Schedule and Zoom link (SE)
The WASP Software Engineering module will be held online, via Zoom meeting.
The course will be held on June 14th, 2022 (day 1) and day two was planned for September 16th, 2022 (new sessions and the material for this will be added). Please attend all sessions - checks on attendance will be made. Two assignments will be set, one to be completed after lecture day 1, and the other one after lecture day 2.
ZOOM Link:
https://chalmers.zoom.us/j/65586345162 Links to an external site.
Zoom Password: 127660
SCHEDULE:
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DAY ONE |
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June 14th, 2022 |
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09:00 – 09:15 |
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Welcome to the Course (RF) |
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09:15 – 10:15 |
L1 |
Course philosophy, Introduction to SE, AI4SE, SE4AI: Background, terminology, basics (RF) Pre-reading: D. Sculley et al., "Hidden Technical Debt in Machine Learning Systems Links to an external site." |
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10:15 – 10:30 |
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BREAK |
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10:30 – 11:30 |
L2 |
Quality Assurance and Testing in SE, QA for ML (RF) |
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11:30 - 12:00 |
P1 |
Demo of SW testing techniques (RF) |
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12:00 – 13:30 |
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BREAK (LUNCH) |
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13:30 – 14:30 |
GL1 |
(Industry guest lecture) Regulatory compliance - Bridging the gap between legalease and SE (Christian Klein, Elastisys and Umeå University) |
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14:30 - 15:30 |
L3 |
Static analysis for SW Quality, Data validation, Data Linter, and Pynblinter (RF and LQ) Pre-reading: Hynes et al., "The Data Linter: Lightweight, Automated Sanity Checking for ML Data Sets Links to an external site." |
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15:30 – 15:45 |
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BREAK |
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15:45 – 16:15 |
P2 |
Pynblinter demo, intro to assignment 1, Q&A (LQ) |
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16:15 - 16:30 |
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Summary, intro to assignment 2, deadlines and scheduling of next day (RF) |
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Afterwards |
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COURSE ASSIGNMENT 1 (Deadline individual session: 2022-06-30, Deadline reflection report: September 15th 2022 (Day before course day 2)) |
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DAY TWO |
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Cancelled - New dates TBD |
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09:00 – 09:30 |
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Welcome to day 2 of course, short summary of day 1 and assignment 1(RF) |
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09:30 – 10:30 |
L4 |
ML Engineering, Requirements Eng for ML, ML Pipelines (RF) Pre-reading: S. Amershi et al., "Software Engineering for Machine Learning: A Case Study Download Software Engineering for Machine Learning: A Case Study" |
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10:30 – 10:45 |
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BREAK |
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10:45 – 11:30 |
L5 |
Data Scientists and SW Engineering, Human aspects in ML Eng (RF) Pre-reading: Kim et al., "Data Scientists in Software Teams: State of the Art and Challenges Download Data Scientists in Software Teams: State of the Art and Challenges" |
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11:30 - 12:00 |
P3 |
Discussion of "soft" ML Engineering (whole class) |
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12:00 – 13:30 |
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BREAK (LUNCH) |
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13:30 – 14:30 |
GL2 |
(Research guest lecture) Understanding SE via AI4SE, Automated prediction/requirements/testing, sentiment analysis (Fabio Calefato, University of Bari and RF) |
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14:30 – 14:45 |
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BREAK |
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14:45 – 15:15 |
P4 |
AutoML tools for sentiment analysis in SE (Fabio Calefato) |
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15:15 - 16:00 |
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Summary of course, intro to assignment 2 and deadlines (RF) |
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Afterwards |
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COURSE ASSIGNMENT 2 (Deadline: October 15th 2022) |
Acronyms used: RF = Robert Feldt, LQ = Luigi Quaranta, LN = Lecture number N, PN = Practice/demo session number N, GLN = Guest lecture number N