Introduction to Generative AI for Software Testing

CT-GenAI · 53 questions

A municipal parking-permit desk encodes “resident + one vehicle + no unpaid tickets → approve” as if-then lines a clerk can open and edit. Which type of AI does this approach represent?
A community-theater box office wants last season’s no-shows sorted into “likely late” versus “likely cancel” after a person picks columns such as weekday and weather. Which AI approach does this describe?
A food-bank inventory app has thousands of photographed shelf labels, and nobody wants to hand-list traits such as font size or glare. Which type of AI is designed to learn features automatically from that kind of large, complex input?
A harbor-ferry tester asks a pre-trained model to draft a weekend-sailing test script from a user story rather than to classify last week’s tickets. Which type of AI does this use?
Four suppliers pitch a public-library hold system: a readable rule engine, a no-show scorer with hand-picked columns, a photo-spine reader that learned its own features, and a model that writes hold-cancellation notices. Which mapping of pitch to AI type is correct?
A community-solar billing tester is told they must first collect a labeled training set before any AI may draft test cases. What Chapter 1 advantage of generative AI for testers corrects that claim?
Last year’s defect tickets feed a predictor that only assigns categories such as “install” or “pay.” A second tool drafts new cases from this sprint’s stories. How should a tester classify these two uses?
A youth-soccer registration tester hears “we bought generative AI” and assumes any image-painting model can review user stories. What correctly describes an LLM in this setting?
A farmers-market stall-booking team can only host a compact on-laptop model for drafting reminder texts. How should they describe a small language model (SLM) compared with a general LLM?
A municipal snow-route incident note is split into sub-words and punctuation before the model processes it. Which LLM basic does this describe?
Two co-op grocery loyalty defect notes—“points vanished” and “balance dropped”—land near each other in a numeric space so the model treats them as related. Which LLM basic does this describe?
A community-college LMS tester mixes up “how the story is chopped,” “how each piece is numbered for meaning,” and “how much of the log still fits.” Which statement keeps the three LLM basics correctly separated?
A city bike-share tester asks why the model writes the next sentence of a defect report one piece at a time. What best explains transformer inference at tester depth?
A credit-union mobile-deposit tester accepts a fluent expected-result paragraph that invents a weekend fee the specification never stated. What Chapter 1 limit does this illustrate?
A volunteer-shift scheduler tester pastes the same user story twice and receives two different case lists. What Chapter 1 explanation fits best?
A municipal recycling-pickup tester pastes three weeks of route logs and the model “forgets” Monday’s missed stops. What does the context window represent?
A community-garden plot tester wants every historic booking CSV in one prompt “so nothing is missed.” What trade-off about a larger context window should they understand?
A small-clinic appointment book is described as “powered by a generative pre-trained transformer.” What does that phrase refer to for testers?
A school-lunch allergy team is quoted three weeks to “train a model on our menus” before anyone may ask for test cases. What practical tester benefit of pre-trained LLMs answers that delay?
A harbor-slip reservation tester’s pasted API log is silently cut off mid-stack-trace. Why should testers care whether prompt plus history fit the context window?
A municipal tree-trimming work-order dump is full of long hyphenated IDs that split into many tokens. What tester implication of tokenization does this illustrate?
A community-radio pledge tester asks the model to rewrite a fuzzy donor story into clearer acceptance language. What should they understand about LLM language help?
A city-pool lane-booking team is offered a general model trained on huge mixed text, code, and image data that still needs adaptation before it will emit their lane-hold case table. Which LLM category is that?
A credit-union wire-transfer tester gets cleaner case drafts after switching to a model further trained on prompt–expected-response pairs so it obeys “list three boundary cases.” Which LLM category is that?
A municipal poll-worker eligibility screen has nested if-then rules, and the tester needs a model that can walk those steps before proposing a case order. Which LLM category fits best over a plain instruction-tuned model?
A food-truck permit tester needs an LLM for two jobs: (a) rewrite one user story into a simple case table, and (b) justify a risk-based case order from several competing constraints. Which pairing best matches model type to task?
An interlibrary-loan tester pastes raw user stories into a foundation model and receives long essays instead of given-when-then cases. What best explains this outcome for test artefact generation?
A municipal water-meter coach tells the team to “use the non-reasoning model for the boilerplate case list.” In this syllabus, which model type does that label refer to?
A community-orchestra seat-map tester is told to “test the reasoning model with neuron coverage.” For CT-GenAI work, what is the appropriate focus?
A municipal dog-license tester waits on a reasoning model only to change the word “owner” to “guardian” throughout a template case. What is the best assessment of that model choice?
A bike-share kiosk team has a wireframe PNG plus a one-line user story and wants unlabeled controls called out for testing. Which model choice best fits the task?
A bike-share screen shows the button label “Unlock” while the user story says the primary action is “Start ride.” How should a tester best use a vision-language (multimodal) model here?
A clinic kiosk defect report says “the Confirm button is missing,” and the attached build screenshot still clearly shows Confirm. Which prompt approach best helps flag that mismatch?
A garden-plot map wireframe shows a disabled “Waitlist” control that the user story never mentions. Why would a tester feed both the wireframe image and the story into a multimodal model when drafting cases?
A pool-lane booking screenshot must inform a multimodal test prompt. A colleague only types lane.png into the chat. What is the key limitation of that approach?
A radio-pledge tester has a well-written user story and no UI yet. A colleague insists they must attach a mock screenshot before any LLM help. What is the soundest response?
A building-permit portal tester pastes a wireframe into a multimodal chat and writes only “what do you see?” Which change best aligns the prompt with a testing goal?
A snow-route map image is low-contrast, and a multimodal model “sees” a button that the PNG does not contain. How should the tester treat that output on this exam?
A ferry check-in story says “fast check-in for regulars” but never defines who counts as a “regular.” Which LLM use best matches requirements-analysis support?
A library-hold user story is given to an LLM, which returns a draft set of cases and suggested test objectives. Which GenAI testing capability does this primarily illustrate?
A community-solar story states a 3% credit. A tester asks an LLM for expected-result lines for three usage bands. What capability is this, and what constraint still applies?
A soccer age-band registration form needs under-8, on-boundary, and over-max birthdates without using real children’s records. Which GenAI testing capability does requesting those values primarily illustrate?
A stall-booking case list is given to an LLM, which returns a first-draft keyword script and suggests adding a boundary check on the date field. Which capability is illustrated?
After a recycling-route regression, a tester pastes a noisy log into an LLM and asks for a short summary plus severity and priority buckets. Which capability does this represent?
A garden-plot release is slipping, and the tester asks an LLM for an updated test-plan paragraph plus a defect-report skeleton. Which capability is this primarily?
A clinic-booking lead says GenAI is “only for writing cases.” Which statement best reflects the official capability view?
A new poll-worker tester types “what is a test condition on this story?” into a chat pane and iterates on the reply. Which interaction model does this describe?
A water-meter suite auto-drafts cases on every build through an API hooked to the test tool; nobody is chatting. Which interaction model is this?
A food-truck permit team must choose between nightly batch case refresh and ad-hoc “explain this requirement” help. How do the two GenAI interaction models compare for those needs?
Stakeholders who do not write scripts want to explore a lane-booking story in plain language for quick clarification. Which GenAI interaction choice fits best?
A bike-share program needs the same case-generation job after every API specification drop. Which interaction model should the team prefer for that repetitive, well-defined work?
A credit-union tester claims “the chatbot is magic so we can skip prompt care, and the API tool already has prompts baked in.” What is the best correction?
A tree-trimming tester walks a chatbot through “list ambiguities, then draft cases” in one sitting, while a colleague’s tool always emits a case table from a ticket id. What contrast does this highlight?