Backed testing is a method or technique that examines the server of database side of web applications or software. The primary motive of performing this test is to test the application layer or database layer to make the software defect-free, and prevent deadlock, data corruption, or data loss. For seamless and efficient working of a software, its GUI and database must interact with each other. Usually, databases are validated for: ACID functions, CRUD operations, Schema, Migration, business rule conformance, security purposes and performance.
This testing is also referred to as "database testing". The data entered through the frontend is stored in the database of backend. This database may be a SQL server, MySQL server, Oracle, etc. The data is recorded as tables as records. This testing is necessary as if it is not performed properly, some serious complications such as deadlock, data corruption, data loss, etc. may arise.
To perform this testing, we do not need any GUI, and it can be done on the AUI and database. Thus, the data can be passed directly with browser and the parameters required for specific functions, and also to get the response in a predefined format, like XML or JSON.
Data mapping − To determine if the UI or frontend forms are accurately and consistently mapped with their respective fields in the database table.
ACID properties of transactions − Each transaction that a database executes must meet these four properties: atomicity, consistency, isolation and durability.
Data integrity − The recent and updated values of shared data must appear on the screens and other forms. The value must not be updated on a screen and then an older value displayed on another. They must be simultaneously updated.
Accuracy of business rules − Complicated databases cause complex components such as relational restrictions, triggers, stored procedures, etc. Thus, testers adopt appropriate SQL queries to authenticate these complex objects.
Transactions − It refers the access and retrieval of data. the ACID properties must be followed during transactions.
Database Schema − The design or structural organization of data in the database.
Triggers − When a particular event takes place in a specific table, a trigger is automatically instructed to be executed.
Procedures − The set of statements or functions that govern the transactions in the database.
Structural Testing − It tests the internal structure of a software. It is usually performed by a team that is well acquainted with the development phase of the software. It checks various aspects of the software based in its types. It enables thorough testing of the software, and also detects defects at an early stage. It eliminates dead code. It does not take much time, and is mostly automated. It demands knowledge of the code to execute test. It also needs expertise on the tool used for testing. It can also be expensive sometimes.
Functional Testing − This testing is done to test the system against the functional requirements and specifications. It makes sure that the requirements and specifications are properly met by the software. It helps deliver defect-free and high-quality software. It primarily emphasizes the specifications as per user demands. However, there is a high chance of performing redundant testing. Some logical errors in the software can go unnoticed.
Non-functional Testing − This testing verifies the non-functional requirements of the software. It determines if the behaviour of the software meets requirements or not. It evaluates all aspects that are not tested in functional testing. It offers a high level of security, ensures loading capacity, and improves performance of the software. Test cases need not be written again as they are never changed, and non-functional testing also consumes less time than other testing processes. However, it must be performed whenever the software is updated. Thus, people need to pay to re-examine the software, which makes it very expensive
Backend testing involves validating the following −
Keys and Indexes
In backend testing, the request is directly passed through a browser with the parameters needed for the function and to obtain a response in a default format, such as XML or JSON. The database must be connected directly and the data must be verified using SQP queries. Debugging is possible through log files.
The preliminary phase of backend testing is to acquire design specification for a database server. Then, to test specification design, followed by implementing test cases in the design using SQL code.
Data Factory − This cloud-based data integration service or tool, developed by Azure, enables creating data-driven workflows in the cloud to automate data movement and transformation. This tool itself does not store any data. it enables monitoring and managing workflows through programmatic and UI mechanisms. It allows creating data pipelines that move and transform data, then run the pipelines on a schedule. The data used and produced by workflows is time-sliced data, and the pipeline mode can be specified as scheduled or one time.
DTM Data Generator − This tool produces data rows and schema objects for testing, e.g., performance analysis, or QA testing. It was developed to offer high quality and realistic test arrays to developers and QA engineers. Data Generator automatically generates data values and optional schema objects.
Test Data Generator − This tool generates mock data for testing, which may be random or specifically selected to obtain a desired result. It is more useful for databases as it saves data in tables and columns that contains particular types of information. Different types of test data generator are random test data generator, goal-oriented test data generator, pathwise test data generator, and intelligent test data generator.
TOAD − This widely used tool supports many databases and platforms. It is free; however, it can be upgraded through subscription. It helps develop high-quality, and better performing software faster. It helps do daily administration tasks efficiently, diagnoses and resolves performance-related problems. It easily manages database changes. It enables integrating database change management into DevOps workflow. Its self-service capabilities can be used for easy data preparation in secure and governed workflows, connecting IT and business. It helps create high-quality data models and also enables making rapid changes in data structures across more than 20 platforms. It tests software against real workloads to make sure they scale up in production and meet performance Service-level Agreements (SLAs).
pHpMyAdmin − This open-source tool allows running queries and interacting with database through a UI. This is an intuitive and excellent tool and does not need any prior training to use. It is most useful as a connection medium to MySQL and MariaDB databases.
HammerDB − This open-source tool is widely used by database experts. It supports many databases, such as Oracle, SQL server, IBM, Db2, MySQL, MariaDB and PostgreSQL. It provides expert level support and can be used to generate bulk data and loads for cloud testing.
Setting up test environment − Backend testing begins with setting up the test environment for the testing to be performed to get quality testing process.
Generating test scenarios − After the test environment is established, the test cases are designed for performing the test.
Execution − It is the core of the testing process, in which the test cases are executed.
Analysis − After all the test cases have been executed, the process and results are analysed to determine if the testing process has been properly performed or not.
Log Defects − Log defects, also known as report submitting, is the last stage where testing team reports the developing team about the defects detected in the system’s database.
It helps test databases, servers as well as APIs.
It actually focuses on data and its organization level in the database.
Backend testing is an in-depth testing and ensures maximum test coverage.
It helps discover many defects in the early stage.
It helps avoid deadlock and data loss.
It improves the software’s durability and functional; constancy. It also enhances data quality.
It comprehensively tests software, thus providing more control over the test coverage.
It requires deep database knowledge.
It may add to the organizational expense.