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What is Interface Testing?Interface testing is a sort of software testing that confirms the proper connectivity between two separate software systems.An interface is a link that connects two components. In the computer world, this interface might be anything from APIs to web services. Interface testing is the process of evaluating these connected services or interfaces.An interface is a software program that contains a collection of instructions, communications, and other properties that allow a device and a user to communicate with one another.How to do Interface Testing?Interface testing consists of two major sections −Interface between a web server and an application ... Read More
To get boxplot data for Matplotlib boxplot we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make data frame using pandas.Make a box plot from DataFrame columns.Get boxplot's outliers, boxes, medians and whiskers data.Prit all the above information.To display the figure, use show() method.Exampleimport seaborn as sns import pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(dict(age=[23, 45, 21, 15, 12])) _, bp = pd.DataFrame.boxplot(df, return_type='both') outliers = [flier.get_ydata() for flier in bp["fliers"]] boxes = [box.get_ydata() for box in ... Read More
Exploratory testing, as the title suggests, is about observing and learning about the program, what it does, what it doesn't do, what works, and what doesn't work. The tester is always deciding what else to check next and where to invest his or her (limited) time. This method is particularly beneficial when there are no or few requirements and speed is of the essence.Exploratory testing could be used with other methodologies.What is Exploratory Testing?Exploratory testing is a practical method in which testers are engaged in as little preparation as possible and as much test execution as possible.The test planning process ... Read More
What is Functional Testing?Functional Testing is a form of software testing in which the software system is validated against the functional requirements/specifications. The goal of functional testing is to test each feature of a software program by giving adequate data and comparing the outcome to the Functional requirements.Functional testing is particularly concerned with black-box testing and is unconcerned with the application's source code. This testing examines the Application Under Test's User Interface, APIs, Database, Security, Client/Server connection, and other features. Testing can be performed automatically or manually.What do you test in Functional Testing?The primary goal of functional testing is to ... Read More
Storage TestingStorage testing is a form of software testing which is used to ensure that the software program under test saves necessary data in the correct folders and has adequate capacity to avoid unanticipated cancellations due to a lack of storage capacity. Storage Performance Testing is another name for it.Why Storage Testing?Slow storage causes slower responsiveness, longer query times, and worse application availability.Poor memory adds to the cost of server infrastructure upkeep.It aids in determining its actual storage limits prior to implementation.It is beneficial to comprehend how the system behaves when a fresh hardware device is installed or updated.Types of ... Read More
What is Destructive Testing?Destructive testing is a kind of software testing used to identify flaws in a software program. It is a testing approach in which an application is purposefully forced to crash in order to verify its resilience and discover the site of breakdown.Unlike the other testing methods that examine an application's functionality, this methodology examines the unexpected user behavior within the program.It is not essential to understand the specified requirements of a software system to do Destructive Testing. But, some understanding might aid in the development of an effective testing method.Why should we do Destructive Testing?It aids in ... Read More
The term 'Harness' in general refers to a 'Tool' for controlling something. The same rule goes for software testing as well. In Software Testing, Test Harness is a collection of software, test data, test drivers, and tools specially developed to test an application under various environments. Developers then analyze the results of the tests to ensure a satisfactory outcome.How is Test Harness done in software testing?Test Harness can be called a process that does all the testing works, such as executing tests via test libraries and generating reports. For that, developers and testers have to develop specific test scripts to ... Read More
Continuous TestingContinuous testing in DevOps is a kind of software testing that entails testing the program at each phase of the software development cycle. The purpose of continuous testing is to evaluate the software quality at each stage of the Continuous Delivery Process by checking promptly and frequently.In DevOps, the Continuous Testing phase encompasses participants such as Developers, DevOps, QA, and the operational system.This article will teach you −What is Continuous Testing?How is Continuous Testing different?How Is Continuous Testing Different from Test Automation?How to do Continuous TestingContinuous testing toolsBenefits of Continuous testingChallenges of continuous testingHow is Continuous Testing different?The traditional ... Read More
To set different opacity of edge and face color, we can use a color tuple and the 4th index of the tuple could set the opacity value of the colors.StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots using subplots() method.Set different values for edge and face color opacity.Add a rectangel patch using add_patch() method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt, patches plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True figure, ax = plt.subplots() edge_color_opacity = 1 # 0Read More
To draw a parametrized curve using pyplot.plot(), we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a variable, N, for number of samples.Create t, r, x and y data points using numpy.Create a figure and a set of subplots.Use plot() method to plot x and y data points.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True N = 400 t = np.linspace(0, 2 * np.pi, N) r = 0.5 + np.cos(t) x, y = r * ... Read More