Distributed and Parallel Computing：Assignment2

Assignment for BST827 International Logistics

Compressing data means reducing the number of bits needed to represent it. Compressed data, due to its reduced size, is a lot faster to transfer and less expensive to store, freeing up storage and increasing network capacity. Algorithms that perform data compression are known as data compression algorithms. Data compression algorithms are divided into two categories: lossy and lossless. Lossy compression algorithms compress more than lossless compression algorithms, but at the cost of losing some information, which can’t be recovered. Lossy compression algorithms are typically used for audio and video files, where a loss in quality is tolerable and often not noticeable. Lossless compression algorithms on the other hand don’t compress as much, but do not lose any data, meaning compressed information can be exactly reconstructed back into its uncompressed form. Lossless compression algorithms are used for data that must maintain integrity, such as binaries, text documents, and source code.

This assignment has just one exercise. It is designed to help you get familiar with hashing and Java’s HashMap.

This is an open-ended assignment in which you are expected to write a detailed report documenting your results. Please submit your solution electronically via gradescope, on or before Dec 7 (Monday week 10). Submissions should be in the form of a written report, which is expected to be at least four pages (double column, 11pt), or roughly 2.5-3 thousand words, plus figures, tables, and equations. See an example template in the lecture slides to get an idea of the length expected. Examples of datasets and projects that may be of interest in this assignment will be discussed in the lectures, though you may use any dataset you wish (including the ones we used for Assignment 1). For a selection of datasets that I frequently use, see https://cseweb.ucsd.edu/~jmcauley/datasets.html

It is very important that you follow the directions as closely as possible. The directions, while perhaps tedious, are designed to make it as easy as possible for the TAs to mark the assignments by letting them run your assignment, in some cases through automated tests. While these tests will never be used to determine your entire grade, they speed up the process significantly, which allows the TAs to provide better feedback and not waste time on administrative details. Plus, if the TA is in a good mood while he or she is grading, then that increases the chance of them giving out partial marks. :) Up to 30% can be removed for bad indentation of your code as well as omitting comments, or poor coding structure.

In recent times, several professionals in health-care analytics are trying to understand the key factors that might dictate the chances of someone getting an infection while admitted at a hospital. 113 patients were randomly sampled, and initially, to predict InfectionRisk (Y) [higher values ⇒ higher risk and we are not extrapolating in any of the questions below], two potential cause variables were examined: ❼ Stay: the number of days the patient remained in hospital. ❼ XRay: the number of XRays the patient received.

In Assignments 8 and 9 you will complete the WLP4 compiler for which you wrote a scanner in Assignment 5, a parser in Assignment 6, and a context-sensitive analyzer in Assignment 7. For each problem, you will write a MIPS code generator for an increasingly larger subset of WLP4, culminating with a full WLP4-to-MIPS compiler. Each code generator will be a Racket or C++ program that takes as input a .wlp4i file and, if it conforms to the context-sensitive syntax of WLP4, produces as output a MIPS .asm file that may be assembled with cs241.binasm (or cs241.linkasm for Assignment 8 Problem 4 onwards) and then executed with mips.twoints or mips.array.

This assignment is due on Sunday Nov 22, 23:59 and has a coding part and a written part. • Submit your written part (Problems 1 and 2) as a single pdf on Gradescope. • Submit your code (Problem 3) on Ed. • All work must be done individually without consulting anyone else’s solutions in accordance with the University’s “Academic Dishonesty and Plagiarism” policies. • For clarifications and more details on all aspects of this assignment (e.g., level of justification expected, late penalties, repeated submissions, what to do if you are stuck, etc.) you are expected to regularly monitor the Ed Forum post “Assignment Guidelines”.

Submission is through WebCMS/give and should be a single pdf file, maximum size 2Mb. Prose should be typed, not handwritten. Use of LATEX is encouraged, but not required. Discussion of assignment material with others is permitted, but the work submitted must be your own in line with the University’s plagiarism policy.