This paper introduces the concept of energy debt: a new metric, reflecting the implied cost in terms of energy consumption over time, of choosing a flawed implementation of a software system rather than a more robust, yet possibly time consuming, approach. A flawed implementation is considered to contain code smells, known to have a negative influence on the energy consumption.Similar to technical debt, if energy debt is not properly addressed, it can accumulate an energy "interest". This interest will keep increasing as new versions of the software are released, and eventually reach a point where the interest will be higher than the initial energy debt. Addressing the issues/smells at such a point can remove energy debt, at the cost of having already consumed a significant amount of energy which can translate into high costs. We present all underlying concepts of energy debt, bridging the connection with the existing concept of technical debt and show how to compute the energy debt through a motivational example.
CCS CONCEPTS• Software and its engineering → Automated static analysis; Software performance.
It has become a common procedure to acquire electrical data for environmental surveys with multi-core cables and multi-channel readers. These systems use pre-loaded protocols that instruct the relay box to combine the electrodes in hundreds of possible arrangements. When acquiring Induced Potential (IP) data, there is always a fear of electromagnetic (EM) coupling on the cables and polarization effects on the steel electrodes. As a precaution, current cables are usually separated from the potential cables and non-polarizable electrodes are used for potential readings. This also implies that special care must be taken when writing the acquisition sequence protocols. All these precautions increase considerably the time needed to assemble and disassemble a line thus leading to greater cost and lesser production. In this work, the effects of multi-core cables and non-polarizable electrodes on shallow time-domain IP surveys are analyzed from a practical point of view. It is shown that, if the instrument is able to perform Self Potential (SP) correction before integration, the results obtained with stainless steel electrodes and multicore cables are virtually the same as those obtained with separate cables and non-polarizable electrodes.
This paper extends previous work on the concept of a new software energy metric: Energy Debt. This metric is a reflection on the implied cost, in terms of energy consumption over time, of choosing an energy flawed software implementation over a more robust and efficient, yet time consuming, approach.This paper presents the implementation a SonarQube tool called E-Debitum which calculates the energy debt of Android applications throughout their versions. This plugin uses a robust, well defined, and extendable smell catalog based on current green software literature, with each smell defining the potential energy savings. To conclude, an experimental validation of E-Debitum was executed on 3 popular Android applications with various releases, showing how their energy debt fluctuated throughout releases.
CCS CONCEPTS• Software and its engineering → Automated static analysis; Software performance.
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