Presenting Data from Experiments in Algorithmics

Algorithmic experiments yield large amounts of data that depends on many parameters. This paper collects a number of rules for presenting this data in concise, meaningful, understandable graphs that have su ciently high quality to be printed in scienti c journals. The focus is on common sense rules that are frequently useful and can be easily implemented using tools such as gnuplot1 .

• Type: Conference
• Year: 2000
• Where: DAGSTUHL
• Authors: Peter Sanders
• Keywords: Common Sense Rules, DAGSTUHL 2000, DAGSTUHL 2007, Large Amounts, Understandable Graphs