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D
Davidson, JE.  2005.  Evaluation Methodology Basics: The Nuts and Bolts of Sound Evaluation. :280. Abstract
Delling, D, Demetrescu C, Johnson DS, Vitek J.  2016.  Rethinking Experimental Methods in Computing (Dagstuhl Seminar 16111). Dagstuhl Reports. 6:24–43. Abstract
Denning, PJ.  1981.  ACM president's letter: performance analysis: experimental computer science as its best. Commun. ACM. 24:725–727.
Denning, PJ.  2005.  Is Computer Science Science? Commun. ACM. 48:27–31. Abstract
Dittrich, J.  2010.  Paper Bricks: An Alternative to Complete-Story Peer Reviewing. SIGMOD Record. 39(4) Abstract
Drummond, C.  2009.  Replicability in not Reproducibility: Nor is it Good Science. The 4th workshop on Evaluation Methods for Machine Learning. Abstract
Druschel, P, Isaacs R, Gross T, Shapiro M.  2006.  Fostering Systems Research in Europe: A White Paper by EuroSys, the European Professional Society in Systems. Abstract
E
Eide, E, Stoller L, Lepreau J.  2007.  An experimentation workbench for replayable networking research. Proceedings of the 4th USENIX conference on Networked systems design & implementation. :16–16. Abstract
Eisenberg, M.  2003.  Creating a computer science canon: a course of "classic" readings in computer science. Proceedings of the 34th SIGCSE technical symposium on Computer science education. :336–340.
F
Feitelson, DG.  2006.  Experimental Computer Science: The Need for a Cultural Change. Abstract
Fenton, NE, Pfleeger S L.  1998.  Software Metrics: A Rigorous and Practical Approach.
Feynman, R.  1974.  Cargo Cult Science. Engineering and Science. 37(7):10-13. Abstract
Fleming, PJ, Wallace JJ.  1986.  How Not to Lie with Statistics: The Correct Way to Summarize Benchmark Results. Commun. ACM. 29:218–221. Abstract
Frachtenberg, E, Feitelson DG.  2005.  Pitfalls in parallel job scheduling evaluation. Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing. :257–282. Abstract
G
Georges, A, Eeckhout L, Buytaert D.  2008.  Java performance evaluation through rigorous replay compilation. Proceedings of the 23rd ACM SIGPLAN conference on Object-oriented programming systems languages and applications. :367–384. Abstract
Georges, A, Buytaert D, Eeckhout L.  2007.  Statistically rigorous java performance evaluation. OOPSLA '07: Proceedings of the 22nd annual ACM SIGPLAN conference on Object-oriented programming systems and applications. :57–76. Abstract
Gil, J Y, Lenz K, Shimron Y.  2011.  A microbenchmark case study and lessons learned. Proceedings of the compilation of the co-located workshops on DSM'11, TMC'11, AGERE!'11, AOOPES'11, NEAT'11, &\#38; VMIL'11. :297–308. Abstract
H
Hanenberg, S.  2010.  Faith, hope, and love: an essay on software science's neglect of human factors. Proceedings of the ACM international conference on Object oriented programming systems languages and applications. :933–946. Abstract
Hoefler, T, Belli R.  2015.  Scientific Benchmarking of Parallel Computing Systems: Twelve Ways to Tell the Masses when Reporting Performance Results. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. :73:1–73:12. Abstract
Höst, M, Wohlin C, Thelin T.  2005.  Experimental context classification: incentives and experience of subjects. Proceedings of the 27th international conference on Software engineering. :470–478. Abstract
Huff, D.  1954.  How to Lie with Statistics.
I
Ioannidis, JPA.  2005.  Why Most Published Research Findings Are False. PLoS Medicine. 2:e124. Abstract
J
Jain, R.  1991.  The Art of Computer Systems Performance Analysis: techniques for experimental design, measurement, simulation, and modeling.
K
Kaiser, JF.  2010.  Richard Hamming - You and Your Research. Simula Research Laboratory. :37-60. Abstract
Kalibera, T, Jones R.  2013.  Rigorous Benchmarking in Reasonable Time. Proceedings of the 2013 International Symposium on Memory Management. :63–74. Abstract