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Lodestone: A Streaming Approach to Behavior Modeling and Load-Testing

EasyChair Preprint no. 2743

8 pagesDate: February 21, 2020


It is evident that our technologically-dependent society rightly expects systems engineers to produce systems having increasing levels of performance, efficiency, and reliability. As such, we must convolve academic and industrial approaches to provide theory, systems, and working technologies which can catalyze and propel engineers, developers, and technical professionals of various disciplines toward the ultimate goal of consistent delivery of quality systems. There exist tools and processes for improving the quality-oriented posture of the systems engineering industry; in practice, the most perpetual form of software testing continues to be rote repetition of test cases through either manual testing or scripted automation of those same manual tests.

We describe Lodestone: a real-time approach for generating workload in software systems. This real-time approach to LT uses streaming log data to generate and dynamically update user behavior models, cluster them into similar behavior profiles, and instantiate distributed workload of software systems. We show that Lodestone outperforms Markov4JMeter through a qualitative comparison of key feature parameters as well through experimentation based on shared data and models.

Keyphrases: Automatic Test Pattern Generation, automatic testing, performance analysis, Software Performance, software quality, software testing, system performance, system testing

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Chester Parrott and Doris Carver},
  title = {Lodestone: A Streaming Approach to Behavior Modeling and Load-Testing},
  howpublished = {EasyChair Preprint no. 2743},

  year = {EasyChair, 2020}}
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