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Journal articles on the topic 'Programs analysis'

Author: Grafiati

Published: 28 June 2021

Last updated: 1 February 2022

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1

Harris, William R., Sriram Sankaranarayanan, Franjo Ivančić, and Aarti Gupta. "Program analysis via satisfiability modulo path programs." ACM SIGPLAN Notices 45, no. 1 (2010): 71–82. http://dx.doi.org/10.1145/1707801.1706309.

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2

Schwarzer, Ralf. "Meta-analysis programs." Behavior Research Methods, Instruments, & Computers 20, no. 3 (1988): 338. http://dx.doi.org/10.3758/bf03203853.

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3

Kaziliūnas, Adolfas. "The Knowledge Management Process for Implementing Quality Improvement Programs." Informacijos mokslai 62 (January 1, 2012): 97–108. http://dx.doi.org/10.15388/im.2012.0.1580.

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The importance of quality to any and all organizations is well known, and it is necessary to teach employees quality discipline. However, the analysis of literature indicates that many of quality improvement programs are ineffective. This article discusses knowledge management processes for the organizational learning mechanisms that can help to plan and implement quality management programs more successfully. The processes are implemented in sequence for the development of knowledge management in an organization in which user needs and expectations are recognized as an input. The processes are controlled by knowledge management strategy planning, knowledge process, customer and knowledge supplier relationships. The mechanisms are led by a knowledge management leader, knowledge management personnel, and knowledge management system infrastructure. The input is transformed into knowledge management results in terms of users’ needs and expectations of knowledge management outcomes, knowledge management strategy and planning outcomes, knowledge management delivery outcomes. By using the knowledge management process organizations can increase the effectiveness of quality management training.Keywords: quality management, knowledge management, ISO 9000 standards, quality programsŽinių vadybos procesas kokybės gerinimo programoms įgyvendinti Adolfas Kaziliūnas Santrauka Daugelis organizacijų, siekdamos konkurencinio pranašumo, įtraukia kokybės gerinimą į savo strateginius tikslus, tačiau literatūros analizė rodo, kad dažnai kokybės gerinimo programos nepasiekia numatytų savo tikslų. Tai dažniausiai atsitinka dėl netikslaus kokybės programų pritaikymo organizacijos reikmėms ir netinkamai vykdomo mokymosi proceso. Šio tyrimo tikslas – rasti būdų efektyviau įgyvendinti kokybės gerinimo programas. Tyrimai parodė, kad pasitelkdamos žinių vadybos patirtį organizacijos gali padidinti kokybės gerinimo programų efektyvumą. Žinių vadybos procesai padeda organizacijai geriau analizuoti, parengti ir įsisavinti aktualią organizacijos darbuotojams informaciją. Straipsnyje pateikiamas literatūros analizės pagrindu parengtas septynių fazių žinių vadybos procesas. Procese nuosekliai išdėstytos veiklos, kurias reikia atlikti rengiant ir įgyvendinant kokybės gerinimo programą. Prieš rengiant šią programą būtina išana lizuoti organizacijos darbuotojų mokymosi poreikius ir pagal tai suformuluoti mokymų strategiją. Organizacijos vadovai turėtų asmeniškai dalyvauti planuojant programą ir pageidautina – mokant darbuotojus. Kokybės gerinimo programos tikslai ir jų pasiekimo planai turi būti aiškiai apibrėžti. Į planavimo procesą būtina įtraukti vidurinės grandies vadybininkus, nes jie geriausiai pastebi darbuotojų žinių trūkumus. Būtina rimtai vertinti dalies darbuotojų skeptišką požiūrį į mokymų programą ir reaguoti į jų pastabas. Labai svarbu mokymosi rezultatų matavimas ir analizė bei nuolatinis grįžtamojo ryšio su programos dalyviais palaikymas. Rezultatų matavimas ir analizė turi būti atliekama po kiekvienos esminės proceso fazės: vartotojų poreikių nustatymo, mokymosi strategijos suformulavimo ir planavimo, mokymo planų įgyvendinimo. Reikšminiai žodžiai: kokybės vadyba, žinių vadyba, kokybės programos, ISO 9000 standartai.

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4

Psarris, Kleanthis. "Program analysis techniques for transforming programs for parallel execution." Parallel Computing 28, no. 3 (2002): 455–69. http://dx.doi.org/10.1016/s0167-8191(01)00132-6.

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5

Sun, Kwangwon, and Sukyoung Ryu. "Analysis of JavaScript Programs." ACM Computing Surveys 50, no. 4 (2017): 1–34. http://dx.doi.org/10.1145/3106741.

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6

Chaudhuri, Swarat, Sumit Gulwani, and Roberto Lublinerman. "Continuity analysis of programs." ACM SIGPLAN Notices 45, no. 1 (2010): 57–70. http://dx.doi.org/10.1145/1707801.1706308.

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7

Bakar, Normi Sham Awang Abu. "The Analysis of Object-Oriented Metrics in C++ Programs." Lecture Notes on Software Engineering 4, no. 1 (2016): 48–52. http://dx.doi.org/10.7763/lnse.2016.v4.222.

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8

Iwamoto, Seiichi. "Associative Dynamic Programs." Journal of Mathematical Analysis and Applications 201, no. 1 (1996): 195–211. http://dx.doi.org/10.1006/jmaa.1996.0250.

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9

Hui, Deng, Liu Hui, Guo Ying, and Zhang Baofeng. "Memory Allocation Vulnerability Analysis and Analysis Optimization for C Programs Based on Formal Methods." Journal of Software 10, no. 9 (2015): 1079–85. http://dx.doi.org/10.17706//jsw.10.9.1079-1085.

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10

Pérez-Bóveda, Astrid, and Concepción Yániz Álvarez de Eulate. "Programas de formación parental. Análisis comparativo // Parenting programs. Comparative analysis." REOP - Revista Española de Orientación y Psicopedagogía 26, no. 2 (2015): 104. http://dx.doi.org/10.5944/reop.vol.26.num.2.2015.15231.

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11

Younghee, Noh, and Jeon Hyeonok. ""Effect Analysis of Humanities Program: Mainly in Religious Culture Programs"." Journal of Humanities and Social sciences 21 11, no. 5 (2020): 171–86. http://dx.doi.org/10.22143/hss21.11.5.13.

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12

Wiser, Ryan, Scott Olson, Lori Bird, and Blair Swezey. "Utility Green Pricing Programs: A Statistical Analysis of Program Effectiveness." Energy & Environment 16, no. 1 (2005): 47–68. http://dx.doi.org/10.1260/0958305053516172.

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13

Larrea, Claudio Marcelo. "An analysis of accreditation standards for undergraduate programs in Argentina." New Trends and Issues Proceedings on Humanities and Social Sciences 4, no. 1 (2017): 43–48. http://dx.doi.org/10.18844/prosoc.v4i1.2050.

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14

Ponikvar, Nina, Marija Anderluh, Eva Strmljan Kreslin, and Mojca Marc. "ECONOMIC EVALUATION OF PREVENTIVE HEALTHCARE: A COST BENEFIT ANALYSIS OF A PARENTING PROGRAM." EURASIAN JOURNAL OF SOCIAL SCIENCES 9, no. 2 (2021): 89–97. http://dx.doi.org/10.15604/ejss.2021.09.02.003.

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The positive impact of parenting programs on the health and wellbeing of individuals and their immediate community has been confirmed in many studies. Often, and especially during the Covid-19 pandemics, prevention health programs are stalled due to other policy priorities. Costbenefit analysis (CBA) can be used for the economic evaluation of public health programs to support evidence-based health policies and allows the comparison of the monetized effects of programs across different societal domains. However, CBA requires a variety of data that are typically difficult to obtain. Using the Incredible Years (IY) parenting program case, we illustrate how CBA can be practically applied. For parenting programs, the positive effects arise exclusively in non-monetary form as benefits arising from avoiding adverse effects in society. We show how to monetize them by estimating the avoided costs of healthcare, educational, and other societal costs due to the program's implementation. At a 4% social discount rate, the economic net present value is positive and high, showing that the present value of the program's benefits exceeds the costs of the program by almost €800 thousand. The benefit-to-cost index of 5.6 confirms that every € invested in the program brings benefits of €5.6 in monetary terms. Cost-benefit analysis provides a convincing foundation for distributing public funds as it allows for a comparison of fieldrelated programs and programs from different fields. Consequently, they increase any public policy's effectiveness and efficiency, but especially preventive health policy.

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15

ZHANG, Jian. "Sharp Static Analysis of Programs." Chinese Journal of Computers 31, no. 9 (2009): 1549–53. http://dx.doi.org/10.3724/sp.j.1016.2008.01549.

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16

Guzev, M. A., M. A. Knyazeva, I. I. Moskalev, and E. Y. Nikitina. "Rank analysis of computer programs." Dal'nevostochnyi Matematicheskii Zhurnal 20, no. 2 (2020): 155–63. http://dx.doi.org/10.47910/femj202017.

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This paper describes the application of the rank analysis method for formal languages on the example of the source codes of programs in the Java language. When describing the technology for compiling frequency dictionaries, attention is focused on how the presence of anaphoric content in computer programs is taken into consideration. When discussing the results, it was noted that the structural components of programs for various purposes correspond to certain areas of the graph of the dependence of rank on the frequency of occurrence of a lexeme.

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17

Jhala, Ranjit, and Rupak Majumdar. "Interprocedural analysis of asynchronous programs." ACM SIGPLAN Notices 42, no. 1 (2007): 339–50. http://dx.doi.org/10.1145/1190215.1190266.

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18

Lin, Man. "Timing Analysis of PL Programs." IFAC Proceedings Volumes 32, no. 1 (1999): 203–8. http://dx.doi.org/10.1016/s1474-6670(17)39988-3.

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19

Painter, James E., and Becky Sabbert. "Two Internet Diet Analysis Programs." Journal of Nutrition Education 33, no. 3 (2001): 173–74. http://dx.doi.org/10.1016/s1499-4046(06)60189-9.

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20

Irizarry, Estelle. "Software Programs for Literary Analysis." Hispania 72, no. 1 (1989): 214. http://dx.doi.org/10.2307/342719.

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21

Sendeckyj, GP, SS Wang, W. Steven Johnson, et al. "Composite Bolted Joints Analysis Programs." Journal of Composites Technology and Research 12, no. 1 (1990): 41. http://dx.doi.org/10.1520/ctr10176j.

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22

Morandi, Benjamin, Sebastian Nanz, and Bertrand Meyer. "Performance analysis of SCOOP programs." Journal of Systems and Software 85, no. 11 (2012): 2519–30. http://dx.doi.org/10.1016/j.jss.2012.05.076.

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23

Lin, Man. "Timing analysis of PL programs." Control Engineering Practice 8, no. 6 (2000): 697–703. http://dx.doi.org/10.1016/s0967-0661(00)00022-8.

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24

Lancashire, Ian. "Concordance programs for literary analysis." ACM SIGCUE Outlook 19, no. 1-2 (1986): 54–61. http://dx.doi.org/10.1145/951656.951663.

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25

Bouajjani, Ahmed, and Michael Emmi. "Analysis of Recursively Parallel Programs." ACM Transactions on Programming Languages and Systems 35, no. 3 (2013): 1–49. http://dx.doi.org/10.1145/2518188.

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26

Sankaranarayanan, Sriram, Aleksandar Chakarov, and Sumit Gulwani. "Static analysis for probabilistic programs." ACM SIGPLAN Notices 48, no. 6 (2013): 447–58. http://dx.doi.org/10.1145/2499370.2462179.

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27

Amey, P. N., and B. J. Dobbing. "Static analysis of Ravenscar programs." ACM SIGAda Ada Letters XXIII, no. 4 (2003): 58–64. http://dx.doi.org/10.1145/959221.959234.

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28

Debray, Saumya K., and Nai-Wei Lin. "Cost analysis of logic programs." ACM Transactions on Programming Languages and Systems 15, no. 5 (1993): 826–75. http://dx.doi.org/10.1145/161468.161472.

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29

Rugina, Radu, and Martin Rinard. "Pointer analysis for multithreaded programs." ACM SIGPLAN Notices 34, no. 5 (1999): 77–90. http://dx.doi.org/10.1145/301631.301645.

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30

Laski, Janusz, William Stanley, and Jim Hurst. "Dependency analysis of Ada programs." ACM SIGAda Ada Letters XVIII, no. 6 (1998): 263–75. http://dx.doi.org/10.1145/301687.289645.

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31

Arts, Thomas, and Lars-Åke Fredlund. "Trace analysis of Erlang programs." ACM SIGPLAN Notices 37, no. 12 (2002): 18–24. http://dx.doi.org/10.1145/636517.636524.

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32

Ehrenfried, Daniel H. "Static analysis of Ada programs." ACM SIGAda Ada Letters XIV, no. 4 (1994): 28–35. http://dx.doi.org/10.1145/181476.181479.

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33

Anjaneyulu, K. S. R. "Bug analysis of Pascal programs." ACM SIGPLAN Notices 29, no. 4 (1994): 15–22. http://dx.doi.org/10.1145/181761.181762.

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34

Altman, Erik, Matthew Arnold, Stephen Fink, and Nick Mitchell. "Performance analysis of idle programs." ACM SIGPLAN Notices 45, no. 10 (2010): 739–53. http://dx.doi.org/10.1145/1932682.1869519.

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35

Simmons, Sharon, Dennis Edwards, and Phil Kearns. "Communication Analysis of Distributed Programs." Scientific Programming 14, no. 2 (2006): 151–70. http://dx.doi.org/10.1155/2006/763568.

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Capturing and examining the causal and concurrent relationships of a distributed system is essential to a wide range of distributed systems applications. Many approaches to gathering this information rely on trace files of executions. The information obtained through tracing is limited to those executions observed. We present a methodology that analyzes the source code of the distributed system. Our analysis considers each process's source code and produces a single comprehensive graph of the system's possible behaviors. The graph, termed the partial order graph (POG), uniquely represents each possible partial order of the system. Causal and concurrent relationships can be extracted relative either to a particular partial order, which is synonymous to a single execution, or to a collection of partial orders. The graph provides a means of reasoning about the system in terms of relationships that will definitely occur, may possible occur, and will never occur. Distributed assert statements provide a means to monitor distributed system executions. By constructing thePOGprior to system execution, the causality information provided by thePOGenables run-time evaluation of the assert statement without relying on traces or addition messages.

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36

Bouajjani, Ahmed, and Michael Emmi. "Analysis of recursively parallel programs." ACM SIGPLAN Notices 47, no. 1 (2012): 203–14. http://dx.doi.org/10.1145/2103621.2103681.

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37

Axler, David M., and John R. Abercrombie. "Computer Programs for Literary Analysis." Journal of American Folklore 99, no. 393 (1986): 360. http://dx.doi.org/10.2307/540836.

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38

Payet, Étienne, and Fausto Spoto. "Static analysis of Android programs." Information and Software Technology 54, no. 11 (2012): 1192–201. http://dx.doi.org/10.1016/j.infsof.2012.05.003.

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39

Weng, Min-Hsien, Mark Utting, and Bernhard Pfahringer. "Bound Analysis for Whiley Programs." Electronic Notes in Theoretical Computer Science 320 (February 2016): 53–67. http://dx.doi.org/10.1016/j.entcs.2016.01.005.

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40

Reichenbach, Christoph, Michael G. Burke, Igor Peshansky, and Mukund Raghavachari. "Analysis of imperative XML programs." Information Systems 34, no. 7 (2009): 624–42. http://dx.doi.org/10.1016/j.is.2009.03.013.

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41

van den Berg, KG, and PM van den Broek. "Static analysis of functional programs." Information and Software Technology 37, no. 4 (1995): 213–24. http://dx.doi.org/10.1016/0950-5849(95)90813-a.

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42

Shapiro, Alexander. "Asymptotic analysis of stochastic programs." Annals of Operations Research 30, no. 1 (1991): 169–86. http://dx.doi.org/10.1007/bf02204815.

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43

Römisch, Werner, and Rüdiger Schultz. "Stability analysis for stochastic programs." Annals of Operations Research 30, no. 1 (1991): 241–66. http://dx.doi.org/10.1007/bf02204819.

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44

Laneve, Cosimo, Michael Lienhardt, Ka I. Pun, and Guillermo Román-Díez. "Time analysis of actor programs." Journal of Logical and Algebraic Methods in Programming 105 (June 2019): 1–27. http://dx.doi.org/10.1016/j.jlamp.2019.02.007.

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45

Veanes, Margus, and Jonathan Jacky. "Composing model programs for analysis." Journal of Logic and Algebraic Programming 79, no. 7 (2010): 467–82. http://dx.doi.org/10.1016/j.jlap.2010.07.004.

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46

Reif, John H., and Harry R. Lewis. "Efficient symbolic analysis of programs." Journal of Computer and System Sciences 32, no. 3 (1986): 280–314. http://dx.doi.org/10.1016/0022-0000(86)90031-0.

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47

Onai, Rikio, Hajime Shimizu, Kanae Masuda, and Moritoshi Aso. "Analysis of sequential PROLOG programs." Journal of Logic Programming 3, no. 2 (1986): 119–41. http://dx.doi.org/10.1016/0743-1066(86)90019-1.

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48

Hanus, Michael. "Analysis of residuating logic programs." Journal of Logic Programming 24, no. 3 (1995): 219–45. http://dx.doi.org/10.1016/0743-1066(94)00105-f.

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49

Choi, Haneul, Sueim Chung, Youngjin Choi, Hyeonji Kang, Jooyoung Jeon, and Donghee Shin. "Analysis of Polar Education Programs." Journal of the Korean earth science society 42, no. 1 (2021): 102–17. http://dx.doi.org/10.5467/jkess.2021.42.1.102.

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50

Coulomb, Jean-Michel, Jerzy A. Filar, and Witold Szczechla. "Asymptotic Analysis of Perturbed Mathematical Programs." Journal of Mathematical Analysis and Applications 251, no. 1 (2000): 132–56. http://dx.doi.org/10.1006/jmaa.2000.7025.

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