Academic literature on the topic 'Software productivity'

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Journal articles on the topic "Software productivity"

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Jackson, Michael. "Software productivity." Science of Computer Programming 12, no. 2 (1989): 170–72. http://dx.doi.org/10.1016/0167-6423(89)90046-4.

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Ennever, J. "Software productivity." Information and Software Technology 31, no. 5 (1989): 283. http://dx.doi.org/10.1016/0950-5849(89)90009-8.

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Hernández-López, Adrián, Ricardo Colomo-Palacios, Ángel García-Crespo, and Fernando Cabezas-Isla. "Software Engineering Productivity." International Journal of Information Technology Project Management 2, no. 1 (2011): 37–47. http://dx.doi.org/10.4018/jitpm.2011010103.

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Software engineering productivity has been widely studied, but there are many issues that remain unsolved. Interesting works related to new metrics and more replications of past productivity analysis have emerged, however, in order to fulfill these unsolved issues, a consensus about influencing factors and well recognized and useful sets of inputs and outputs for using in measurements must be reached. In this regard, a clear state of the art may shed light on further research in software engineering productivity, which remains a promising research area. In this paper, general concepts of softw
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Boehm. "Improving Software Productivity." Computer 20, no. 9 (1987): 43–57. http://dx.doi.org/10.1109/mc.1987.1663694.

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Yu, Weider D., D. Paul Smith, and Steel T. Huang. "Software Productivity Measurements." AT&T Technical Journal 69, no. 3 (1990): 110–20. http://dx.doi.org/10.1002/j.1538-7305.1990.tb00339.x.

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Chiang, I. Robert, and Vijay S. Mookerjee. "Improving software team productivity." Communications of the ACM 47, no. 5 (2004): 89–93. http://dx.doi.org/10.1145/986213.986217.

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Maxwell, K. D., and P. Forselius. "Benchmarking software development productivity." IEEE Software 17, no. 1 (2000): 80–88. http://dx.doi.org/10.1109/52.820015.

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Humphrey, W. S., and N. D. Singpurwalla. "Predicting (individual) software productivity." IEEE Transactions on Software Engineering 17, no. 2 (1991): 196–207. http://dx.doi.org/10.1109/32.67600.

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Kemerer, Chris F. "Software development productivity measurement." ACM SIGMIS Database: the DATABASE for Advances in Information Systems 17, no. 4 (1986): 41. http://dx.doi.org/10.1145/1113523.1113533.

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Jalil, Abdurrahman. "Designing A Mobile Application to Improve User’s Productivity on Computer-based Productivity Software." Journal of Advanced Research in Dynamical and Control Systems 12, SP3 (2020): 226–36. http://dx.doi.org/10.5373/jardcs/v12sp3/20201257.

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Dissertations / Theses on the topic "Software productivity"

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Moschoglou, Georgios Moschos. "Software testing tools and productivity." Virtual Press, 1996. http://liblink.bsu.edu/uhtbin/catkey/1014862.

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Testing statistics state that testing consumes more than half of a programmer's professional life, although few programmers like testing, fewer like test design and only 5% of their education will be devoted to testing. The main goal of this research is to test the efficiency of two software testing tools. Two experiments were conducted in the Computer Science Department at Ball State University. The first experiment compares two conditions - testing software using no tool and testing software using a command-line based testing tool - to the length of time and number of test cases needed to a
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Evans, David Wyn. "The impact of underutilising productivity software." Thesis, Cape Peninsula University of Technology, 2010. http://hdl.handle.net/20.500.11838/1205.

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Thesis (MTech (Quality))--Cape Peninsula University of Technology, 2010<br>The aim of this study is to examine the level of utilisation of productivity software by staff of the Engineering Faculty of a South African University, and the impact it has on productivity. One of the primary effects of staff underutilisation is time wasted by staff who are doing tasks manually, instead of learning faster methods of doing tasks. It was thought that the use of computers would free staff up from the tedium of everyday manual tasks, effectively giving staff a shorter work day, however the actual i
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Lipkin, Ilya. "Testing Software Development Project Productivity Model." University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1321593577.

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Long, Rick, and Peter Crump. "SOFTWARE QUALITY AND PRODUCTIVITY: ARE THEY COMPATIBLE?" International Foundation for Telemetering, 1999. http://hdl.handle.net/10150/608443.

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International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>Many view quality and productivity as competing concepts. After all, doesn’t high software quality come at a high cost? Doesn’t it mean that a large amount of "extra stuff" needs to be done during the software development cycle? And, doesn’t that mean that software productivity takes a back seat to (and a major hit from) quality efforts? This paper will explore these issues. This paper provides some preliminary data that supports how a disciplined software enginee
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Siok, Michael F. "Empirical study of software productivity and quality." Ann Arbor, Mich. : ProQuest, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3337487.

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Thesis (Ph.D. in Engineering Management)--S.M.U.<br>Title from PDF title page (viewed Oct. 7, 2009). Source: Dissertation Abstracts International, Volume: 69-12, Section: B, page: 7789. Adviser: Jeff Tian. Includes bibliographical references.
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Gupta, Shweta. "Software Development Productivity Metrics, Measurements and Implications." Thesis, University of Oregon, 2018. http://hdl.handle.net/1794/23816.

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The rapidly increasing capabilities and complexity of numerical software present a growing challenge to software development productivity. While many open source projects enable the community to share experiences, learn and collaborate; estimating individual developer productivity becomes more difficult as projects expand. In this work, we analyze some HPC software Git repositories with issue trackers and compute productivity metrics that can be used to better understand and potentially improve development processes. Evaluating productivity in these communities presents additional challenges b
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Yun, Seok Jun. "Productivity prediction model based on Bayesian analysis and productivity console." Texas A&M University, 2003. http://hdl.handle.net/1969.1/2305.

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Software project management is one of the most critical activities in modern software development projects. Without realistic and objective management, the software development process cannot be managed in an effective way. There are three general problems in project management: effort estimation is not accurate, actual status is difficult to understand, and projects are often geographically dispersed. Estimating software development effort is one of the most challenging problems in project management. Various attempts have been made to solve the problem; so far, however, it remains a complex
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Cavalcante, Marcia Beatriz. "The impact of team software organizations on software quality and productivity." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0006/MQ44140.pdf.

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Unlu, Cumhur. "The Effects Of Test Driven Development On Software Productivity And Software Quality." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609969/index.pdf.

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In the 1990s, software projects became larger in size and more complicated in structure. The traditional development processes were not able to answer the needs of these growing projects. Comprehensive documentation in traditional methodologies made processes slow and discouraged the developers. Testing, after all code is written, was time consuming, too costly and made error correction and debugging much harder. Fixing the code at the end of the project also affects the internal quality of the software. Agile software development processes evolved to bring quick solutions to these existing pr
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AQUINO, JÚNIOR Gibeon Soares de. "Value-based productivity measurement in software development projects." Universidade Federal de Pernambuco, 2010. https://repositorio.ufpe.br/handle/123456789/1768.

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Made available in DSpace on 2014-06-12T15:52:15Z (GMT). No. of bitstreams: 2 arquivo3204_1.pdf: 2932974 bytes, checksum: ed70cb5e6dddd387ea04292de409a2f3 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010<br>A fim de melhorar a sua competitividade no mercado global, as organizações de software têm se preocupado cada vez mais com a questão de produtividade na execução de projetos. No entanto, para melhorar a produtividade, as organizações de software devem definir uma forma de medí-la. O problema é que a medição da produtividade ape
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Books on the topic "Software productivity"

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Mills, Harlan D. Software productivity. Dorset House, 1988.

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Parker, Charles S. Productivity software guide. Dryden Press, 1994.

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Parker, Charles S. Productivity software guide. Dryden Press, 1995.

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Martin, Edward G. Productivity software guide. Dryden Press, 1995.

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Harrington, Jan L. Productivity software guide. Dryden Press, 1991.

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Kee, Charles E. Productivity software guide. Dryden Press, 1995.

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Parker, Charles S. Productivity software guide. 3rd ed. Dryden Press, 1991.

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Parker, Charles S. Productivity software guide. s.n., 1994.

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Price, Wilson T. Using productivity software. Holt, Rinehart, and Winston, 1987.

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Lee, Matthew, Ben-Zion Barta, and Peter Juliff, eds. Software Quality and Productivity. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34848-3.

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Book chapters on the topic "Software productivity"

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Cocklin, Thomas G. "Software Usability and Productivity." In Psychology and Productivity. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-9969-8_2.

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Horgan, Jack. "Productivity Through Software Prototyping." In CAD/CAM Robotics and Factories of the Future. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-52320-5_3.

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Baldi, M., and M. L. Jaccheri. "Software Process Model Specification." In Software Quality and Productivity. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34848-3_22.

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Mendes, Emilia. "Web Cost Estimation and Productivity Benchmarking." In Software Engineering. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-95888-8_8.

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Dromey, R. G. "Software Quality and Productivity Improvement." In Software Quality and Productivity. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34848-3_2.

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Billington, J. "ISO Standards in Software Engineering." In Software Quality and Productivity. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34848-3_28.

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Brunskill, David A., and Alan Samuel. "Experience in Software Inspection Techniques." In Software Quality and Productivity. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34848-3_38.

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Azuma, Motoei. "Towards the 21st Century’s Software, State of the art and International Standard in JTC1/SC7." In Software Quality and Productivity. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34848-3_1.

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Mochizuki, Sumio, and Takuya Katayama. "A Proposal for Composing Software Design Process." In Software Quality and Productivity. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34848-3_10.

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Sawyer, S., and P. J. Guinan. "Team-Based Software Development Using an Electronic Meeting System: The Quality Pay-Off." In Software Quality and Productivity. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34848-3_11.

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Conference papers on the topic "Software productivity"

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Vasilateanu, Andrei, Răzvan-Doru Ene, and Cristian-Andrei Popescu. "GAMIFICATION SOFTWARE FOR IMPROVING SOFTWARE DEVELOPMENT PRODUCTIVITY." In 11th annual International Conference of Education, Research and Innovation. IATED, 2018. http://dx.doi.org/10.21125/iceri.2018.2094.

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Desharnais, Jean-Marc, and Alain April. "Software maintenance productivity and maturity." In the 11th International Conference. ACM Press, 2010. http://dx.doi.org/10.1145/1961258.1961289.

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Meyer, André N., Thomas Fritz, Gail C. Murphy, and Thomas Zimmermann. "Software developers' perceptions of productivity." In the 22nd ACM SIGSOFT International Symposium. ACM Press, 2014. http://dx.doi.org/10.1145/2635868.2635892.

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Arthur, Lowell Jay. "Software productivity and quality measurement." In the 1985 ACM annual conference. ACM Press, 1985. http://dx.doi.org/10.1145/320435.320496.

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Canedo, Edna Dias, and Giovanni Almeida Santos. "Factors Affecting Software Development Productivity." In SBES 2019: XXXIII Brazilian Symposium on Software Engineering. ACM, 2019. http://dx.doi.org/10.1145/3350768.3352491.

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Harkonen, Ari K., Risto S. Mitikka, and Ilkka Moring. "Software tool for developing algorithms for surface inspection systems." In Optics for Productivity in Manufacturing, edited by Christophe Gorecki and Richard W. T. Preater. SPIE, 1994. http://dx.doi.org/10.1117/12.194352.

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Moazeni, Ramin, Daniel Link, and Barry Boehm. "Lehman's Laws and the Productivity of Increments: Implications for Productivity." In 2013 20th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2013. http://dx.doi.org/10.1109/apsec.2013.84.

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Pyster, A., and B. Barnes. "The software productivity consortium reuse program." In COMPCON Spring 88. IEEE, 1988. http://dx.doi.org/10.1109/cmpcon.1988.4867.

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Robinson, Will, and Ben D'Angelo. "Integrating software productivity tools into Eclipse." In the 2003 OOPSLA workshop. ACM Press, 2003. http://dx.doi.org/10.1145/965660.965669.

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Besker, Terese, Antonio Martini, and Jan Bosch. "Technical debt cripples software developer productivity." In ICSE '18: 40th International Conference on Software Engineering. ACM, 2018. http://dx.doi.org/10.1145/3194164.3194178.

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Reports on the topic "Software productivity"

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Heroux, Michael A., Lois McInnes, David Bernholdt, et al. Advancing Scientific Productivity through Better Scientific Software: Developer Productivity and Software Sustainability Report. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1606662.

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Bodik, Rastislav. Software Synthesis for High Productivity Exascale Computing. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1214546.

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SOFTWARE OPTIONS INC CAMBRIDGE MA. Improving Productivity in the Development of Large Software Systems. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada282270.

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Solar-Lezama, Armando. Final Report on XStack: Software Synthesis for High Productivity ExaScale Computing. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1261628.

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Dongarra, Jack. PaRSEC: A Software Framework for Performance and Productivity on Hybrid, Manycore Platforms. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1348914.

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Johansen, Hans, Lois Curfman McInnes, David E. Bernholdt, et al. Workshop on Software Productivity for Extreme-scale Science, January 13-14, 2014, Hilton Hotel, Rockville, MD. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1471106.

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Osadcha, Kateryna P., and Viacheslav V. Osadchyi. The use of cloud computing technology in professional training of future programmers. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4435.

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The article provides a brief analysis of the current state of the study of cloud technologies by future software engineers at foreign and Ukrainian universities. The author experience in the application of cloud technologies in the training of future software engineers in Ukraine is presented. The application of cloud business automation systems, online services to monitor the implementation of the software projects, Google services for collaboration, planning and productivity while studying professional disciplines and carrying out diploma projects is described. Based on the survey conducted
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Lee, Sophie. Introduction to R with Tidyverse. Instats Inc., 2024. http://dx.doi.org/10.61700/boynumn1t516o1024.

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The 'Introduction to R with Tidyverse' seminar is a two-day workshop aimed at equipping researchers across various disciplines with the skills to leverage R software for academic research. Participants will gain a solid foundation in R programming and Tidyverse, enabling reproducible data analysis, visualization, and effective communication of results using R Markdown, thereby enhancing research productivity and impact. The workshop assumes no prior R programming or statistical experience.
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Bloesch, Justin, and Jacob P. Weber. Congestion in Onboarding Workers and Sticky R&D. Federal Reserve Bank of New York, 2023. http://dx.doi.org/10.59576/sr.1075.

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R&amp;D investment spending exhibits a delayed and hump-shaped response to shocks. We show in a simple partial equilibrium model that rapidly adjusting R&amp;D investment is costly if the probability of converting new hires into productive R&amp;D workers (“onboarding”) is decreasing in the number of new hires (“congestion”). Congestion thus causes R&amp;D-producing firms to slowly hire new workers in response to good shocks and hoard workers in response to bad shocks, providing a microfoundation for convex adjustment costs in R&amp;D investment. Using novel, high-frequency productivity data o
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Hicks, Julie, Laurin Yates, and Jackie Pettway. Mat Sinking Unit supply study : Mississippi River revetment. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41867.

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The Mississippi Valley Division (MVD) has maintained the Mississippi River banks for over 80 years. The Mat Sinking Unit (MSU), built in 1946, was considered state-of-the-art at the time. This system is still in operation today and has placed over 1,000 miles of Articulated Concrete Mats along the Mississippi River from Head of Passes, LA, to Cairo, IL. A new MSU has been designed and is expected to be fully mission capable and operational by the 2023 season, which is expected to increase the productivity from 2,000 squares/day up to 8,000 squares/day with double shifts and optimal conditions.
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