A model-based DevOps process for development of mathematical database cost models

Abstract

Obviously, the complexity of mathematical database cost models increases with the evolution of the database technology brought by emerging hardware and the new deployment platforms (ex. Cloud). This finding raises questions about the reliability of past Cost Models (CMs). Indeed, redesigning a database CM to evaluate the quality of service (QoS) attributes (i.e. response time, energy, sizing, etc.) is becoming a challenging task. First, because developers directly implement the CM by hard coding inside a DBMS without a prior design. Second, due to a lack of a stepwise development process to support an incremental CM design and continuous testing to diagnose errors that occur at each design stage. Moreover, reusing CMs for other purposes is a major issue that necessitates investigations to allow designers reusing and adapting CMs according to their needs. To take up these challenges, we propose a model-based framework for incremental design and continuous testing of Database CMs Specifically, we are motivated by proposing an approach that aims at shifting CMs design from an adhoc design to a structured and shared design by using a set of design guidelines inspired from software engineering practices. Finally, we propose to use the DevOps reuse practices (Continuous Integration/Continuous Delivery: CI/CD) to store the CM under design in a repository after each upgrade to be reused, improved, calibrated, and refined for other purposes. We evaluate our approach against common CM features, and we carry out a comparison with some analytical models from the literature. Findings show that our framework provides a high CM prediction accuracy, and identify the right design components with a precision ranging from 85% to 100%.