CS173: Intro to Computer Science - Array Averaging (100 Points)

Assignment Goals

The goals of this assignment are:
  1. To use arrays to store collections of values

Background Reading and References

Please refer to the following readings and examples offering templates to help get you started:

The Assignment

In this lab, develop and use arrays to simplify your computation over collections of data, so that you do not need to know how many data elements you are working with in order to develop a generalized algorithm.

Consider the grading table of our course syllabus. It lists grading weights for each component of the course (for example, programming assignments). To compute your course grade, you would first average all your programming assignment grades together, and all the other grade component averages. To compute the assignment average \(\mu_{x}\), take the sum of each of your \(n\) assignment scores \(x_{i}\), and divide by the number of assignments, as follows:


\(\mu_{x} = \frac{\sum\limits_{i=1}{n} x_{i}}{n}\)

Then, those averages are averaged - but not equally. The weighted average is computed by multiplying each of your component averages by a weight \(w_{i}\), given by the syllabus (for example, a 50% weight would be computed as 0.5 for that corresponding \(w_{i}\)):


\(\mu_{x} = \sum\limits_{i=1}{n} w_{i} \times x_{i}\)

This is actually the same as the standard equally-weighted average, where \(w_{i}\) is \(\frac{1}{n}\), giving equal weight to all the components.

Create a program that assigns variable values to labs, assignments, etc., according to the syllabus grade breakdown. Compute your average lab grade, average assignment grade, etc., using equal weighted averaging.

Then, take those computed averages, and compute a weighted average of them, using the weights in the syllabus. Print out your final grade.

It is nice to be able to compute these averages without having to do so by hand, but you probably noticed how tedious is was to copy and paste, or re-write, your averaging code over and over again! We can use functions to reduce this workload.

Part 1: Equal Averages

Write a function computeEqualAverage that returns a double, and accepts an array of double for your individual grades. Modify your program so that you replace your equal-weight averaging with calls to this function. Pass your individual grades as an array parameter to this function.

Each time you return an equal average (for example, the equal average of your lab grades, the equal average of your assignment grades, and so on), insert those into an array called courseAverages that you will pass to computeWeightedAverage later. You can create an array of a certain size like this in your main() function, and each of these will hold the result of one of your calls to computeEqualAverage:

double[] averages = new double[4];

where you know up-front that you will store 4 averages (for example, assignments, labs, projects, and attendance). You have to specify how many elements you are storing up-front for now (we will improve upon this again later!).

Each time you call computeEqualAverage, store the result in one of these elements (for example, averages[0] = computeEqualAverage(grades); where grades is a double[], an array of double values representing your collection of individual grades: double[] grades).

You can create a pre-initialized array of grades like this:

double[] assignmentGrades = {90, 100, 80};
double[] labGrades = {95, 100, 85};

You can pass each of these to calls to computeEqualAverage, and assign the result to each index of averages, for example:

averages[0] = computeEqualAverage(assignmentGrades);
// ... and so on

Part 2: Weighted Averages

Now, write a function computeWeightedAverage that also returns a double, and accepts an array of double for your course averages, and an additional array of double to represent the weights. Call this function passing the average array and a weights array as parameters.

Exporting your Project for Submission

When you’re done, write a README for your project, and save all your files, before exporting your project to ZIP. In your README, answer any bolded questions presented on this page. Here is a video tutorial describing how to write a README for your project, and how to export it.

Submission

In your submission, please include answers to any questions asked on the assignment page in your README file. If you wrote code as part of this assignment, please describe your design, approach, and implementation in your README file as well. Finally, include answers to the following questions:
  • If collaboration with a buddy was permitted, did you work with a buddy on this assignment? If so, who? If not, do you certify that this submission represents your own original work?
  • Please identify any and all portions of your submission that were not originally written by you (for example, code originally written by your buddy, or anything taken or adapted from a non-classroom resource). It is always OK to use your textbook and instructor notes; however, you are certifying that any portions not designated as coming from an outside person or source are your own original work.
  • Approximately how many hours it took you to finish this assignment (I will not judge you for this at all...I am simply using it to gauge if the assignments are too easy or hard)?
  • Your overall impression of the assignment. Did you love it, hate it, or were you neutral? One word answers are fine, but if you have any suggestions for the future let me know.
  • Any other concerns that you have. For instance, if you have a bug that you were unable to solve but you made progress, write that here. The more you articulate the problem the more partial credit you will receive (it is fine to leave this blank).

Assignment Rubric

Description Pre-Emerging (< 50%) Beginning (50%) Progressing (85%) Proficient (100%)
Algorithm Implementation (60%) The algorithm fails on the test inputs due to major issues, or the program fails to compile and/or run The algorithm fails on the test inputs due to one or more minor issues The algorithm is implemented to solve the problem correctly according to given test inputs, but would fail if executed in a general case due to a minor issue or omission in the algorithm design or implementation A reasonable algorithm is implemented to solve the problem which correctly solves the problem according to the given test inputs, and would be reasonably expected to solve the problem in the general case
Code Quality and Documentation (30%) Code commenting and structure are absent, or code structure departs significantly from best practice, and/or the code departs significantly from the style guide Code commenting and structure is limited in ways that reduce the readability of the program, and/or there are minor departures from the style guide Code documentation is present that re-states the explicit code definitions, and/or code is written that mostly adheres to the style guide Code is documented at non-trivial points in a manner that enhances the readability of the program, and code is written according to the style guide
Writeup and Submission (10%) An incomplete submission is provided The program is submitted, but not according to the directions in one or more ways (for example, because it is lacking a readme writeup) The program is submitted according to the directions with a minor omission or correction needed The program is submitted according to the directions, including a readme writeup describing the solution

Please refer to the Style Guide for code quality examples and guidelines.