hw1

A test strategy is defined as:

a) Why is a test program's specified behaviour different from its implemented behaviour?   b) What are the key differences between special value testing and random testing when employing boundary value analysis?

Do the two methods of testing differ?

Definition of Parameterized Testing.

As we've previously seen, equations describing situations often contain uncertain parameters, that is, parameters that aren't necessarily a single value but instead are associated with a probability distribution function. When more than one of the variables is unknown, the outcome is difficult to visualize. A common way to overcome this difficulty is to simulate the scenario many times and count the number of times different ranges of outcomes occur. One such popular simulation is called a Monte Carlo Simulation. In this problem-solving exercise you will develop a program that will perform a Monte Carlo simulation on a simple profit function. Consider the following total profit function: PT=nPv Where Pr is the total profit, n is the number of vehicles sold and P, is the profit per vehicle. PART A Compute 5 iterations of a Monte Carlo simulation given the following information: n follows a uniform distribution with minimum of 1 and maximum 10 P, follows a normal distribution with a mean…

What distinguishes exploratory testing from other testing techniques?

An experiment is performed and four events (A, B, C, and D) are defined over the set of all possible outcomes. Use the table below to select the pair of events that are independent: P(A) = 1/6 p(A/B) = 1/6 P(B) = 1/3 p(A/D) = 1/3 P(C) = 1/6 p(C/B) = 1/4 P(D) = 1/3 p(C/D) = 1/3

Please dont USE Ai  Fuzzy Logic-Based Fake News Detection Example Suppose we have a news article with the following features that you use to determine whether the article is likely to be fake news: Word Count: The total number of words in the article. Emotional Tone: A score indicating the article's emotional tone (positive, negative, or neutral). Source Reliability: A rating (on a scale of 0 to 1) representing how reliable the news source is. To describe the qualitative characteristics of the above features and represent its inherently vague or imprecise, we use these linguistic variables: Word Count: Low, Medium, High Emotional Tone: Negative, Neutral, Positive Source Reliability: Low, Medium, High These membership functions represent each feature.             Consulting a group of experts, they suggest that to classify an article as fake news, we must follow two basic rules: If the Word Count is High AND the Emotional Tone is Negative, the article is likely fake. If…

e) Design a factorial ANOVA test and run it in the statistical software package of your choice. Write all the steps (two-way factorial ANOVA model, statistical hypotheses, Tukey comparisons, interaction plot and conclusion).

Supervised machine learning:   includes a fair amount of trial and error in model design.   requires picking the correct model from the start, or else your foundations are weak   requires a PhD or the equivalent level of experience in Computer Science   will often need millions of images to build any sort of useful model   is largely dependent on the quality of your data. Clean, well-labeled data builds strong models.

Software testing experts claim that applying a stratified sample of real-life test cases is more effective for identifying errors and more efficient than regular random sampling. 1. If you agree, list your arguments. 2. If you disagree, list your contradictory arguments.

select more than one!

When it comes to testing, what exactly is parametrized testing?

Supervised learning example: Iris classificationLet’s take a look at another example of this process, using the Iris dataset we discussed earlier. Our question will be this: given a model trained on a portion of the Iris data, how well can we predict the remaining labels?

T or F

The p-value of a test is the smallest level of significance at which the null hypothesis can be rejected. True False