Professor Thomas J. Marlowe is Program Advisor for Computer Science, has been a member of the Department of Mathematics and Computer Science at Seton Hall University for over 30 years, and has taught a wide variety of courses in both disciplines. Professor Marlowe enjoys working with students and with professional colleagues-- almost all his research is collaborative. His professional interests include in mathematics, abstract algebra and discrete mathematics; in computer science, programming languages, real-time systems, and software engineering, and in information science, collaboration and knowledge management. The connection between graphs and algebraic structures is a recurrent theme.
T.J. Marlowe, N. Jastroch, V. Kirova, M. Mohtashami, “A Classification of Collaborative Knowledge,” Special Session on Collaborative Knowledge Management, Workshop on Knowledge Generation, Communication and Management (KGCM 2010), to appear, June 2010.
T. J. Marlowe, V. Kirova, “High-level Component Interfaces for Collaborative Development: A Proposal”, Journal of Systemics, Cybernetics, and Informatics, 7 (6), pages 1-6, 2009.
Rountev, S. Kagan, T. J. Marlowe, “Interprocedural Dataflow Analysis in the Presence of Large Libraries”, Proceedings of CC 2006, 216, Lecture Notes in Computer Science 3923, 2006.
S. P. Masticola, T. J. Marlowe, B. G. Ryder, "Multisource Data Flow Problems'', ACM Transactions on Programming Languages and Systems, 17 (5), 777 -803, September 1995.
D. Stoyenko, T. J. Marlowe, "Polynomial-Time Program Transformations and Schedulability Analysis of Parallel Real-time Programs with Restricted Resource Contention'', Journal of Real-Time Systems, 4 (4), 1992.
T. J. Marlowe, B. G. Ryder, "Properties of data flow frameworks: A unified model'', Acta Informatica, 28 (2), 121 -164, 1991.
Professor Marlowe is member of more than 10 Ph. D. thesis and 5 M.S. thesis committees, member of more than 20 conference program committees, and reviewer for numerous conferences, journals, and grants. He is the founder of an ongoing professional conference, and co-founder of a new workshop on collaboration.
Who needs metrics? Where do they come from, anyway? How can we make sense or progress without them? Is a bad metric better than no metric? Are metrics the source of their own failure? How can we avoid misapplying metrics? What is a zombie metric?
We present an overview with examples of uses, abuses, pitfalls and misunderstandings in the definition and application of metrics, and argue for a better understanding of and a more careful approach to metrics.
