Waterfall?

I don’t teach methodology per se in my software engineering class, at least not the explicit sequence of waterfall, iterative, and agile. I do discuss a bit about sequencing activities, the notion of a wicked problem, etc. We, in fact, iterate a piece of software.

But as with the idea of a software crises, I’m worried about our standard narratives. This blog post points to discussions of how waterfall was ever a thing and how iterative methods were proposed very early on.

I suspect that some of our hoary old narratives are just things we say. I’m not sure software is all that different from buildings or that other sorts of engineering have all that easy a time.

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Fail Fast Textbook Selection

I’m strongly considering changing my reading material for my software engineering class. I like Code Complete in a lot of ways, but it really does feel a bit old and a lot of bits are not super well organised or presented. And it’s big without being super nicely modularised. It’s not really a textbook. I’m planning a pretty significant reworking of the course (to consolidate some stuff) so this is the time to change.

I was looking at a text that has some good reviews and decent presence on Open Syllabus and a metric ton of supporting material. I’ve never used supporting material but one can see the attraction!

I’m skimming a copy starting with the intro. The intro of text tends to be a really weak bit especially if it’s didactic instead of tutorialesque, so I forgave the cutesy intro dialogue. There were some helpful fake graphs about characteristic error rates which seemed fun. Then I hit the following description in a list of “kinds of software”:

Artificial intelligence software—makes use of nonnumerical algorithms to solve complex problems that are not amenable to computation or straightforward analysis. Applications within this area include robotics, expert systems, pattern recognition (image and voice), artificial neural networks, theorem proving, and game playing.

Say what? “Nonnumerical algorithms”?!?!?! Right before talking about artificial neural networks??!?! Maaaaybe there’s a specialised enough variant of “numerical algorithm” (written primarily in Fortran?!?) where this is technically not wildly false, but it sure the hell is misleading here (given the standard distinction between symbolic and non-symbolic AI). Seriously bonkers.

But…ok. Does one extremely boneheaded bit of a sort of throwaway warrant tossing the whole thing? Maybe? I want to be fair. I can always guard against this in lecture…I guess. Then I hit:

  • Software has become deeply embedded in virtually every aspect of our lives, and as a consequence, the number of people who have an interest in the features and functions provided by a specific application has grown dramatically. When a new application or embedded system is to be built, many voices must be heard. And it sometimes seems that each of them has a slightly different idea of what software features and functions should be delivered. It follows that a concerted effort should be made to understand the problem before a software solution is developed.

Oy. I mean, the dude has chapters on iterative and agile processes, so there’s some course correction. But. Come. ON!

Ok, now I dump it from the list.

Some Query Links

I have a buncha tabs about SQL and query optimizations. So a bit of clean up:

Lots more tabs to be cleaned.

A Week of Blogging Fail

I went a whole week without blogging. BOO! I was commenting a bit more on LGM but really illness and class knocked me out. And then it snowballed.

I’ll try to post two a day for this week. But it might be slapdash.

My anxiety was brutal last week as I had to prepare a new class with material I inherited which was challenging to interpret much less prep.

Plus figure out how the changes affected the coursework. Yeek.

Per usual, it worked out. Per usual, it cost me an all nighter.

The lecture itself felt really really good. I’m working on whole class participation and I think it was working ok. I did a retrospective of the prior week first as outline and then again as slide snippets. I was able to emphasize how they should be pulling things to get in their heads. Then we applied it to the new material.

I came out tired and happy. And with a brutal sore throat. I also manage to spill not so hot tea over me and the desk. Yay.

Another 61511 Done

Four years ago, I made a push to change how we teach software engineering at the MSc level. I had ambitious plans about how to change the whole sequence, but I was going to start by taking over the first class in the sequence.

The first year was super tough as the person who has been teaching it took medical retirement (sadly). My early ideas just weren’t workable given me and the cohort.

I completely revamped it, esp the coursework and have edge closer and closer to something which has some good innovation. It needs another overhaul but this year went pretty smoothly (still some coursework marking to go).

I won’t said it’s best of breed because I don’t have a lot of comparisons. But it seems good and rather interesting. One class out of four isn’t enough to be transformative but it’s a start!

Plus I taught the whole day with a unicorn horn on my head. Good times!

Not An Easier Week

I thought it was going to be an easier week. Buuut…MSc project grading (done!), three exams to write (whoa, those are hugely not done), class prep (Not Done sob), and a programming contest (somewhat advanced)….it’s a bit much.

Sometimes, I can harness this pressure, but usually closer to the wire. Which I want to avoid!

Oh well. Next week is the last week of period 1. Now, I have a class in period 2 to panic over. Yay.

Grading Postmortem

I just finished the followup of grading a programming/software engineering assignment with a mostly automated toolkit. The goal was to have “next class” turnaround. It wasn’t quite same day but it was definitely within 20 hours, for the bulk of people. Some of the problem was that Blackboard is terrible. Just terrible. It refused to upload marks and feedback for people who had had multiple submissions and then sent me into a hellscape to try to enter them manually. So there were some upload errors (2 people didn’t have any feedback and a 1 had the wrong feedback due to cut and paste fail). Out of 49 submissions, I had 17 people report a problem or request a regrade. Of those 5 resulted in a change of mark for a total of 19 marks added (the total possible for each was 10 per assignment so 490 total ; 170 were originally given thus 10% of “rightful” marks went missing and needed a manual update; one of these was due to a rouge extra submission after the deadline that was the wrong one to grade for 3 points, so 8.5 missing marks were due to grader bugs).

Now the people with wrong marks generally got “0” often when it was obvious that they shouldn’t have. This was because their program would either crash in a new way or return a really unexpected result. In the later case, since we try to parse the program out put, we’d through an expected exception for that odd output. In both scenarios, this unexpected scenario would crash the grader before it wrote any feedback. Missing feedback was inferred to be an “upload” problem so the students got 0 and an unhelpful error message.

These were stupidly hard bugs to track down! But they point to a couple of holes in our robustness and test isolation approach (we’re generally pretty good on that). In general, I’d like to review the 0s before uploading to confirm but the tight time frame was just too much. It was a tradeoff between the real anxiety, pain, and confusions some students would feel at getting an erroneous 0, and delaying feedback. It’d have been great if I could have turned around the corrections more quickly, but I have only so much time and energy. All students who filed an issue got a resolution by the subsequent Monday evening at the latest. So, two full days with correct feedback before the next assignment. Obviously, quicker is always better, but this isn’t unreasonable.

At least two people were misled by the feedback which basically said “You are missing this file” when it should have said “You are missing at least one of this file or that directory.” Oops! That was mostly work for me than anything else.

In the same day lab, the students did an over the shoulder code review of each other’s first assignment. I wish I had gathered stats on problems found. I told everyone who wanted to file an issue to send me an email aftertheir code review discovered no problems and they had some simple test cases passing. In many of those cases, there were very obvious problems that a simple sanity test would have revealed and oddities in the code which lept out (to me).

I feel this justifies my decision not to return granular feedback or explicit tests. The program is very small and they have an oracle to test against (they are reverse engineering a small unix utility). The points awarded are few and  2 come from basically not messing up the submission format. 1 comes from following the spec requirement to use tabs as an output separator.

But the goal of these assignments is to get people thinking about software engineering, not programming per se. They need to reflect on their testing and release process and try to improve them. I had several students ask for detailed feedback so they would lose fewer marks on the next assignment and that’s precisely what I don’t want to do. The learning I’m trying to invoke isn’t “getting this program to pass my tests” but “becoming better at software engineering esp testing and problem solving and spec reading and…”.

It’s difficult, of course, for students to care about the real goals instead of the proxy rewards. That’s just being a person! All I can do is try to set up the proxy rewards and the rest of my teaching so as to promote the real goal as much as possible.

Giving students low marks drives a lot of anxiety and upset on my part. I hate it. I hate it because of their obvious suffering. I hate it because it can provoke angry reactions against me. I hate it because I love seeing people succeed.

But it seems necessary to achieve real learning. At least, I don’t see other ways that are as broadly effective.