Observation-Driven Configuration of Complex Software Systems
Aled Sage

TL;DR
This paper presents an approach using automated experiments and Taguchi Methods to efficiently configure complex software systems, demonstrated through a case study on DC-Directory.
Contribution
It introduces the novel application of Taguchi Methods for software system configuration, combined with an automated experimental framework, ACT.
Findings
Taguchi Methods effectively model and optimize software configurations.
Automated experiments help identify configurations meeting stakeholder needs.
The approach is validated through a successful case study on DC-Directory.
Abstract
The ever-increasing complexity of software systems makes them hard to comprehend, predict and tune due to emergent properties and non-deterministic behaviour. Complexity arises from the size of software systems and the wide variety of possible operating environments: the increasing choice of platforms and communication policies leads to ever more complex performance characteristics. In addition, software systems exhibit different behaviour under different workloads. Many software systems are designed to be configurable so that policies can be chosen to meet the needs of various stakeholders. For complex software systems it can be difficult to accurately predict the effects of a change and to know which configuration is most appropriate. This thesis demonstrates that it is useful to run automated experiments that measure a selection of system configurations. Experiments can find…
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Taxonomy
TopicsAdvanced Software Engineering Methodologies · Software Engineering Research · Software Reliability and Analysis Research
