Programming Languages

Paul R Eggert

Programming Languages

Computer Science department

Paul R Eggert

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from 71 users

Ratings

Bad
Overall 3.1
Good
Hard
Easiness of class 1.6
Easy
Heavy
Workload 1.7
Light
Not Clear
Clarity of professor 3.2
Clear
Not Helpful
Helpfulness of professor 3.3
Helpful
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Tags

  • Tough Tests
  • Needs Textbook
  • Engaging Lectures
  • Useful Textbooks
  • Tolerates Tardiness
  • Appropriately Priced Materials

Grades

Spring 2020
27.5%
22.9%
18.3%
13.7%
9.2%
4.6%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Winter 2020
27.3%
22.7%
18.2%
13.6%
9.1%
4.5%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2020
23.0%
19.1%
15.3%
11.5%
7.7%
3.8%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Spring 2019
19.5%
16.3%
13.0%
9.8%
6.5%
3.3%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Winter 2019
19.6%
16.3%
13.0%
9.8%
6.5%
3.3%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2019
20.0%
16.7%
13.3%
10.0%
6.7%
3.3%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2018
25.0%
20.8%
16.7%
12.5%
8.3%
4.2%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Winter 2017
20.7%
17.3%
13.8%
10.4%
6.9%
3.5%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2017
25.5%
21.2%
17.0%
12.7%
8.5%
4.2%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Winter 2016
22.3%
18.6%
14.9%
11.2%
7.4%
3.7%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2016
22.7%
18.9%
15.1%
11.3%
7.6%
3.8%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Spring 2015
23.6%
19.7%
15.7%
11.8%
7.9%
3.9%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Winter 2015
19.7%
16.4%
13.1%
9.8%
6.6%
3.3%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2015
23.0%
19.1%
15.3%
11.5%
7.7%
3.8%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Spring 2014
22.4%
18.7%
14.9%
11.2%
7.5%
3.7%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Winter 2014
29.0%
24.2%
19.4%
14.5%
9.7%
4.8%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Winter 2013
29.3%
24.4%
19.5%
14.7%
9.8%
4.9%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2012
29.5%
24.6%
19.7%
14.7%
9.8%
4.9%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Spring 2010
31.3%
26.0%
20.8%
15.6%
10.4%
5.2%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Winter 2010
24.3%
20.3%
16.2%
12.2%
8.1%
4.1%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2009
25.4%
21.2%
16.9%
12.7%
8.5%
4.2%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Spring 2006
35.7%
29.8%
23.8%
17.9%
11.9%
6.0%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

Fall 2006
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

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2 of 6

Reviews

Quarter Taken: Fall 2019 Submitted Dec. 5, 2019 Grade Received: N/A

Eggert, as a lecturer, is very enthusiastic and knowledgable. I can tell he is super passionate about computer science and knows a ton. However, the workload and rigor of this class is TOO MUCH. I can barely catch a break while I was in this class. The professor's lectures were all over the place, with no clear direction and random concepts thrown in as a mush. I still do not understand many of the concepts of the class. Eggert's exams were impossible to study for, as he just puts whatever he wants. Overall, I applaud him for being a good lecturer, but the course needs to be organized better.

Quarter Taken: Spring 2020
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
Submitted May 28, 2020
Grade Received: I

I think I learned a lot from this course, but at the expense of my mental health unfortunately. The lectures are a bit all over the place in terms of organization, and it is sometimes difficult to know what are the essential concepts to take away from a lesson are. I do appreciate the professor's enthusiasm and extensive domain knowledge on the subject, and his little tidbits and asides kept the lectures from being dull. He is also really good at addressing questions that are brought up during lecture and is approachable in that regard. Overall, the lectures were very informational, but not very digestible. Sometimes the "bigger picture" was lost in the focus on minute details.

The homework/projects, on the other hand, are an utter mess. I wish I was being hyperbolic. The assignments are written in a way that almost seems like they are intentionally trying to be confusing and frustrating for students. I quickly learned that there is very little point in starting the homework before discussion section because it is simply not worth my time to decipher (and probably misinterpret) the assignment. Luckily, the TAs are great in filling the gaps in this respect, but their absolute necessity to make any meaningful progress on the assignments is very telling of their quality. Keeping updated on every Piazza post is a must to not lose points on arbitrary requirements that were mentioned vaguely, if at all in the assignment. For example, the Scheme parsing assignment is nearly impossible to complete by just reading the very open-ended specifications -- you almost have to code against the already additional sample test cases provided by the TAs to have a chance to do well or spend hours writing code to handle edge cases at random. This was especially frustrating because new test cases would be updated multiple times throughout the assignment period, though I am at least thankful they existed to make up for the shortcomings of the specification.

The stress of these assignments that many students complain about come from this dispiriting experience of programming based on assumptions that they are forced to make while waiting on TA's to confirm/deny via Piazza. It is sad to say that it is actually a viable strategy to wait for these Piazza clarification posts before starting the assignment. Overall, even though the assignments could be better formulated, I did feel like I learned a lot about the different programming styles by completing them. It's just a shame that my experience had to be this way, and although I think the TAs did a great job considering these circumstances, the course should be able to stand on its own.

Quarter Taken: Winter 2021
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
Submitted March 29, 2021
Grade Received: C+

I made the mistake of not githubing anything in this class. I know the material really well did remarkably well in the homework (as in lost points only because I submitted late), but you need only look at my grade to see how that turned out.

Here's a few tips for the class if you're looking for a good grade:
1) Don't try. Really. Just github all the projects. You'll need the high grades on homework since everyone else is githubbing too and they'll have perfect scores.
2) BS on the exam. You may know how to code well on all the languages and understand the concepts, it won't matter. You need to write as much as you can using words that pop up in lecture. Don't paraphrase.
3) If you're taking exams online, cheat as much as you can. They won't be able to tell as there is no way to tell.
Do yourself a favor, do what CS35L really tried hard to teach you to do: Copy, steal and lie.

If on the other hand you actually want to learn something in this crap class do all the projects yourself, read the textbook and try to understand by digging deeper into every concept.
You will learn a lot. I'm a better programmer because of this class. I'm a worse student however as my GPA says.
I am also a smarter human because of it too! I know now that you need to take advantage of everything you can regardless of whether it is fair or honest. I don't know if that was the lesson Professor Eggert was trying to give, or if he even cares enough to give any lesson.

I am bitter because of my results in this class, but at least I learned a lot.

Quarter Taken: Fall 2020
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
Submitted Dec. 29, 2020
Grade Received: A

It's hard. The midterm was already difficult, and then the final took it to another level. One of the questions could legitimately be a Scheme homework assignment. Generally speaking, there are three types of exam questions:

- Rote: Implementing a simple function, drawing syntax diagrams, etc. This is as close to free points as you're gonna get, so I try to do these first.
- Discussion: I save them for last since they're pretty easy to BS. On the flip side, the TA's will often have a random reason to dock points.
- Cool stuff: Occasionally there will be a question that is like a logic puzzle. The answer was not discussed in class exactly, but you can arrive at it with a solid understanding of the course material. Probably where people lose most points.

Overall, there is no difference between remote and non-remote Eggert exams; they're still timed and he still writes them the day before.

On the other hand, the homeworks are extremely fair. The spec contains a lot of test cases, and if you pass all of them you're almost certainly going to score perfectly. Not to mention the exponential decay penalty for late submission :chef_kiss:

Quarter Taken: Winter 2020 Submitted April 1, 2020 Grade Received: A

Ok so this is probably an unpopular opinion but I didn't find 131 to be as tough as people make it out to be. Yes it's still hard. Yes I still struggled. And I'm surprised I got an A (was honestly expecting a B+) so hear me out:

I took CS33 with him and that was an absolute madhouse so I was prepared for 131 to be so much worse but was surprised when it wasn't. I actually understood what he was talking about for like 70% of lectures and the stuff that I didn't get I would go online and read articles, watch YouTube, and go through the textbook to make sense of it. If you go into the class with the mindset of being ready to work hard, you will learn a lot in this class. The textbook was really helpful to read (it doesn't cover everything though) but it's a good way to gain a simple understanding of material if you have no idea what's happening.

The TAs are all super good and super active on piazza and also had hint code on github for us to refer to (tbh it wasn't that helpful after the first homework). Homeworks 2 and 5 (Scheme) were the hardest imo. It's difficult conceptually to wrap your head around let alone code yourself so be prepared to be super frustrated with these. Homeworks 3 and 6 were the easiest and took like 2 and 4 hours respectively. It's really important that you put in effort for the project report and HW6 because these are more conceptual and high level and are more than likely to be tested.

Also, I took 111 with Harry Xu before 131 and I think that helped me out a little bit because I had the analytical skills of weighing pros/cons that you do a lot in 111.

Tests are open notes like usual and our midterm average was like 70% which is ridiculously high for an Eggert test and most people thought that this midterm was easy. It definitely felt more straightforward and the questions weren't as convoluted as usual. The final was online because of the whole COVID-19 situation and the average was bout 65% which is again, super high but we had open internet access and 24 hours to do the test.

Quarter Taken: Fall 2019 Submitted Nov. 25, 2019 Grade Received: NR

nothing new, homie Eggert, "interesting" exams, annoying specs, satisfying curves :|

Quarter Taken: Spring 2020
COVID-19 This review was submitted during the COVID-19 pandemic. Your experience may vary.
Submitted May 27, 2020
Grade Received: P

Honestly after taking 35L and 111 with Eggert I thought it couldn't get any worse but it does. This is hands down the most useless class I've ever been apart of. The amount of work involved with it is absolutely insane(much more than his 111 IMO), and his "late policy" is just his way of assigning more work than can be done in class.

For the Prolog section, he started going over the language the day the homework was due. Python project is due in less than 48 hours and he hasn't spoken about Python of TCP once haha. It's absolute madness. They need to rework this entire class. Remove one of the OCAML homeworks and maybe you could have a decent schedule.

Quarter Taken: Fall 2019 Submitted Feb. 25, 2020 Grade Received: N/A

The projects are moderately hard. The midterm and final are ridiculously hard. Open book and open notes will help you little. If you want your effort to be paid off reasonably, avoid him at all costs.

Quarter Taken: Fall 2017 Submitted Feb. 11, 2018 Grade Received: A

宝儿作为在职的软件工程师 讲他做喜欢的软件工程(不是计算机科学)
看得出来满腔热情
思路很快 得保持全神贯注
能学到很多

Quarter Taken: Winter 2019 Submitted June 29, 2019 Grade Received: B

Get ready to spend countless hours a week on these insane projects, especially the first two. Eggerts lectures are very interesting but often are not remotely useful to the homework until AFTER the assignments are due. Midterm and final are a guessing game of what might be on them, pray that you are able to take this class with Millstein instead.

2 of 6

Tags

  • Tough Tests
  • Needs Textbook
  • Engaging Lectures
  • Useful Textbooks
  • Tolerates Tardiness
  • Appropriately Priced Materials
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