I.D. Coman∗ and A. Sillitti∗


  1. [1] S.L. Pfleeger, Lessons learned in building a corporate metricsprogram, IEEE Software, May 1993, 67–74.
  2. [2] M. Daskalantonakis, A practical view of software measure-ment and implementation experiences within Motorola, IEEETransactions on Software Engineering, 18 Nov 1992, 998–1010.
  3. [3] A. Gopal, M.S. Krishnan, T. Mukhopadhyay, & D.R. Golden-son, Measurement programs in software development: Determi-nants of success, IEEE Transactions on Software Engineering,28(9), 2002.
  4. [4] A.M. Disney & P.M. Johnson, Investigating data quality prob-lems in the PSP, 6th Intl. Symposium on the Foundations ofSoftware Engineering, Orlando, USA, 1998.
  5. [5] P.M. Johnson & A.M. Disney, A critical analysis of PSPdata quality: Results from a case study, Journal of EmpiricalSoftware Engineering, 1999.
  6. [6] C.A. Moore, Project LEAP: Personal process improvement forthe differently disciplined, Proc. of ICSE, 1999, 726–727.
  7. [7] J. Henry,
  8. [8] P.M. Johnson, H. Kou, J. Agustin, C. Chan, C. Moore,J. Miglani, S. Zhen, & W.E.J. Doane, Beyond the per-sonal software process: Metrics collection and analysisfor the differently disciplined, Technical report, July 2002,
  9. [9] M. Kersten & G. Murphy, Mylar: A degree-of interest Modelfor IDEs, 4th Conference on Aspect-Oriented Software Devel-opment, 2005.
  10. [10] M.P. Robillard & G. Murphy, Automatically inferring concerncode from program investigation activities, 18th InternationalConference on Automated Software Engineering, 2003, 225–234.
  11. [11] M.P. Robillard & G.C. Murphy, Program navigation analysis tosupport task-aware software development environments, Proc.of ICSE Workshop on Directions in Software EngineeringEnvironments, 2004, 83–88.
  12. [12] I.D. Coman & A. Sillitti, Automated identification of tasks indevelopment sessions, Proc. of Intl. Conference on ProgramComprehension, 2008.
  13. [13] A.J. Ko, B.A. Myers, M.J. Coblenz, & H.H. Aung, An ex-ploratory study of how developers seek, relate and collect rel-evant information during software maintenance Tasks, IEEETransactions on Software Engineering, December 2006.
  14. [14] I.D. Coman & A. Sillitti, An empirical exploratory study oninferring developers’ activities from low-level data, Proc. ofSoftware Engineering and Knowledge Engineering, 2007.
  15. [15] A. Sillitti, A. Janes, G. Succi, & T. Vernazza, Collecting, inte-grating and analyzing software metrics and personal softwareprocess data, Proc. of EUROMICRO, 2003.
  16. [16] C. Parnin & C. G¨org, Building usage contexts during pro-gram comprehension, Proc. of IEEE Conference on ProgramComprehension, 2006.
  17. [17] M.P. Robillard, Automatic generation of suggestions for pro-gram investigation, Proc. of ESEC/FSE, 2005.
  18. [18] P.M. Johnson, H. Kou, J.M. Agustin, Q. Zhang, A. Kagawa,& T. Yamashita, Practical automated process and productmetric collection and analysis in a classroom setting: Lessonslearned from Hackystat-UH, Proc. of the 2004 Intl. Symposiumon Empirical Software Engineering, August 2004.
  19. [19] G. Burnell, 6th Sense Analytics, homepage,
  20. [20] M. Ohira, R. Yokomori, M. Sakai, K. Matsumoto, K. Inoue,& K. Torii, Empirical project monitor: A tool for miningmultiple project data, Proc. of Workshop on Mining SoftwareRepositories, 2004.
  21. [21] F. Schlesinger & S. Jekutsch, ElectroCodeoGram: An envi-ronment for studying programming, Proc. of Workshop onEthnographies of Code, March 2006.
  22. [22] N.A. Nystrom, J. Urbanic, & C. Savinell, Understanding pro-ductivity through non-intrusive instrumentation and statis-tical learning, Proc. of 2nd Workshop on Productivity andPerformance in High-End Computing (P-PHEC), 2005.
  23. [23] I. Majid & M.P. Robillard, NaCIN – An eclipse plug-in forprogram navigation-based concern inference, OOPSLA 2005Eclipse Technology Exchange, 2005.

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