January 2020 Reflections

Posted by Patrick Lam on Monday, January 13, 2020

Table Of Contents

Bryan Cantrill (of dtrace fame) writes about engineering performance management.


He suggests the following five questions for engineers to answer twice a year.

  1. What are you most proud of in the last six months?
  2. What did you learn?
  3. Where did you struggle?
  4. What are you anxious about in the coming six months?
  5. What are you excited about in the coming six months?

Most proud of

Having recently removed the se-director email from my Thunderbird, I realized that this role consumed a lot of time and energy. I am most proud of having completed my term and helping students, both in the moment (advising and leading the advising team) and through program changes.


The deepest technical content I learned over the past six months was what I discussed with Laurian about the “Proofs from Tests” paper by Beckman and all. We talked about how their system abstracts the state space and creates tests to guide further abstraction.


I’d like to help my graduate students become more effective at doing research. I think that we’re having significant struggles with systems and I hope that I can be more hands-on to help overcome these hurdles. David and Ali have been in places where working together closely at a terminal has been useful, and I’d like to continue doing that (remotely).

I think we can use tmux sessions to do so:


Sabbaticals are an excellent opportunity to recharge and to reset one’s research program. I’m pretty sure that the recharging is going to happen. I’m anxious that the research isn’t going to happen as much as I’d like.


I think that our research projects are at a stage where it’s possible to make significant progress, and I hope that we can work together to make this happen. I would like to discover new knowledge, which I feel that I haven’t been doing as much of over the past few years as I’d like.

Specifically in terms of my personal research I want to look at the broader view of combining tests and static analysis, and exploring novel static analyses that statically ensure properties that are so far only tested dynamically.