@inproceedings{pittard_tharp_2010, title={Simplified self-adapting skip lists}, volume={6283}, DOI={10.1007/978-3-642-15381-5_16}, abstractNote={The Simplified Self-Adapting Skip List, a practical new extension of the Skip List data structure, is designed for use with data that exhibit bias, that is, a nonuniform distribution of queries to set elements. The structure observes an initially unknown degree of bias in queries to a data set and adapts itself to a consistently nearly-optimal configuration, improving search efficiency and speed. By modifying the original Skip List design in intuitive ways, self-optimization is achieved while maintaining an extreme simplicity of description, implementation, and operation unmatched by previous dynamic Skip Lists. The additional memory, time, and conceptual overheads introduced by this structure over the original Skip List are considerably less than in previous dynamic designs, but search speed is comparable or superior, making the SSASL better suited than its predecessors for operations in which time or memory efficiency is critical.}, booktitle={Intelligent data engineering and automated learning - ideal 2010}, author={Pittard, J. J. and Tharp, A. L.}, year={2010}, pages={126–136} }
 @article{cox_tharp_2010, title={Toward a Visualization of DNA Sequences}, volume={680}, ISBN={["978-1-4419-5912-6"]}, ISSN={["2214-8019"]}, DOI={10.1007/978-1-4419-5913-3_48}, abstractNote={Most biologists associate pattern discovery in DNA with finding repetitive sequences or commonalities across several sequences. However, pattern discovery is not limited to finding repetitions and commonalities. Pattern discovery also involves identifying objects and distinguishing objects from one another. Human vision is unmatched in its ability to identify and distinguish objects. Considerable research into human vision has revealed to a fair degree the visual cues that our brains use to segment an image into separate regions and entities. In this paper, we consider some of these visual cues to construct a novel graphical representation of a DNA sequence. We exploit one of these cues, proximity, to segment DNA into visibly distinct regions and structures. We also demonstrate how to manipulate proximity to identify motifs visually. Lastly, we demonstrate how an additional cue, color, can be used to visualize the Shannon entropy associated with different structures. The presence of large numbers of such regions and structures in DNA suggests that they likely play some important biological role and would be interesting targets for further research.}, journal={ADVANCES IN COMPUTATIONAL BIOLOGY}, author={Cox, David N. and Tharp, Alan L.}, year={2010}, pages={419–435} }
 @article{deodhar_tharp_2009, title={Shift Hashing for Memory-Constrained Applications}, ISBN={["978-1-4244-4525-7"]}, ISSN={["0730-3157"]}, DOI={10.1109/compsac.2009.77}, abstractNote={Hardware innovations such as motes, RFIDs, embedded microprocessors, and wireless sensors have introduced a new set of wide-ranging applications for business, government, industry, and individuals. These applications include connected cities, smart homes and appliances, smart vehicles, improved security and surveillance, business integration and e-commerce to name a few. The real-time nature of these applications requires direct access to data and minimal response time from underlying hardware systems. This paper presents a new hashing method, Shift Hashing, which is an improvement over existing hashing schemes such as Tridirectional Computed Chaining, which reduce the direct access time by providing multi-way branching of individual probe chains. What is distinctive about Shift Hashing is that it not only allows faster access to data in most cases, but also eliminates the space requirement for storing links completely. There is no time-space tradeoff. Hence the method is suitable for applications in which space is quite limited and fast and real-time access is important. It is simple, easy to implement and its generality makes it very flexible to use. Storage efficiency is achieved by incorporating a link field in the key of the record by using bit shifting methods. The concept of using shifting to compute data rather than storing it may be applicable to other situations as well.}, journal={2009 IEEE 33RD INTERNATIONAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE, VOLS 1 AND 2}, author={Deodhar, Sushamna and Tharp, Alan L.}, year={2009}, pages={531–536} }
 @article{fornaro_heil_tharp_2007, title={Reflections on 10 years of sponsored senior design projects: Students win-clients win!}, volume={80}, ISSN={["1873-1228"]}, DOI={10.1016/j.jss.2006.09.052}, abstractNote={Undergraduate computer science degree programs often provide an opportunity for students to experience real software projects as a part of their programs of study. These experiences frequently reside in a course in which students form software development teams, are assigned to a project offered by a corporate sponsor and devote one or two semesters to the task of making progress on the project. In an ideal model, faculty mentor student teams who, in turn, behave as subcontractors or consultants to the sponsor. Students work for a grade, not directly for the sponsor as a true subcontractor would. In the ideal model, students demonstrate what they have learned about software engineering process, as well as their ability to implement programmed solutions. Student teams provide progress reports, both oral and written, and directly experience many of the challenges and successes of true software engineering professionals. This paper reports on one such program after 10 years of operation. The technologies and software development processes of student projects are summarized and presented as an informal survey. Student response is discussed in terms of software systems they produced and how they went about producing them. The maturation of these students as software engineering professionals is also discussed.}, number={8}, journal={JOURNAL OF SYSTEMS AND SOFTWARE}, author={Fornaro, Robert J. and Heil, Margaret R. and Tharp, Alan L.}, year={2007}, month={Aug}, pages={1209–1216} }
 @book{tharp_1988, title={File organization and processing}, publisher={New York: J Wiley}, author={Tharp, Alan L.}, year={1988} }