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CompatibilityIn simple terms, compatibility is the state in which two different things can coexist without conflicting. In real world, milk is compatible with water, oil and water are not compatible with each other.Compatibility TestingCompatibility testing is sub-category of software testing performed to determine whether the software under test can function on different hardware, operating systems, applications, network environments and mobile devices. It is a non-functional testing and is performed only after the software becomes stable.The main objective of compatibility testing is to check the functionality of the software on different software, hardware, networks, etc. It is essential to software development ... Read More
A 1-phase supply produces a pulsating magnetic field which does not rotate in the space. Therefore, a 1-phase supply cannot produce rotation in a stationary rotor. Although, like a 3-phase supply, the 2-phase supply can also produce a rotating magnetic field of constant magnitude. Therefore, all the single-phase induction motors, except shaded pole induction motor, are started as 2-phase motor. Once so started, the motor will continue to run on the 1-phase supply.How does a 2-Phase Supply Produce Rotating Magnetic Field of Constant Magnitude?Consider a 2-phase, 2 pole motor, where the phases A and B are fed by a balanced ... Read More
Performance testing tools aid in determining the system's, computer's, network's, program's, or application's speed, effectiveness, reliability, scalability, and interoperability.The following is a hand-picked list of the Top Load Testing Tools. The list contains both free and paid tools, each with the most recent features and downloadable links.We've already done the legwork for you. The following is a comparison of the best web application performance and load testing tools −WebLOADLoadNinjaReadyAPI PerformanceStormForgeLoadViewApache JMeterLoadRunnerAppvanceNeoLoadLoadCompleteWebLOAD WebLOAD is the tool of choice for businesses with high user loads and complex testing needs. It enables you to load and stress test any internet application by generating load ... Read More
What exactly is test coverage?In software testing, test coverage is defined as a statistic that indicates the quantity of testing completed by a collection of tests. It will entail obtaining information about which sections of a program are executed when the test suite is performed in order to establish whether conditional statement branches have been taken.It is a way for making sure that your tests are testing your code or how much of your code you exercised by running the test.Code Coverage and Test CoverageCode coverage and test coverage are frequently mistaken. Even while the basic concepts are the same, ... Read More
To put the line title at the bottom of a figure in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a variable, N, to get the number of sample data.Plot the x and y data points using scatter() method.Set the title at the bottom of the figure in matplotlib, with y=-0.01.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True N = 100 x = np.random.rand(N) y = np.random.rand(N) plt.scatter(x, y, c=x, ... Read More
To make a simple lollipop plot in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a dataframe, df, of two-dimensional, size-mutable, potentially heterogeneous tabular data.Make an ordered dataframe, using sort_values().Make a list in the range of dataframe index.Create a stem plot, using the ordered dataframe.Set xticks and labels using xticks() method.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt import pandas as pd plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame({'group': list(map(chr, range(65, 85))), 'values': np.random.uniform(size=20)}) ... Read More
We can use ax.loglog(x, y) and set_major_formatter() methods to replace tick labels with computed values.StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Make a plot with log scaling on both the X and Y axis.Set the formatter of the major ticker.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt, ticker plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() ax.loglog(np.logspace(0, 5), np.logspace(0, 5)**2) ax.xaxis.set_major_formatter(ticker.LogFormatterExponent()) plt.show()OutputRead More
To have a function return a figure in Python (using Matplotlib), we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Make a function plot(x, y) that creates a new figure or activate an existing figure using figure() method.Plot the x and y data points using plot() method; return fig instance.Call plot(x, y) method and store the figure instance in a variable, f.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = ... Read More
To make a quiver plot in polar coordinates using Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create radii, thetas, theta and r data points using numpy.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Make poly collections of arrows.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True radii = np.linspace(0, 1, 5) thetas = np.linspace(0, 2 * np.pi, 20) theta, r = ... Read More
Risk-based Testing (RBT)It is a sub-category of software testing based on the probability of risks. In this test, the software is assessed to identify risk. It includes assessing criticality of business, frequency of usage, possible areas with problems, etc. This type of testing emphasizes testing of software’s features and functions which are vulnerable to defects.Risk is the occurrence of nay unwanted event that may have an effect (positive or negative) on the results of the project. Risks can either be events that have occurred previously or current events, or even something that could take place in future. These events affect ... Read More