Runtime Monitoring in Continuous Deployment by Differencing Execution Behavior Model

Abstract

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An interview study about the use of logs in embedded software engineering

“…Indeed, as discussed by the interviewed developers, when logging software systems, developers need to make several trade-offs. A significant amount of effort has been made in the research community to study such questions as where to log (Fu et al 2014;Li et al 2018), what to log (Zhu et al 2015), how to log (Chen et al 2017) and how to use logs (Gupta et al 2018); and such challenges as absence of logs (Li et al 2020a), non-standard logging (Pecchia et al 2015), and presence of noise and incomplete logging (Li et al 2020a).…”

Augmenting Diffs With Runtime Information

“…Execution logs are one of the sources that can be used to model the execution behavior [38]. Goldstein et al [39] present an algorithm to visualize behavioral differences using execution logs in four steps.…”

Single-state state machines in model-driven software engineering: an exploratory study

“…In addition, given the caused permissive verification is perceived as a risk by our interviewees, we suggest proposing possible alternatives to SSSM-IMs by investigating the order in which events are actually being called during system operation. One can consider analysing the execution traces of the generated code with pattern mining techniques widely studied in the field of model learning (Yang et al 2019;Wieman et al 2017;Aslam et al 2018), specification mining (Lemieux et al 2015;Lo et al 2011) andprocess mining (van der Aalst 2011;van der Werf et al 2009;Gupta et al 2018).…”