cookie based browsers.
• In case one of the machine fails or goes down, the user information (served by that machine) will be lost and there will be no way to recover user session.

Some of the disadvantages of REST are:

• Since there is no contract defined between service and client, it has to be communicated through other means such as documentation or emails.
• Since it works on HTTP, there can’t be asynchronous calls.
• Sessions can’t be maintained.

In software engineering, Don't Repeat Yourself (DRY) or Duplication is Evil (DIE) is a principle of software development.

• With a Clustered index the rows are stored physically on the disk in the same order as the index. Therefore, there can be only one clustered index. A clustered index means you are telling the database to store close values actually close to one another on the disk.
• With a Non Clustered index there is a second list that has pointers to the physical rows. You can have many non clustered indices, although each new index will increase the time it takes to write new records.
• It is generally faster to read from a clustered index if you want to get back all the columns. You do not have to go first to the index and then to the table.
• Writing to a table with a clustered index can be slower, if there is a need to rearrange the data.

• Developers practicing continuous integration merge their changes back to the main branch as often as possible. By doing so, you avoid the integration hell that usually happens when people wait for release day to merge their changes into the release branch.
• Continuous delivery is an extension of continuous integration to make sure that you can release new changes to your customers quickly in a sustainable way. This means that on top of having automated your testing, you also have automated your release process and you can deploy your application at any point of time by clicking on a button.
• Continuous deployment goes one step further than continuous delivery. With this practice, every change that passes all stages of your production pipeline is released to your customers. There's no human intervention, and only a failed test will prevent a new change to be deployed to production.

• Monolithic Architecture is similar to a big container wherein all the software components of an application are assembled together and tightly packaged.
• A Service-Oriented Architecture is a collection of services which communicate with each other. The communication can involve either simple data passing or it could involve two or more services coordinating some activity.
• Microservice Architecture is an architectural style that structures an application as a collection of small autonomous services, modeled around a business domain.

UNION puts lines from queries after each other, while JOIN makes a cartesian product and subsets it -- completely different operations. Trivial example of UNION:

mysql> SELECT 23 AS bah
    -> UNION
    -> SELECT 45 AS bah;
+-----+
| bah |
+-----+
|  23 |
|  45 |
+-----+
2 rows in set (0.00 sec)

similary trivial example of JOIN:

mysql> SELECT * FROM
    -> (SELECT 23 AS bah) AS foo
    -> JOIN
    -> (SELECT 45 AS bah) AS bar
    -> ON (33=33);
+-----+-----+
| foo | bar |
+-----+-----+
|  23 |  45 |
+-----+-----+
1 row in set (0.01 sec)

WHERE clause introduces a condition on individual rows; HAVING clause introduces a condition on aggregations, i.e. results of selection where a single result, such as count, average, min, max, or sum, has been produced from multiple rows. Your query calls for a second kind of condition (i.e. a condition on an aggregation) hence HAVING works correctly.

As a rule of thumb, use WHERE before GROUP BY and HAVING after GROUP BY. It is a rather primitive rule, but it is useful in more than 90% of the cases.

While you're at it, you may want to re-write your query using ANSI version of the join:

SELECT  L.LectID, Fname, Lname
FROM Lecturers L
JOIN Lecturers_Specialization S ON L.LectID=S.LectID
GROUP BY L.LectID, Fname, Lname
HAVING COUNT(S.Expertise)>=ALL
(SELECT COUNT(Expertise) FROM Lecturers_Specialization GROUP BY LectID)

This would eliminate WHERE that was used as a theta join condition.