In CS, we explore logic questions, and how to use computing skills to create real-world applications. We started the year off by learning HTML/CSS to create these websites and spent the rest of the year focused on Java and the AP Computer Science curriculum content. The class culminates with the Apps for Good projects, where we use our computing skills to help the community.
Major transitions in life can be challenging for many groups of people such as young adults trying to live on their own, new immigrant families, and older adults trying to live independently. Buying and renting homes and real estate properties is one of the best ways to build wealth over time and be financially independent. However, current real estate websites only provide housing options based on minimal criteria such as location, budget, bedroom, and bathroom needs. The perfect house can be found in many places, but a strong community is what transforms a house into a true home. The proposed application attempts to increase personalization during the home-finding process. The application is called HackStreet, which would be able to filter homes based on criteria that the user defines as significant in buying a home. Ultimately, this application hopes to increase financial literacy and buyer confidence before purchasing a new home. The app will have a variety of features that assist the user in deciding their future home. Whether it be pricing, walk score, or local supermarkets, the list of potential housing will be automatically narrowed down to end up with an easily digestible list of potential homes for a user.
Major transitions in life can be challenging for many groups of people such as young adults trying to live on their own, new immigrant families, and older adults trying to live independently. Current real estate websites only provide housing options based on minimal criteria such as location, budget, bedroom, and bathroom needs. However, no product effectively provides housing options based on other criteria such as proximity to public transportation, schools, shopping centers, and more.
Anyone who needs to choose a suitable living area is a potential user of the app. The app will be able to take into account multiple considerations that different people may need, with varying degrees of importance. A college student looking for suitable living areas may want a campus within walking distance, along with a nearby grocery store. Families may want proximity to places of work and the nearby public school system. The needs are different from person to person, and the application will be able to accommodate for most requirements. The app will be made with the intent to satisfy all people who are moving to a new area’s needs.
The proposed application attempts to increase personalization during the home-finding process. The application is called HackStreet, which would be able to filter homes based on criteria that the user defines as significant in buying a home. The user would be able to select their desired zip code and distances to specific places such as hospitals, grocery stores, or other infrastructures that are important to them. Additionally, the web application would include a resource page that holds multiple modules to teach first-time buyers important financial terms and definitions. Buying a home is a significant financial undertaking, and users must be confident and informed before closing a deal. According to a survey by Bankrate, over 54% of teenagers reported feeling unprepared to finance the life they hope to have in adulthood (Johnson, 2022). Ultimately, this application hopes to increase financial literacy and buyer confidence before purchasing a new home.
Current products on the market such as Zillow and Redfin are great tools for finding homes. They provide up-to-date listings, and access to real estate agents, and allow users to collaborate with their partners to share their homes. However, the major real estate platforms lack advanced search filters that can help users not just learn about the house, but also the community of the house. Therefore, in our product, we incorporated search filters for distance to the nearest hospital, walk score, access to public transportation, and more. Additionally, many real estate websites lack robust decision-making tools to help users determine which home best meets their needs. In our product, we created a feature that allows users to favorite homes and rank which features matter most to them and the algorithm displays the house that meets those criteria.
This code uses randomization functions and the Applet class to generate random stars. I utilized the geometry of a star to create one star, and then placed it in a loop to create 10 stars of random sizes across the screen. This problem required a lot of collaboration and trail and error as there were multiple ways to approach it.
The Sieve of Eratosthenes is an algorithm to determine the number of primes up to a given number. All values are initialized to true to begin with, and the loop iterates from 1 to the square root of the largest number. The multiples of each number from 1 to the square root are converted to false as it is not a prime. The remaining true values are all prime numbers. I enjoy problems like these as they require a twist of math and logic, and there are multiple ways to reach a similar outcome.