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Ocean Sound College

Ocean Sound College, a liberal arts college located on the West Coast, provides dormitory housing for approximately half of its students. Students who choose not to live on campus, or who do not get assigned dormitory space, must find housing in the surrounding community. Currently, the housing office uses a cumbersome system of multiple binders to keep track of housing opportunities for students, faculty, and staff of the college. Housing listings are for college-owned housing, housing owned by private parties including landlords and individuals looking for roommates. The current system is difficult to maintain and keep up-to-date. The new college president approved a request to fund the development of a system to provide easier access and maintenance of listings. You are the systems analyst assigned from the college IT department to conduct the initial investigation into the feasibility of such a system. The preliminary investigation reports resulted in approval for you to proceed with the systems analysis phase. You have already developed data flow diagrams, documented the data stores, and created a data dictionary. Now you are at the point in the analysis phase where you need to describe the processes that will be used in the housing system.

Background

Based on your information gathering to date, you have determined the following about a listing system for the housing office at Ocean Sound College:

The current listing system revolves around multiple copies of three binders of housing listings. These are separate binders for undergraduate listings, graduate listings, and faculty/staff listings. Within each binder are copies of listings available to a particular group. Listings either are generated by the college housing office from their own housing units, or from private landlords who call the housing office to list housing vacancies. In addition, students or other groups of people who have rooms available in a residence may list the rooms.

The data dictionary has been developed to include data elements contained in each listing which includes the following: listing owner (college-owned housing, private landlord, or individual room for rent), type of housing (apartment, house, condo, etc.), square footage, number of bedrooms, number of bathrooms, rent, security deposit, utilities included, handicap features, other features and amenities, date of availability, lease term, multiple lease parties allowed, contact information, and restrictions on rental (smoking, non-smoking, gender, etc). Pet policy data elements include pets accepted, type of pet (cats, small dogs, large dogs, or other), pet fees, and deposits. Each property may be listed in any or all of the binders, to allow the listing party to direct their listing to their target audience.

When the college rents a property, the listing is removed from all binders in which it appears. Private landlords are asked to call in when a property is rented to facilitate the removal of that listing from the binders. People using the binders who find housing listings that already have been rented are asked to report those so they can be removed. The binders are reviewed at the end of each month by the housing office staff, and private listings older than 2 months are removed.

Based on the results of your information gathering, the next step is to develop a logical model of the proposed listing system. We use process descriptions to explain the logical steps that each process performs. To create these descriptions, we use three tools: structured English statements, decision tables, and decision trees.

Tasks

1. Create a set of structured English statements that accurately describes one process found in this system.

2. Design a decision table for a process in this system with all possibilities.

3. Simplify the table by combining rules where appropriate to demonstrate the logic that will be transformed into program code in the new system.

4. Draw a decision tree that reflects a process used in the system.

Operation Management, Management Studies

  • Category:- Operation Management
  • Reference No.:- M93114355

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