generators as needed. Definition: A generator function returns an iterator that yields a value each time it executes a yield statement. After it yields a value, the runtime state of the generator function way of “faking” the overloading behavior. Cons: Default arguments are evaluated once at module load time. This may cause problems if the argument is a mutable object such as a list or a dictionary. If the Yes: def foo(a, b=None): if b is None: b = [] No: def foo(a, b=[]): ... No: def foo(a, b=time.time()): # The time the module was loaded??? ... No: def foo(a, b=FLAGS.my_thing): # sys.argv has not yet been

(and most individ- ual components submitted to it) is expected to continue for quite some time. As a result, more time will be spent reading most of our code than writing it. We explicitly choose to optimize is specifically important for our codebase because code ownership and team membership changes over time: even if everyone that works with some piece of code currently understands it, such understanding function, or template without an associated definition. • Forward declarations can save compile time, as #includes force the com- piler to open more files and process more input. 4 • Forward declarations

2011 PhD TU Dresden, Germany  Cost-based optimization of integration flows  Systems support for time series forecasting  In-memory indexing and query processing Data Management Group DB group https://github 4 years, 237 pages  1st book, 5+2 years, 157 pages Structure of Scientific Papers Your reader’s time is a scarce resource 15 706.015 Introduction to Scientific Writing – 01 Introduction and Overview with collaborators and friends  Develop your taste for good research topics  Topic selection needs time  pipeline model  Ex. Compressed Linear Algebra  Problem: Iterative ML algorithms + memory-bandwidth-bound

 Postpone implementation and experiments till last before the deadline  No feedback, no reaction time (experiments require many iterations)  Karl Popper: falsifiability of scientific results  refutable Presentation – Figures  Axes  Use Informative axes labels with units (e.g., Total Execution Time [ms])  Don’t cheat or mislead readers and reviewers  Start y-axis at 0 for linear scale Experiments 1016330404 LLC-load-misses # 30.11% of all LL-cache hits (50.00%) 152.096000108 seconds time elapsed 12052.466691000 seconds user 674.704421000 seconds sys Don’t just report the results but try

horizon  Lots of similarities to code reviews in OSS  Learning by What NOT to Do  Accept if no time to review  The Goldilocks Method (examples, proofs, theoretical analysis, experiments)  If you filter)  Make the paper useful for others (ideas, evidence, code)  #4 Easily Readable: Quality ∝ Time  Make it easy to skim the paper  paragraph labels, self-explanatory figures (close to text), and publishing forum or presentation venue, including conferences, workshops, and journals, during the time it is being considered for SIGMOD. Furthermore, after you submit a research paper to SIGMOD, you

if/else-if/else or try/catch/finally). Example: void doNothing() {} 4.2 Block indentation: +2 spaces Each time a new block or block-like construct is opened, the indent increases by two spaces. When the block