Code-level Energy Hotspot Localization via Naive Spectrum Based Testing

With the growing adoption of ICT solutions, the requirement for developing energy efficient software becomes increasingly important. Current methods aimed at analyzing energy demanding portions of code, referred to as ``energy hotspots'', often require ad-hoc analyses that constitute an additional process in the development life cycle. This leads to the scarce adoption of such methods in practice, leaving an open gap between source code energy optimization research and its concrete application. Thus, our underlying goal is to provide developers with a technique that enables them to efficiently gather source code energy consumption information without requiring excessive time overhead and resources. In this research we present a naive spectrum-based fault localization technique aimed to efficiently locate energy hotspots in source code. More specifically, our research aims to understand the viability of spectrum based energy hotspot localization and the tradeoffs which can be made between performance and precision for such techniques. Our naive yet effective approach takes as input an application and its test suite, and utilizes a simple algorithm to localize portions of code which are potentially energy-greedy. This is achieved by combining test case coverage information with runtime energy consumption measurements. The viability of the approach is assessed through an empirical experiment. We conclude that the naive spectrum based energy hotspot localization approach can effectively support developers by efficiently providing insights of the energy consumption of software at source code level. Since we use processes already in place in most companies and adopt straightforward data analysis processes, naive spectrum based energy hotspot localization can reduce the effort and time required for assessing energy consumption of software and thus make including the energy consumption in the development process viable. As future work we plan to (i) further investigate the tradeoffs between performance and precision of spectrum based energy hotspot approaches (ii) compare our approach to similar ones through large-scale experiments. Our ultimate goal is to conceive ad-hoc tradeoff tuning of performance and precision according to development and organizational needs.