#16: 2/23/18 Program #3 Graded 
I have run the automatic batch selfcheck tests for Program #3 and the grades
are now recorded.
See the
assignment grades and
Grades(zipped .xlsm file) files, whose
details are discussed below, in Announcement #7.
I used a different bsc test file for
grading: one that defined a pnamedtuple('Quad1', 'x y z f'), having a
different number of fields with different names not in alphabetical order.
The class average was about 99% and the median was 104%, meaning that most
students correctly solved most problems, and over half (91%) of the class
correctly solved all the problems (or had minor deductions).
Note that this problem had an extra credit part, as well as the standard extra
credit for an early submission.
Overall there were 91% As, 2% Bs, 0% Cs, and 6% Ds and Fs.
About 45% of the students submitted early, and these early submitters scored
better (average of 103%) than students submitting on the due day (average
of 95%); I am assuming that some students ran out of time before they
finished all the problems, and will plan to get started earlier on later
program.
In the assignment spreadsheet, Column A contains the Hashed IDs of all students (in sorted order); Column B contains an X if we believe the student submitted work on time (for pairs, only the submitting student will show an X, not their partner); Column C shows the extra credit points for early submissions (students submitting a few minutes late show 2; students submitting more than a few minutes late were not graded). Row 2 shows the number of points each group of batchself checks is worth; row 3 shows the number of tests performed for each problem: all were batchself check tests. Rows 45 shows further information about the tests performed in each column. Rows 6 and beyond show the number of failed tests for each student (a blank indicates no failed tests: equivalent to 0 failed tests). To compute the number of points for a problem/in a column, compute the percentage of successful tests and multiply it by the number of points the problem is worth. So for example, if a student missed 1 of 4 tests on a 4 point problem, he/she would receive 3/4*4 = 3 points. Column L shows each student's cumulative score, for all the tests in the single problem in this assignment. Columns MO show each student's cumulative Score, the score Rounded to an integer (what integer is entered in the Grades spreadsheet) and Percent, based on the number of points the assginment is worth (here 50). Note that these columns are filled in both for submitters and their partners (these are the only columns filled in for partners): a partner should see his/her submitter's line for details. Students should talk to the TA for their Lab first, if they do not understand why they received the marks they did or dispute any of these marks. The best time to talk with your TA about grades is during one of your Labs, when both student and TA are physically present to examine the submission and the grade, possibly running the solution on a computer they can share. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). IMPORTANT Information about Student Grades
This assignment was designed to illustrate the richness of ways to solve programming problems: writing a program that automatically writes a class, given the required information to specify it (class name and fields). It also provided an opportunity to improve your stringprocessing abilities. As with all assignments, you should examine my solution. 
#15: 2/19/18 Midterm Graded 
The TAs and I have graded and recorded the scores for the midterm exam.
The TAs will distribute the graded midterms in their labs this week.
If you do not pick up your exam then, you will have to come to my office hours
to retrieve it (and I would prefer not to have hundreds of exams
stockpiled in my office).
See the
assignment grades and
Grades(zipped .xlsm file) files.
The class average was about 66% and the median was 68% (last Fall they were 65% and 66%). Because the average was below 75%, about 11 normalization points (9%) will be added when computing the average of all graded instruments on the spreadsheet. The grades recorded in the spreadsheet (both in Columns R and S) are the actual exam grades (without normalization points; see cell R8, highlighted in yellow, for the number of normalization points that will boost your score). After normalizing the scores on the midterm, overall there were 22% As, 23% Bs, 22% Cs, 14% Ds, and 19% Fs (last Fall there were 22% As, 23% Bs, 18% Cs, 19% Ds, and 18% Fs; that is a pretty close match). I will show some more detailed information about the exam in lecture on Monday. Now is a good time to look at course grades as well, as we have graded nearly half of the total number of testing instruments (450 of 1,000 points). Now is the first time that recorded grades are truly meaningful, because they include testing instruments in all the major categories: quizzes, programs, inlab exams, and written exams. The approximate distribution of course grades (for those students who submitted a midterm exam) is 51% As, 21% Bs, 13% Cs, and 15% Ds and Fs: these numbers are better than my original prediction of of 25% in each of these four categories (e.g., we have 72% As and Bs instead of 50% As and Bs). The different problems, with the indicated averages, were graded by the following staff.
If you have any issues with how any exam problem was graded, talk to the staff member who graded it, and they can discuss the rubric with you and resolve any issues. But first, please examine my solution and understand the differences between it and your answer. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). Note: Because we examined code (unlike for the InLab exam) sometimes points were deducted not for correctness issues, but for stylistic issues: e.g., using extra data structures/loops, not using unpacking appropriately, Imporant: As with the InLab Exams, if a student performs better on the Final Exam (since it is cumulative), I will replace their Midterm Exam score with their Final Exam score.

#14: 2/9/18 Quiz #4 Graded 
I have run the automatic batch selfcheck tests for Quiz #4 and the grades are
now recorded.
See the
assignment grades and
Grades(zipped .xlsm file) files, whose
details are discussed below, in Announcement #7.
The class average was about 88% and the median was 100%, meaning that most
students correctly solved most problems, and over half (77%) of the
class correctly solved all the problems (or had minor deductions).
Overall there were 77% As, 6% Bs, 3% Cs, and 14% Ds and Fs.
About 29% of the students submitted early, and these early submitters scored
much better (100% average) than students submitting on the due day (84%); I am
assuming that some students ran out of time before they finished all the
problems, and will plan to get started earlier on later quizzes.
In the assignment spreadsheet, Column A contains the Hashed IDs of all students (in sorted order) and Column B contains an X if we believe the student submitted work on time. Row 1 for Columns CI shows how many points the problems were worth. Row 2 shows the number of tests performed for each problem. Row 3 shows the part of the problems in more detail. Rows 4 and beyond show the number of failed tests for each student (a blank indicates no failed tests: equivalent to 0 failed tests). To compute the number of points for a problem/in a column, compute the percentage of successful tests and multiply it by the number of points the problem is worth. So for example, if a student missed 5 of 20 tests on a 4 point problem, he/she would receive 15/20*4 = 3 points. Columns JK show the cumulative score for each Problem. Columns LN show each student's cumulative Score, the score Rounded to an integer (what integer is entered in the Grades spreadsheet) and Percent, based on the number of points the assginment is worth (here 25). Students should talk to the TA for their Lab first, if they do not understand why they received the marks they did or dispute any of these marks. The best time to talk with your TA about grades is during one of your Labs, when both student and TA are physically present to examine the submission and the grade, possibly running the solution on a computer they can share. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). IMPORTANT Information about Student Grades

#13: 27/18 Program #2 Graded 
I have run the automatic batch selfcheck tests for Program #2 and the grades
are now recorded.
See the
assignment grades and
Grades(zipped .xlsm file) files, whose
details are discussed below, in Announcement #7.
The class average was about 95% and the median was 100%, meaning that most
students correctly solved most problems, and over half (85%) of the class
correctly solved all the problems (or had minor deductions).
Overall there were 85% As, 4% Bs, 4% Cs, and 7% Ds and Fs.
About 49% of the students submitted early, and these early submitters scored
much better (102% average) than students submitting on the due day (92%
average); I am assuming that some students ran out of time before they
finished all the problems, and will plan to get started earlier on later
programs.
In the assignment spreadsheet, Column A contains the Hashed IDs of all students (in sorted order); Column B contains an X if we believe the student submitted work on time (for pairs, only the submitting student will show an X, not their partner); Column C shows the extra credit points for early submissions. Row 2 for Columns DAE shows how many points the problems were worth. Row 3 shows the number of tests performed for each problem: all were batchself check tests. Row 4 shows further information about the tests performed in each column. Rows 5 and beyond show the number of failed tests for each student (a blank indicates no failed tests: equivalent to 0 failed tests). To compute the number of points for a problem/in a column, compute the percentage of successful tests and multiply it by the number of points the problem is worth. So for example, if a student missed 1 of 4 tests on a 4 point problem, he/she would receive 3/4*4 = 3 points. Columns AFAG show each student's cumulative score, for all the tests in each of the two problems in this assignment. Columns AHAJ show each student's cumulative Score, the score Rounded to an integer (what integer is entered in the Grades spreadsheet) and Percent, based on the number of points the assginment is worth (here 50). Note that these columns are filled in both for submitters and their partners (these are the only columns filled in for partners): a partner should see his/her submitter's line for details. Students should talk to the TA for their Lab first, if they do not understand why they received the marks they did or dispute any of these marks. The best time to talk with your TA about grades is during one of your Labs, when both student and TA are physically present to examine the submission and the grade, possibly running the solution on a computer they can share. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). IMPORTANT Information about Student Grades
This assignment was designed to provide you with a good grounding in the use of classes and the practice of overloading operators in classes. Quiz #4 covers decorators for iterators using generators. All these topics will be tested again on the Midterm and InLab Exam #2. As with all assignments, you should examine my solutions. 
#12: 2/4/18 Quiz #3 Graded 
I have run the automatic batch selfcheck tests for Quiz #3 and the grades are
now recorded.
See the
assignment grades and
Grades(zipped .xlsm file) files, whose
details are discussed below, in Announcement #7.
The class average was about 90% and the median was 100%, meaning that most
students correctly solved most problems, and over half (67%) of the class
correctly solved all the problems (or had minor deductions).
Overall there were 67% As, 18% Bs, 5% Cs, and 10% Ds and Fs.
About 32% of the students submitted early, and these early submitters scored
much better (97% average) than students submitting on the due day (87%
average); I am assuming that some students ran out of time before they
finished all the problems, and will plan to get started earlier on later quizzes.
There were only one student whose code timedout when I graded it; I let the grading program run everyone's code for 10 seconds. If you code timedout, talk to your TA about replacing the body of any offending code by just pass, so that it won't timeout, allowing all the other code to be graded. In the assignment spreadsheet, Column A contains the Hashed IDs of all students (in sorted order) and Column B contains an X if we believe the student submitted work on time. Row 1 for Columns CN shows how many points the problems were worth. Row 2 shows the number of tests performed for each problem. Rows 4 and beyond show the number of failed tests for each student (a blank indicates no failed tests: equivalent to 0 failed tests). To compute the number of points for a problem/in a column, compute the percentage of successful tests and multiply it by the number of points the problem is worth. So for example, if a student missed 5 of 20 tests on a 4 point problem, he/she would receive 15/20*4 = 3 points. Columns OP show the cumulative score for each Problem. Columns QS show each student's cumulative Score, the score Rounded to an integer (what integer is entered in the Grades spreadsheet) and Percent, based on the number of points the assginment is worth (here 25). Students should talk to the TA for their Lab first, if they do not understand why they received the marks they did or dispute any of these marks. The best time to talk with your TA about grades is during one of your Labs, when both student and TA are physically present to examine the submission and the grade, possibly running the solution on a computer they can share. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). IMPORTANT Information about Student Grades
In the Fraction class, some students wrote operators that returned strings instead of Fraction objects; a few bsc.txt tests fail in such cases. In the Private class, some students wrote __getattr__ using an incomplete if structure: not doing anything under certain circumstances; others wrote code that worked only for the methods/attributes in the download (not classes in general). I added a few new bsc.txt test to fail in such cases. 
#11: 2/2/18 InLab Programming Exam #1 Graded 
I have run the automatic batch selfcheck tests for InLab Exam #1 and the
grades are now recorded.
See the
assignment grades and
Grades(zipped .xlsm file) files, whose
details are discussed below, in Announcement #7.
You can find your solutions (by your Hashed ID), my solutions, and the actual bsc.txt files I used to compute grades for this assignment, in the EEE dropbox for this class (see the name pattis_ilestudentsolutions.zip); when you test your code with the bsc.txt, you will have to replace its script by importing driver and calling driver.driver(). See the script in my solutions for this code. For Labs 19 use bscile1W18.txt and for Labs 1015 use bscile2W18.txt. I believe the InLab Exams are the best indicator, of all testing instruments, of your ability to program: read specifications and transform them into working code (writing code and debugging what you wrote). As I'll say in class, Tolstoy is often quoted (from Anna Karenina) as writing, "Happy families are all alike; every unhappy family is unhappy in its own way."My adaptation of this quote is "Highscoring students are all alike (knowing how to program well); every lowscoring student did poorly in his/her own way: e.g., lack of programming or debugging ability, freezing on the exam, misreading or misunderstanding some problem statements, spending too much time debugging one problem, being ill when taking the exam, arriving late, etc."So, I understand that there are many possible reasons that students don't do well on InLab Exams. If you did poorly, think about why; don't fool yourself. The spreadsheet computes grades the standard way: the percentage of tests passed for each function multiplied by 20 (each problem was worth 20 points), with all the points added up. Column I computes this number, which is also the same as the rounded value (Column J) and the percentage (Column K) The result was the class average was about 93% and the median was about 101%. The large skew between these statistics shows that although the majority of students solved all the problems correctly, there were other students who did very poorly, dragging down the average much more than the median. At the extremes, 61% of the students submitted code in which all six functions passed all batch selfcheck tests; another submitted code in which five functions passed all batch selfcheck tests; 6% submitted code in which 2 or fewer functions passed all batch selfcheck tests; everyone solved the first problem correctly. The approximate distribution of grades on this InLab exam is 82% As, 6% Bs, 0% Cs, 6% Ds, and 6% Fs. There were actually two different exams given. Although they both used Stock Portfolios, 4 of 6 questions were different (but similar in how they were solved). FYI, the averages for the different exams was 92% for students in Labs 19 and 93% for students in Labs 1015. This exam was very similar in the kinds of problems it asked as the practice exam I distributed, so I expected students to do well. Students should talk to the TA for their Lab first, if they do not understand why they received the marks they did or dispute any of these marks. The best time to talk with your TA about grades is during one of your Labs, when both student and TA are physically present to examine the submission and the grade, possibly running the solution on a computer they can share. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). IMPORTANT Information about Student Grades
Finally, if students score a higher percentage on their InLab Exam #2 (which involves material from the first, as well as Classes, Operator Overloading, and writing Iterators), I will score their InLab Exam #1 higher (in the past I have often made the first exam score equal to the second; thereby erasing the first score; other times I have averaged the two). Therefore, even a terrible grade on this exam can have a minimal effect on your final grade if you perform much better on InLab Exam #2. 
#10: 1/26/18 Quiz #2 Graded 
I have run the automatic batch selfcheck tests for Quiz #2 and the grades are
now recorded.
See the
assignment grades and
Grades(zipped .xlsm file) files, whose
details are discussed below, in Announcement #7.
The class average was about 83% and the median was 88%, meaning that most
students correctly solved most problems; almost half (46%) of the class
correctly solved all the problems (or had minor deductions).
Overall there were 44% As, 28% Bs, 13% Cs, and 13% Ds and Fs.
Problem #3 turned out to be harder for students than I predicted:
only 117 students(23%) solved it correctly; check my solution.
Look at my solution to 1c: besides including my solution,it includes a way to
use a bunch of smaller named rules and re_expand to solve the problem.
About 18% of the students submitted early, and these early submitters scored
much better (93% average) than students submitting on the due day (81%
average);
I am assuming that some students ran out of time before they finished all the
problems, and will plan to get started earlier on later quizzes.
In the assignment spreadsheet, Column A contains the Hashed IDs of all students (in sorted order) and Column B contains an X if we believe the student submitted work on time. Row 1 for Columns CK shows how many points the problems were worth. Row 2 shows the number of tests performed for each problem. Rows 4 and beyond show the number of failed tests for each student (a blank indicates no failed tests: equivalent to 0 failed tests). To compute the number of points for a problem/in a column, compute the percentage of successful tests and multiply it by the number of points the problem is worth. So for example, if a student missed 5 of 20 tests on a 4 point problem, he/she would receive (205)/20*4 = 15/20*4 = 3 points. Columns LN show each student's cumulative Score, the score Rounded to an integer (what integer is entered in the Grades spreadsheet) and Percent, based on the number of points the assginment is worth (here 25). Students should talk to the TA for their Lab first, if they do not understand why they received the marks they did or dispute any of these marks. The best time to talk with your TA about grades is during one of your Labs, when both student and TA are physically present to examine the submission and the grade, possibly running the solution on a computer they can share. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). IMPORTANT Information about Student Grades

#9: 1/24/18 Program #1 Graded 
I have run the automatic batch selfcheck tests for Program #1 and the grades
are now recorded.
See the
assignment grades and
Grades(zipped .xlsm file) files, whose
details are discussed below, in Announcement #7.
The class average was about 87% and the median was 100%, meaning that most students correctly solved most problems, and over half (66%) of the class correctly solved all the problems (or had minor deductions). Overall there were 66% As, 10% Bs, 7% Cs, and 17% Ds and Fs. FYI, last quarter, there were 63% As, 9% Bs, 11% Cs, and 17% Ds and Fs. About 35% of the students submitted early, and these early submitters scored much better (102% average) than students submitting on the due day (93% average). I am assuming that some students ran out of time before they finished all the problems, and will plan to get started earlier on later programs. In the assignment spreadsheet, Column A contains the Hashed IDs of all students (in sorted order); Column B contains an X if we believe the student submitted work on time (for pairs, only the submitting student will show an X, not their partner); Column C shows the extra credit points for early submissions or deductions if too many parts were submitted on the last two days: although the exact algorithm is a bit more complex, students submitting multiple programs on the due date lost 3 points for all but one; students submitting multiple programs on the day before the due date lost 2 points for all but one, but I did grade all the submitted programs. Recall the published rubric said that I would not grade multiple programs submitted on these days, so the rubric I used was less severe. About 20% of the submissions received some kind of penalty: the average penalty was about 7 points. Columns AIAK show how many submissions were early, were on the day before the due date, and were on the due date respectively. Row 2 for Columns DY shows how many points the problems were worth. Row 3 shows the number of tests performed for each problem: all were batchself check tests. Rows 45 show further information about the tests performed in each column. Rows 6 and beyond show the number of failed tests for each submission (a blank indicates no failed tests: equivalent to 0 failed tests). To compute the number of points for a problem/in a column, compute the percentage of successful tests and multiply it by the number of points the problem is worth. So for example, if a student failed 1 of 4 tests on a 5 point problem, he/she would receive (41)/4*5 = 3/4*5 = 3.75 points. Columns ZAD show each student's cumulative score, for all the tests in each of the problems in this assignment. Columns AEAG show each student's cumulative Score, the score Rounded to an integer (what integer is entered in the Grades spreadsheet) and Percent, based on the number of points the assginment is worth (parts 12 24; parts 35 26). Note that these columns are filled in both for submitters and their partners (these are the only columns filled in for partners): a partner should refer to his/her submitter's line for details. Students should talk to the TA for their Lab first, if they do not understand why they received the marks they did or dispute any of these marks. The best time to talk with your TA about grades is during one of your Labs, when both student and TA are physically present to examine the submission and the grade, possibly running the solution on a computer they can share. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). IMPORTANT Information about Student Grades
This assignment was designed to provide you with a good grounding in the use of the standard data structures in Python: list, tuple, set, and dict (and the defaultdict variant). It also included practice iterating overs such structures, writing comprehensions, use of the sorted function and lambda, and other useful/important Python functions. Unlike Quiz #1, the problems were bigger, requiring more interesting algorithms to solve, but still all expressible with a small number of Python language features. All these topics will be tested again on the Midterm and InLab Exam #1. As with all assignments, you should examine my solutions. 
#8: 1/22/18 Quiz #1 Graded 
I have run the automatic batch selfcheck tests for Quiz #1 (checking
correctness) and the Readers/TAs have examined problem 1 and the code
(checking requirements: e.g., statements/solution) and the grades are now
recorded and posted.
See the
assignment grades and
Grades(zipped .xlsm file) files, whose
details are discussed below, in Announcement #7.
The class average was about 78% and the median was 88%, meaning that most
students correctly solved most problems (40% As), and 11% of the class
correctly solved all the problems.
Overall there were 40% As, 24% Bs, 11% Cs, and 25% Ds and Fs for those students
who submitted work; most of the students who scored near 0 submitted
code that we could not run (see the paragraphs below for possible regrading by
your TA).
FYI, the Fall quarter grades for this quiz were
43% As, 17% Bs, 13% Cs, and 27% Ds and Fs for those students who submitted
work.
About 20% of the students submitted early (although there are no extra credit points on quizzes for doing so), and these early submitters scored much better than students submitting on the due day (89% compared to 75%): a difference of 1.5 full grades (students submitting 2 days early had an average of 91%). I am assuming that some students ran out of time before they finished all the problems, and will plan to get started earlier on later quizzes. In the assignment grades spreadsheet, Column A contains the ID Hashed of all students (in sorted order) and Column B contains an X if we believe the student submitted work on time. Column C shows deductions for
Rows 4 and beyond show the number of failed tests for each student (a blank indicates no failed tests: equivalent to 0 failed tests). To compute the number of points you scored for a problem/in a column, compute the percentage of successful tests and multiply it by the number of points the problem is worth. So for example, if a student missed 2 of 6 tests on a 5 point problem, he/she would receive (62)/6 * 5 = 3.3 (actually, 3.333...) points. Columns PR show each student's cumulative Score, the score Rounded to an integer (that integer is the score entered in the Grades spreadsheet) and Percent, based on the number of points the assginment is worth (here 25). Readers graded problem 1 for all students and the TAs graded the function requirements for all students in their labs. The TAS will distribute these pages in labs this week only; after that, the papers will be archived in my office. The rubric for this problem was as follows: each part was worth .5 pt.
Students should talk to the TA for their Lab first, if they do not understand why they received the marks they did or dispute any of these marks. The best time to talk with your TA about grades is during one of your Labs, when both student and TA are physically present to examine the submission and the grade, possibly running the solution on a computer they can share. Students should examine their graded work immediately and get any regrade issues settled as soon as possible (within a week of when the grade is assigned). Show up to lab and settle these issues immediately. IMPORTANT Information about Student Grades

#7: 1/15/18 Programming Assignment #0 Graded 
The TAs have graded (and I have recorded the grades for) Programming
Assignment #0.
As with most assignments, there are two files that you should download, unzip,
and examine to understand your performance on this assignment, and your
cumulative performance in this class.
Both of these files are sorted by Hashed IDs (which are computed from the 8digit UCI IDs of all the students in the class). To determine your Hashed ID, see Message #6 below.
IMPORTANT: Scores wil revert to 0, if I do not receive a signed Academic Integrity Contract from you (we are tabulating them this week). Please come by during my office hours as soon as possible if you need to fix this problem. This assignment was designed to test you on whether you have mastered the basics of using Python in Eclipse, the Eclipse Debugger perspective, and batchselfcheck files in the driver.py module (in courselib). It was also designed to see if you could follow instructions and ask questions: more on that below. The class average was 28 (or about 95%) and the median was 30 (or about 100%). For those students submtting work, there were 84% As, 9% Bs, 2% Cs, and 5% Ds and Fs. The assignment was not meant to be hard, but it was not trivial either, and there were many opportunities to lose points (and learn from your mistakes). Your work in the Eclipse/Python Integrated Developement Environment (IDE) throughout the quarter will leverage off the understanding and skills that you acquired in this assignment. Let me talk about what will probably be the most contentious single point of the 1,000 points that this course is worth (thus .1% of the grade) I took off 1 point if you corrected the misspelling Inteprxter (and took off 2 points if you didn't have either spelling: in this second case you obvious failed to meet the specifications because you did not print what was required). When some students hear about this point deduction, their heads explode and they cannot believe that I am taking off a point for correcting what you thought was my mistake. But... I am trying to foster an atmosphere where nothing is taken for granted in the instructions that I give: if anything seems confusing or plain wrong, I should be questioned about it preferably in public, on a MessageBoard forum so others can learn if there really is a problem, and if so the correction.
We deducted 1 point on the demo.py program if your # Submitter line did not perfectly match what was required, including using correct spacing, punctuation, lower/uppercase letters, etc. Many students lost a point here; ensure that you know what you did wrong so you won't lose points in subsequent submissions. Also, some students did not carefully read the instructions in the Debugger Perspective document for the quiz part, which required them to change a line in the craps script before running it with the debugger to gather the required information. With this change in your program, we can check your answers for correctness; without it, we cannot check you answers for correctness. Finally, about 54% of the students submitted the program 2 or more days early; about 19 submitted the program 1 day early. So, about 73% of the students submitted this assignment early. Keep up the good work: you can earn 12 extra points if you turn in every Programming Assignment 2 or more days early (upping your grade by 1.2%): for some students, this boost will be enough to raise their final grade. Over the course of a two week assignment, it will be to everyone's benefit students and staff alike if students try to finish and submit early. IMPORTANT If you believe that we graded your work correct, please examine the files mentioned above first, then contact the TA who graded it, to discuss the issues with him/her. Such a discussion can have only positive outcomes: either he/she will agree with you that you deserve more credit (and, we do want you to receive all the credit that you are due), or you will come to understand the question, program, or solution better and realize why you lost points. This is certainly a winwin situation. Please read my solution and the assignment grades spreadsheet carefully before contacting your TA; ensure that you understand what is the correct answer and what points were deducted from your assignment and why. If there is a problem, your TA will email me a revised summary about your program, and cc a copy to you. I will update the grades spreadsheet as appropriate (it might take a bit of time for all these events to cumulate in a changed grade) and email you. If you feel there is still an unresolved problem after talking to your TA, please contact me (but always contact your TA first). Also, because of the size of this class, if you have a grading issue, we will consider it only if you bring it to your TAs attention within a week of when I return the materials. This policy is in place to avoid an avanlance of work because of "gradegrubbing" late in the quarter. 
#6: 1/8/18 Hashed ID 
When we grade assignments, we often distribute/update various spreadsheets with the relevant grading information. These spreadsheets are indexed and sorted by each student's Hashed ID. The course webpage has a Find ID Hashed (grade key) link, right below the Grades(zipped .xlsm file) link, which you can use to retrieve your Hashed ID (or click Find ID Hashed). Use the result it shows when examining any spreadsheets of grades; I suggest that you find this number once, and write it down for future reference. 
#5: 1/8/18 Important: Submitting Code without Losing Points 
ICS33 uses software that automatically grades most quizzes and programming
assignments; it uses (selfchecking) testing cases that we supply with the
testing instruments that we distribute.
You will learn about these tools in Programming Assignment #0.
Here are a few hints to ensure that you will understand the grading process
better and minimize your point loss.
After an assignment is graded automatically, the Announcement for it will contain a link to an Excel file that you can examine for detailed information about how your score was computed. If this information does not match your expectations from running the assignment's selfchecks while developing your code, contact your TA. It is best to meet with your TA during lab hours: he/she can talk to you about your code and run it while you are present, to help resolve the difference. But, if we have to modify your code to grade it properly (see the typical source of problems above), then we will deduct points. I hope that by students carefully writing/submitting their code, these grading anomalies and point deductions will be minimized during the quarter. 
#4: 1/8/18 Communication 
There are many ways to communicate with me (and other staff and students).
Here is a quick overview.
Note that for questions that are not specific to you questions that are relevant to the entire class it is best to ask them on the appropriate Message Board forum.

#3: 1/8/18 First Lab 
I expect students to attend all their scheduiled labs (unless they have
already finished the current programming assignment).
Programming Assignment #0 is assigned before the first lab of the quarter; so
if you have not already finished it, I expect you to attend your first lab
and work on it there.
Generally, you can get invaluable help in lab from the TAs and Tutors relating to

#2: 1/8/18 Install Course Software 
All students with computers should download and install the course Software:
Java (to run Eclipse), Python, and Eclipse.
All three products are available for free on the internet.
Students can view instructions for downloading and installing this software
by following the
Course Software
link.
If you are using a Mac there are special instructions for you
(e.g., Java is already installed)
If you have installed a version of Python prior to 3.6, you should install the current version of Python (and the most uptodate version of Eclipse as well, which is currently "Oxygen"). Although students can work on their programming assignments on the computers in the UCI labs, I expect students with computers to download and install this software by the end of the first week of the quarter. If you are having difficulty with this task, the TAs and Lab Tutors will help you during the first Lab meeting (or beyond, if necessary: bring your computer to the lab). If you have successfully downloaded and installed this software, please help other students do so too. Finally, you can also use the class MessageBoard Forums to ask questions about installing this software and help other students install it. I strongly suggest that you BACKUP YOUR WORK daily: computers can malfunction, break, or be stolen. 
#1: 1/8/18 First Message 
Welcome to ICS33.
I am going to post and archive important messages about the class in this
announcements web page: each entry will be numbered, dated, and labeled.
The entries will appear in reverse chronological order.
Whenever you follow the link to this page, scan its top for new announcements;
scan downward for older announcements.
This message will always appear at the bottom of this file.
I will never remove a message from this page
I have already posted some important messages before the start of the quarter. Expect a few new messages to be posted here each week, mostly regarding returned and graded work. Check this Announcements page, along with your email and the MessageBoard Forums, daily. 