Day *5* Q&A - HackMD

# Day *5* Q&A   - Zoom: https://uu-se.zoom.us/j/66409709879 Passcode: 583470 # Optimization ## Q: What would be **bad advice** to improve the run-time speed of a program? - Assume you can put everything in memory - Store intermediate/stepwise parameters - Use many for-loops in Python - Implement a GPU-suitable version of your code anyways - Buy a better CPU - Comment out lines that take a lot of time/memory- Hard - too many print - Hardcode end result - don't bother looking for a function that already exists, your own will always be faster - you can do it simpler without using OOD - Just write a lookuptable for it - Remove all tests to gain speed (Lars) ## Q: What would be **good advice** to improve the run-time speed of a program? - [good advices here] - (Python) Rely on NumPy for operations involving matrices - parallelise - Use a compiled language rather than an interpreted language - Investigate code that takes most time - Keep it simple -> efficiency - parallellize - Test code regularly - identify the bottle neck (most time consuming part) and focus on optimizing that - interact with users as little as possible ## Q: When to optimize for speed? - [good advice here] - . - . # What was the most useful/interesting in the course? - Design and pairing are fun. - . - I haven't thought so much about using testing and TDD before. - Social usage of git with pull requests and issues, as well as tools for continuous integration. Also nice with good practices for clarifying/organizing the tasks with UML - design, UML, calculate big O,Git +1 - social programming good - TDD +3 - Planning the software +1 - SDLC - Social programming +3 - TDD and planning ahead of coding +3 - Development models - Most parts of the git +1 - requirement analysis ## Questions above this line ----------------------------------------------------------------- # Day 5 Retrospective Only Day 5 here :-) Please, no pointing fingers (I am sure Jon would want me to say that :-) ) ## What went well? - Pairing works much better +1 - Using HackMD for UML was very nice. +2 - learning what modules are - nice too have R examples +1 - Using HackMD to code rather than screen sharing +3 - Activity diagram +2 - Once it worked, plantUML in VS code was very nice ## What held us back? - Still material and exercise description - The presentation is less informative to follow on - did not finish all of morning lecture +1 - some changes are not staged after Git pulling. No change.. - More info about use-cases/activity diagrams. Use, differences etc. - morning exercises rushed - maybe somewhat unclear difference between use-case and activity diagrams +1 - UML issues +3 - too little time for material and exercises of morning session - profiling part was a little diffuse ## What can we improve? - spend more time on use-case and activity diagrams +3 - provide the uml code for diagram examples in lecture - Written instructions for exercises - talk more about design patterns +1 or maybe share some nice tutorials - Have a mini start-to-end exercise after the course where we can spend half the day running through a small piece of coding. Practise all of it. - Be clearcut on what to do in the exercise. - examples for optimisation showing well- and poorly-optimised examples +1 # Course Retrospective Here we have a Retrospective on the course as a whole. Please, no pointing fingers (I am sure Jon would want me to say that :-) ) ## What went well? - Pair programming +3 - Lots of exercises +2 - Windows XP background -1 - Github workflow (CI) +2 - Hand-on demos that can be used in the future +3 - Provided an opportunity for more social programming, including working in a live github repository where other people are working +1 - Frequent breaks +3 - Time for questions and answers - teachers are enthusiastic and seem to know what they're talking about - Good level of social interaction +1 - Well expereicned teachers +1 - chatting during breaks +1 - cats +4 - providing references ## What held us back? - Lars rushed through the last parts of his lectures - Too low tempo, especially in the lectures. +1 - Some excercises could be explained better. We spent a lot of time just discussing what we were supposed to do. +1 - Unclear desciption and explanation of exercises +5 - (Still) too many lectures -- Zoom fatigue - Some parts of the pair programming seems not needed - Presentations - Balance between lectures and exercises. - Skipping over content throughout the course; it gets confusing - might be helfpul to do the git stuff all together - too often told to not point fingers :finger_gun: - less reading documents after Wed. - too manny cats -6 - Different levels of preparation, everyone does not fulfill course prerequisites or preparations from last friday ## What can we improve? - If exercises or examples are related with published papers - Personally, I felt that the course was held at too low level. I was expecting more details and technical discussion, especially in the algorithm and data structure sections and I was familiar with most of the course content. In the future I would suggest that you should make it more clear what level of material to expect. +1 (but in the opposite direction - found a lot was very technical) - More focus on a project to try out all the things taught in the course. Design -> Tests -> Implementation -> Iterations - If there is an opportunity giving small group project and make presentation at the final day - The course website should be keep maintaining - No need to attempt completeness, one week is not enough -- material on top of what is discussed in documentation on GitHub -- more exercises, less lectures - provide the correct/complete presentation PDFs on GitHub - The coures was 'top-heavy'. The beginning (in my opinion) should be more interactive and with more utilities, like git, being taught. After the first day, then you can bring in more and more theory. - I think when it is online, the course is limited in several certain ways. MAybe consider on-sote class? - it would be nice to survey attendees beforehand for their favourite languages and experience with specific parts of the course - e.g some are gitmasters, some have never used git before and found it confusing af - and tailor classes appropriately - Show more "good" github repos - 🐱🐱🐱 more cats 🐱🐱🐱 +2 - additional animals +3 - Additional materials - more dogs :dog2: - more on design of larger program projects - More examples of how these things are practiced in an academic setting - if possible, work only on example project (no planets,no bacteria)