Green Software Engineering: The Curse of Methodology
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[1] Abram Hindle. Green mining: A methodology of relating software change to power consumption , 2012, 2012 9th IEEE Working Conference on Mining Software Repositories (MSR).
[2] C. Davis,et al. Harnessing Green IT: Principles and Practices , 2012 .
[3] Margaret Martonosi,et al. Run-time power estimation in high performance microprocessors , 2001, ISLPED '01.
[4] Abram Hindle,et al. On improving green mining for energy-aware software analysis , 2014, CASCON.
[5] Bastin Tony Roy Savarimuthu,et al. Mining Software Repositories for Social Norms , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[6] Justyna Petke,et al. Reducing Energy Consumption Using Genetic Improvement , 2015, GECCO.
[7] Gabriele Bavota,et al. Mining energy-greedy API usage patterns in Android apps: an empirical study , 2014, MSR 2014.
[8] Ahmed E. Hassan,et al. What Do Mobile App Users Complain About? , 2015, IEEE Software.
[9] Abram Hindle. Green mining: Investigating power consumption across versions , 2012, 2012 34th International Conference on Software Engineering (ICSE).
[10] Daniel M. Germán,et al. The Impact of User Choice on Energy Consumption , 2014, IEEE Software.
[11] Eleni Stroulia,et al. The power of system call traces: predicting the software energy consumption impact of changes , 2014, CASCON.
[12] Ruzanna Chitchyan,et al. Sustainability Design and Software: The Karlskrona Manifesto , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[13] Bill Tomlinson,et al. Green tracker: a tool for estimating the energy consumption of software , 2010, CHI Extended Abstracts.
[14] William G. J. Halfond,et al. Truth in Advertising: The Hidden Cost of Mobile Ads for Software Developers , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[15] Sam Malek,et al. Component-Level Energy Consumption Estimation for Distributed Java-Based Software Systems , 2008, CBSE.
[16] Abram Hindle,et al. Green mining: energy consumption of advertisement blocking methods , 2014, GREENS 2014.
[17] Uwe Aßmann,et al. Energy Consumption and Efficiency in Mobile Applications: A User Feedback Study , 2013, 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing.
[18] Ramesh Govindan,et al. Calculating source line level energy information for Android applications , 2013, ISSTA.
[19] Maurizio Morisio,et al. Proceedings of the Fourth International Workshop on Green and Sustainable Software , 2012, ICSE 2012.
[20] Andrew Wolfe,et al. Instruction level power analysis , 1996 .
[21] Patrick Kurp,et al. Green computing , 2008, Commun. ACM.
[22] Abram Hindle,et al. What Do Programmers Know about Software Energy Consumption? , 2016, IEEE Software.
[23] Yepang Liu,et al. Diagnosing Energy Efficiency and Performance for Mobile Internetware Applications: Challenges and Opportunities , 2015 .
[24] Abram Hindle,et al. GreenMiner: a hardware based mining software repositories software energy consumption framework , 2014, MSR 2014.
[25] Eric Horvitz,et al. The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users , 1998, UAI.
[26] Alireza Sadeghi,et al. EcoDroid: An Approach for Energy-Based Ranking of Android Apps , 2015, 2015 IEEE/ACM 4th International Workshop on Green and Sustainable Software.
[27] A. Hassan,et al. What Do Mobile App Users Complain About ? A Study on Free iOS Apps , 2014 .
[28] Gustavo Pinto,et al. Mining questions about software energy consumption , 2014, MSR 2014.
[29] S. Malek,et al. An Energy Consumption Framework for Distributed Java-Based Software , 2022 .
[30] Lionel C. Briand,et al. A practical guide for using statistical tests to assess randomized algorithms in software engineering , 2011, 2011 33rd International Conference on Software Engineering (ICSE).
[31] Ivica Crnkovic,et al. Framing sustainability as a property of software quality , 2015, Commun. ACM.
[32] Denilson Barbosa,et al. Hadoop branching: Architectural impacts on energy and performance , 2015, 2015 Sixth International Green and Sustainable Computing Conference (IGSC).
[33] Ramesh Govindan,et al. Estimating mobile application energy consumption using program analysis , 2013, 2013 35th International Conference on Software Engineering (ICSE).
[34] Abram Hindle,et al. A system-call based model of software energy consumption without hardware instrumentation , 2015, 2015 Sixth International Green and Sustainable Computing Conference (IGSC).
[35] Abram Hindle,et al. A green miner's dataset: mining the impact of software change on energy consumption , 2014, MSR 2014.
[36] Abram Hindle,et al. Is HTTP/2 more energy efficient than HTTP/1.1 for mobile users? , 2015, PeerJ Prepr..
[37] Eleni Stroulia,et al. GreenAdvisor: A tool for analyzing the impact of software evolution on energy consumption , 2015, 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME).
[38] Paola Grosso,et al. A user perspective on energy profiling tools in large scale computing environments , 2015, 2015 Sustainable Internet and ICT for Sustainability (SustainIT).
[39] Gabriele Bavota,et al. Optimizing energy consumption of GUIs in Android apps: a multi-objective approach , 2015, ESEC/SIGSOFT FSE.
[40] Lori L. Pollock,et al. How do code refactorings affect energy usage? , 2014, ESEM '14.
[41] A.E. Hassan,et al. The road ahead for Mining Software Repositories , 2008, 2008 Frontiers of Software Maintenance.
[42] Ding Li,et al. An Empirical Study of the Energy Consumption of Android Applications , 2014, 2014 IEEE International Conference on Software Maintenance and Evolution.
[43] Lori L. Pollock,et al. SEEDS: a software engineer's energy-optimization decision support framework , 2014, ICSE.
[44] Jacob Aristotle,et al. Stack Overflow , 2012 .
[45] Sharad Malik,et al. Instruction level power analysis and optimization of software , 1996, Proceedings of 9th International Conference on VLSI Design.
[46] Thomas J. Ostrand,et al. \{PROMISE\} Repository of empirical software engineering data , 2007 .
[47] V. Caron,et al. United states. , 2018, Nursing standard (Royal College of Nursing (Great Britain) : 1987).
[48] Paola Grosso,et al. Energy-Efficient Networking Solutions in Cloud-Based Environments , 2015, ACM Comput. Surv..
[49] David Notkin,et al. Proceedings of the 43rd International Conference on Software Engineering , 2013, ICSE 2013.
[50] Eleni Stroulia,et al. Understanding Android Fragmentation with Topic Analysis of Vendor-Specific Bugs , 2012, 2012 19th Working Conference on Reverse Engineering.
[51] Paul M. Greenawalt. Modeling power management for hard disks , 1994, Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems.
[52] Chenlei Zhang. The Impact of User Choice and Software Change on Energy Consumption , 2013 .
[53] Ming Zhang,et al. Bootstrapping energy debugging on smartphones: a first look at energy bugs in mobile devices , 2011, HotNets-X.
[54] Abram Hindle,et al. What do programmers know about the energy consumption of software? , 2015, PeerJ Prepr..
[55] Sasu Tarkoma,et al. Energy modeling of system settings: A crowdsourced approach , 2015, 2015 IEEE International Conference on Pervasive Computing and Communications (PerCom).
[56] Abram Hindle,et al. What do programmers know about the energy consumption of software , 2015 .
[57] Abram Hindle,et al. Green mining: a methodology of relating software change and configuration to power consumption , 2013, Empirical Software Engineering.
[58] Abhik Roychoudhury,et al. Detecting energy bugs and hotspots in mobile apps , 2014, SIGSOFT FSE.
[59] Tom Mens,et al. A Historical Analysis of Debian Package Incompatibilities , 2015, 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories.