DMFE

Abstract

In this paper we present DMFE (did my function execute?), which is a concept capable of learning and recognizing functional-level events, states, and loads from low-level execution-data. DMFE-functions are not necessarily software functions, as in "my_fun( )", but general functions in the etymological sense of the word, such as "someone pushed code to git", or "player activity is high". This allows DMFE to act as a general multi-purpose sensor which can be applied across a variety of software components-to be used for software monitoring, debugging, or testing-all without requiring the need for a deep understanding of the source code. Since the truth is always in the code, the main idea behind DMFE is to have the code itself "paint" execution-data on a "canvas" during run-time, and then let a deep neural network detect patterns which it associates with these functions and behaviors. We have successfully applied DMFE on internal production-code, and to illustrate how this is done we have also applied it on the two open-source projects: i) the distributed version-control system Git and ii) a text-based multi-user dungeon game Mud.