home | syllabus | groups | moodle | video | review | © 2022
Some notes on the past and future of SE
Once upon a time:
- "users" were considered to be outside of the scope of SE.
- “The notion of user cannot be precisely defined and therefore has no place in CS or SE” -- Dijkstra, ICSE4, 79
- And then ...
- "compiling" was considered not safe practice for programmers
- See "cleanrooms" and Harlan Mills, 1985.
- And then ...
- "requirements" was not an SE prolem.
- "Analysis and allocation of the system requirements is NOT the responsibility of the SE group but is a prerequisite for their work”. -- Paulk, 1993
- And then ...
- "testing" was seen as "someone else's problem" (the test team). And then ...
- "operations" was seen as "someone else's problem" (the field engineers and the maintaince team). And then ...
- "AI" was seen as separate to SE. And then ...
See other trends, below:
- Warning the following timeline might be wrong ± 5 years.
- Also if some trend is big in one decade,
- then you know that was the result of years of prior engineering.
- Computers and atomic bombs were invented at the same time, by the same people, for the same reasons.
- We live today inside their hastily (but brilliantly) conceived design assumptions.
1960: The mother of all abstractions (warning: amazing): about :: in python
- "As computers have grown more powerful,
the new languages being developed have been moving steadily toward the 'Lisp' model.
A popular recipe for new programming languages in the past 20 years has been to take the 'C'; model of computing and add to it, piecemeal,
parts taken from the 'Lisp' model, like runtime typing and garbage collection."
-- Paul Graham
1968: The Mother of All Demos (warning: long) about :: video
See also: Mythical Man (sic) Month
"For some years I have been successfully using the following rule of thumb for scheduling a software task:
- l/3 planning
- l/6 coding
- l/4 component test and early system test
- l/4 system test, all components in hand."
Pay attention: half of development is testing.
Alan Kay: the best way to predict the future is to invent it.
- If you want to see what he meant: Microelectronics and the Personal Computer Alan C. Kay Scientific American Vol. 237, No. 3 (September 1977), pp. 230-245
"The user makes his primary input through a typewriter like keyboard and a pointing device called a mouse which controls the position of an arrow on the screen."
"WINDOWS" display frames within the larger display screen, enabling the user to organize and edit information at several levels of refinement.
- Internet,
- Open Source; e.g. see Shares of Linux Firm Red Hat More Than Triple After IPO
- Internet Bubble:
1995 to 2001, massive price rises in Internet stocks. Then...
- "The bursting of the bubble caused market panic through massive sell-offs of dotcom company stocks, driving their values further down, and by 2002, investor losses were estimated at around $5 trillion."
Welcome to the attention economy.
- The age is (myth)misinformation. Information, weaponized.
Cloud
- (Some history)[https://www.dataversity.net/brief-history-cloud-computing/]
Autonomous vehicles.
AI-driven Development Is Here: Should you worry? e.g. you type:
# import a file named“observations.csv”
# and print the number of rows and columns
# then use the data to create
# a plot of the observations
and Github's copilot tool reponds woth
data = []
with open(‘observations.csv’) as csvfile:
reader = csv.reader(csvfile)
for row in reader:
data.append(float(row[0]))
print(“Number of rows: ,” len(data))
print(“Number of columns: ,” len(data[0]))
plt.plot(data)
plt.show()Warning: this code is learned from 159 Gb of code from Github. So this is very much average code with the average number of bad ideas and secutiry holes.
er... what can we say about blockchain? well...
- Aug 12, 2021: Ezra Klein, NY Times:
- If the original internet let you easily copy information, the next internet will let you easily trade ownership of digital goods.
- Crypto lets you make digital goods scarce, which increases their value; it lets you prove ownership, which allows you to buy and sell them; and it makes digital identities verifiable, as that’s merely information you own
- Together, they unlock the potential for a true economy for digital goods, where creators actually get rewarded for what they make. I will admit to some skepticism that this is how it’ll play out, as many of the financiers funding crypto also founded and sit on the boards of the companies that set the terms of today’s internet, but we’ll see.
- Jun 29, 2022:
A: none of them.
And the language you use next is probably not the one you are using now:
- Empirical Analysis of Programming Language Adoption Leo A. Meyerovich, Ariel Rabkin, OOPSLA ’13.
And even if you are working on some language/tool now, if your work changes, that could change too
Projects are build from 2-5 Programming Languages
- Mayer, Philip, and Alexander Bauer. "An empirical analysis of the utilization of multiple programming languages in open source projects." Proceedings of the 19th International Conference on Evaluation and Assessment in Software Engineering. 2015.
- Tomassetti, Federico, and Marco Torchiano. "An empirical assessment of polyglot-ism in github." Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering. 2014.
An average engineer routinely uses 7 PLs:
- Mayer, Philip, Michael Kirsch, and Minh Anh Le. "On multi-language software development, cross-language links and accompanying tools: a survey of professional software developers." Journal of Software Engineering Research and Development 5.1 (2017): 1.
How to learn so many languages:
- Cross-language self-tutoring
- If you can do X in language1, find out how to do X in language2;
- Jean Scholtz and Susan Wiedenbeck. 1990. Learning second and subsequent programming languages: A problem of transfer. International Journal of Human-Computer Interaction 2, 1 (1990), 51–72.
- N. Shrestha, T. Barik, and C. Parnin. 2018. It’s Like Python But: Towards Supporting Transfer of Programming Language Knowledge. In 2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). 177–185.
Programmers don't just program:
- Tom Zimmermann, Microsoft
- If you think of a typical software engineer at Microsoft, they spend about half of a day on development related activities, and the other half of the day is spent on other activities like coordinating with other people in meetings, sending emails.... So, there’s actually not that much time that they can spend on writing code, and the time they spend writing code, on a good day, it’s actually only 96 minutes, and on a bad day it’s, on average, 66 minutes. And half an hour writing code actually can make the difference between a bad and a good workday.
What else do "programmers" do:
- Convincing you that the system is trustable
- Helping you when the systems fails
Current roles of software engineering experts when adopting data mining approaches:
- Problem definition.
- Data collection.
- Data “surrogates” (when the joins fail you)
- Model building.
- Managing organizational impact
- MINKU, L.L.; MENDES, E.; TURHAN, B. . "Data Mining for SE and Humans in the Loop", Progress in Artificial Intelligence (PRAI), 5(4), 307-314, Nov 2016
Programmers are the people who know when not to program:
- Exhibit A: Ken Thompson, of Unix and C fame, once said "One of my most productive days was throwing away 1000 lines of code."
- Exhibit B: programmers know that not all openned issues should be closed
