Relevant bibliographies by topics / Software python

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Software python'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Software python"

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Peta, Saphalya. "Python- An Appetite for the Software Industry." International Journal of Programming Languages and Applications 12, no. 4 (2022): 1–14. http://dx.doi.org/10.5121/ijpla.2022.12401.

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Python is a scripting language that's high- positioned, interpreted, interactive, and object- oriented. Python is intended to be a veritably accessible programming language. It generally uses English terms rather than punctuation, and it has smaller syntactical structures than other languages. Python is a must-have skill for scholars and working professionals who want to become exceptional software masterminds, especially if they work in the web development field. It's a freshman-friendly scripting language. Some of the crucial features of Python programming language are- It supports OOP as we
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Peirce, Jonathan W. "PsychoPy—Psychophysics software in Python." Journal of Neuroscience Methods 162, no. 1-2 (2007): 8–13. http://dx.doi.org/10.1016/j.jneumeth.2006.11.017.

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Elserwy, Tamer Bahgat, Tarek Aly, and Basma E. El-Demerdash. "End-user software engineering approach: improve spreadsheets capabilities using Python-based user-defined functions." Indonesian Journal of Electrical Engineering and Computer Science 38, no. 2 (2025): 1024. https://doi.org/10.11591/ijeecs.v38.i2.pp1024-1032.

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<p>End-user computing enables non-developers to handle data and applications, boosting collaboration and productivity. Spreadsheets are a key example of end-user programming environments that are extensively utilized in business for data analysis. However, the functionalities of Excel have limitations compared to specialized programming languages. This study aims to address this shortcoming by proposing a prototype that integrates Python's features into Excel via standalone desktop Python-based user-defined functions (UDFs). This method mitigates potential latency concerns linked to clou
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Tamer, Bahgat Elserwy Tarek Aly Basma E. El-Demerdash. "End-user software engineering approach: improve spreadsheets capabilities using Python-based user-defined functions." Indonesian Journal of Electrical Engineering and Computer Science 38, no. 2 (2025): 1024–32. https://doi.org/10.11591/ijeecs.v38.i2.pp1024-1032.

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End-user computing enables non-developers to handle data and applications, boosting collaboration and productivity. Spreadsheets are a key example of end-user programming environments that are extensively utilized in business for data analysis. However, the functionalities of Excel have limitations compared to specialized programming languages. This study aims to address this shortcoming by proposing a prototype that integrates Python's features into Excel via standalone desktop Python-based user-defined functions (UDFs). This method mitigates potential latency concerns linked to cloud-based s
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Soujanya, Reddy Annapareddy. "Real-World Applications of Python in Firmware and Software Automation." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 10, no. 2 (2024): 1–6. https://doi.org/10.5281/zenodo.14540900.

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Python has become a versatile tool in firmware and software automation, enabling efficient development and testing workflows across various industries. Its simplicity, extensive libraries, and cross-platform support make it ideal for automating tasks like firmware flashing, version verification, and hardware communication. This paper explores real-world applications of Python in firmware and software automation, including integrating serial communication protocols, streamlining build and deployment processes, and implementing test frameworks for embedded systems. It highlights how Python's eco
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LOBARYOV, D., and N. LOBARYOV. "SYNTHESIS OF NONDETERMINISTIC FINITE AUTOMATON FROM REGULAR EXPRESSIONS BY GLUSHKOV'S ALGORITHM IN JFF FORMAT." HERALD OF POLOTSK STATE UNIVERSITY. Series С FUNDAMENTAL SCIENCES, no. 1 (April 18, 2025): 9–13. https://doi.org/10.52928/2070-1624-2025-44-1-9-13.

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The paper presents the results of the implementation of a software tool for synthesizing nondeterministic finite automaton using regular expressions in JFF format. Glushkov's algorithm is used as a method for synthesizing automata. When developing the program, the integrated development environment for the Python – Visual Studio Code, the JFLAP software package for visualizing finite automaton, as well as the Python libraries xml.etree and pythonds were used.
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Zonca, Andrea, Ben Thorne, Nicoletta Krachmalnicoff, and Julian Borrill. "The Python Sky Model 3 software." Journal of Open Source Software 6, no. 67 (2021): 3783. http://dx.doi.org/10.21105/joss.03783.

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Kerr, Cliff C., Paula Sanz-Leon, Romesh G. Abeysuriya, et al. "Sciris: Simplifying scientific software in Python." Journal of Open Source Software 8, no. 88 (2023): 5076. http://dx.doi.org/10.21105/joss.05076.

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Chen, Xiaojie. "Introduction and Analysis of Python Software." Frontiers in Computing and Intelligent Systems 5, no. 2 (2023): 41–43. http://dx.doi.org/10.54097/fcis.v5i2.12348.

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In the context of the era of rapid development of computer and Internet technology, it gives enterprises the possibility of realizing informationization and automation. Due to the traditional office needs to take up a lot of human, material and financial resources, as well as paper filing method is not environmentally friendly, easy to damage, easy to lose, poor security and other shortcomings, has been unable to meet the needs of modern office. With the development of science and technology, Microsoft Office, Adobe Systems PDF and other office software came into being, their role is increasin
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Bouzenia, Islem, Bajaj Piyush Krishan, and Michael Pradel. "DyPyBench: A Benchmark of Executable Python Software." Proceedings of the ACM on Software Engineering 1, FSE (2024): 338–58. http://dx.doi.org/10.1145/3643742.

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Python has emerged as one of the most popular programming languages, extensively utilized in domains such as machine learning, data analysis, and web applications. Python’s dynamic nature and extensive usage make it an attractive candidate for dynamic program analysis. However, unlike for other popular languages, there currently is no comprehensive benchmark suite of executable Python projects, which hinders the development of dynamic analyses. This work addresses this gap by presenting DyPyBench, the first benchmark of Python projects that is large-scale, diverse, ready-to-run (i.e., with ful
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Dissertations / Theses on the topic "Software python"

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Alenazi, Mohammed, Santosh Ajith Gogi, Dongsheng Zhang, Egemen K. Çetinkaya, Justin Rohrer, and James P. G. Sterbenz. "ANTP Protocol Suite Software Implementation Architecture in Python." International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595748.

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ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada<br>Due to the highly-dynamic nature of airborne telemetry networks, we have developed the ANTP protocol suite consisting of AeroTP, AeroRP, and AeroNP. Having verified these protocols through simulation and analysis, the next step towards deployment of the ANTP suite is developing a cross-platform implementation of the protocols. Towards this end we present a preliminary architecture for the protocol stack to
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New, Wesley. "Python based FPGA design-flow." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/20339.

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This dissertation undertakes to establish the feasibility of using MyHDL as a basis on which to develop an FPGA-based DSP tool-ow to target CASPER hardware. MyHDL is an open-source package which enables Python to be used as a hardware definition and verification language. As Python is a high-level language, hardware designers can use it to model and simulate designs, without needing detailed knowledge of the underlying hardware. MyHDL has the ability to convert designs to Verilog or VHDL allowing it to integrate into the more traditional design-ow. The CASPER tool- ow exhibits limitations such
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Eitzen, Benjamin. "GpuPy : efficiently using a GPU with Python." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Thesis/Summer2007/b_eitzen_082307.pdf.

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Silva, Alexandre Gonçalves. "Ambiente de suporte ao ensino de processamento de imagens usando a linguagem Python." [s.n.], 2003. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259828.

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Orientador: Roberto de Alencar Lotufo<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-03T06:21:14Z (GMT). No. of bitstreams: 1 Silva_AlexandreGoncalves_M.pdf: 3505020 bytes, checksum: c1f83603950906f46eeb9138e4f30df5 (MD5) Previous issue date: 2003<br>Mestrado
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Nielson, John A. "A Jython-based RESTful Web Service API for Python Code Reflection." ScholarWorks@UNO, 2018. https://scholarworks.uno.edu/td/2480.

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Often times groups of domain experts, such as scientists and engineers, will develop their own software modules for specialized computational tasks. When these users determine there is a need to integrate the data and computations used in their specialized components with an enterprise data management system, interoperability between the enterprise system and the specialized components rather than re-implementation allows for faster implementation and more flexible change management by shifting the onus of changes to the scientific components to the subject matter experts rather than the enter
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Fabbri, Lorenzo. "Implementazione in Python di un software per il calcolo delle metriche di combustione." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24224/.

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Implementazione di un software per il calcolo delle metriche relative alla combustione con il linguaggio Python. Vengono spiegate le fondamenta del linguaggio e come funziona il programma in questione.
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Kullberg, Jonathan. "En jämförelse av webb-ramverk i Python – Django och Pyramid." Thesis, Mittuniversitetet, Avdelningen för data- och systemvetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-29971.

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I dagens samhälle vill så väl företag som privatpersoner finnas på webben – det är en platform som de flesta förväntar sig hitta information på. För att minska på kostnaderna men samtidigt garantera såväl funktionalitet som säkerhet, så finns det webb-ramverk, ett slags bibliotek av funktioner för utvecklare att använda sig av. Företaget NTT Communications använder sig ofta av programmeringsspråket Python för utveckling av interna webb-applikationer. De är intresserade av att veta vilket webb-ramverk, för detta språk, som bäst möter de krav de ställer; snabb utveckling och modularitet. Till st
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Hardman, Owen Russell. "Optimizing a Network Layer Moving Target Defense by Translating Software from Python to C." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/64435.

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The security of powerful systems and large networks is often addressed through complex defenses. While these types of defenses offer increased security, they are resource intensive and therefore impractical to implement on many new classes of networked systems, such as mobile phones and small, embedded network infrastructure devices. To provide security for these systems, new defenses must be created that provide highly efficient security. The Moving Target IPv6 Defense (MT6D) is a network layer moving target defense that dynamically changes Internet Protocol version 6 (IPv6) addresses mid-ses
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Husein, Bassam, and Ihab Al-Maeeni. "PostIB : Framtagning av produkt för notifikation av post." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42411.

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PostIB tillhandahåller en produkt som skall kunna lämna en notifikation när brev eller paket anlänt till mottagarens brevlåda. Dessa notifikationer skall presenteras hemma för användaren. Då produkten inte finns på svenska marknaden, sattes projektplanen upp tillsammans i projektgruppen, där mål och krav definierades.   Arbetsprocessen inleddes med en marknadsanalys samt en kundundersökning, för att ta reda på samtliga möjliga lösningar för denna produkt. Genom kundundersökningen kunde man ta reda på vad potentiella kunder skulle vilja ha för funktioner i produkten. Den slutgiltiga rapporten i
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Andersson, Peter, and Robin Blomqvist. "Software Defined Network : Med openflow." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-28597.

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Detta projekt har haft som mål att skapa ett redundant SDN-nätverk som ska ligga som grund för ett fiktivt företag. Företeaget ska kunna använda nätverket som vi bygger upp för att vidareutveckla detta och anpassa det efter verksamhetens behov. Nätverket byggs upp med mininet som används för att simulera en nätverksmiljö. Det fiktiva företaget ska sedan bara kunna lyfta ut nätverket från mininet ut till ett riktigt nätverk. Nätverkets funktioner, såsom protokollen STP och LACP implementeras med hjälp av programmeringsspråket python.<br>The goal for this project is to setup a redundant Software
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Books on the topic "Software python"

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Nix, Markus, and Martin Grimme. Exploring Python: Software-Entwicklung für Profis. Entwickler.press [u.a.], 2005.

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Downey, Allen B. Think Python: An introduction to software design. SoHo Books, 2009.

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Ferrill, Paul. Pro Android Python with SL4A. Apress, 2011.

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Petter, Langtangen Hans, ed. Programming for Computations - Python: A Gentle Introduction to Numerical Simulations with Python. Springer Nature, 2016.

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Bearb, Gherman Dinu C., ed. Python Standard-Bibliothek. O'Reilly, 2002.

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Petter, Langtangen Hans, ed. Programming for Computations - Python: A Gentle Introduction to Numerical Simulations with Python 3.6. Springer Nature, 2020.

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Python: Python Basics for Beginners. Ladoo Publishing LLC, 2021.

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Python for Software Design. Cambridge University Press, 2009.

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Pillai, Anand Balachandran. Software Architecture with Python. Packt Publishing - ebooks Account, 2017.

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Lunch, Fredric. Instant Python Applications. O'Reilly Media, Incorporated, 1997.

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Book chapters on the topic "Software python"

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Loubser, Nico. "Programming in Python." In Software Engineering for Absolute Beginners. Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6622-9_4.

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Irving, Damien, Kate Hertweck, Luke Johnston, Joel Ostblom, Charlotte Wickham, and Greg Wilson. "Testing Software." In Research Software Engineering with Python. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003143482-12.

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Irving, Damien, Kate Hertweck, Luke Johnston, Joel Ostblom, Charlotte Wickham, and Greg Wilson. "Creating Packages with Python." In Research Software Engineering with Python. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003143482-15.

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Bräunl, Thomas. "Robot Software." In Robot Adventures in Python and C. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38897-3_2.

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Varga, Ervin. "Software Engineering." In Practical Data Science with Python 3. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4859-1_3.

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Martín Hernández, Edgar, and Mariano Martín. "Python for Chemical Engineering." In Introduction to Software for Chemical Engineers. CRC Press, 2019. http://dx.doi.org/10.1201/9780429451010-6.

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Lukasczyk, Stephan, Florian Kroiß, and Gordon Fraser. "Automated Unit Test Generation for Python." In Search-Based Software Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59762-7_2.

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Drymonitis, Alexandros. "Communicating with Other Software with OSC." In The Python Audio Cookbook. Focal Press, 2023. http://dx.doi.org/10.4324/9781003386964-6.

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Gladstone, Adam. "Building a Python Extension Module." In C++ Software Interoperability for Windows Programmers. Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7966-3_7.

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Misra, Sanjay, and Ferid Cafer. "A Software Metric for Python Language." In Computational Science and Its Applications – ICCSA 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12165-4_24.

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Conference papers on the topic "Software python"

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Moldovan, Vasilica-Andreea, Liviu-Marian Berciu, and Rares-Danut Patcas. "The Python Software Quality Dataset." In 2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). IEEE, 2024. https://doi.org/10.1109/seaa64295.2024.00066.

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Persaud, A., M. Ayllon Unzueta, E. K. Surry, and A. M. Parsons. "Python-based software tools for MCNP." In 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD). IEEE, 2024. http://dx.doi.org/10.1109/nss/mic/rtsd57108.2024.10655039.

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Latendresse, Jasmine, Naoures Day, SayedHassan Khatoonabadi, and Emad Shihab. "The Software Librarian: Python Package Insights for Copilot." In 2025 IEEE/ACM 47th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion). IEEE, 2025. https://doi.org/10.1109/icse-companion66252.2025.00014.

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Boloori, Aryan, and Tushar Sharma. "DPy: Code Smells Detection Tool for Python." In 2025 IEEE/ACM 22nd International Conference on Mining Software Repositories (MSR). IEEE, 2025. https://doi.org/10.1109/msr66628.2025.00119.

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Zhang, Zejun, Zhenchang Xing, Xin Xia, Xiwei Xu, and Liming Zhu. "Making Python code idiomatic by automatic refactoring non-idiomatic Python code with pythonic idioms." In ESEC/FSE '22: 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. ACM, 2022. http://dx.doi.org/10.1145/3540250.3549143.

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Niederhut, Dillon. "Software Transactional Memory in Pure Python." In Python in Science Conference. SciPy, 2017. http://dx.doi.org/10.25080/shinma-7f4c6e7-002.

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Kraft, Amanda, Matthew Widjaja, Trevor Sands, and Brad Galego. "Programmatically Identifying Cognitive Biases Present in Software Development." In Python in Science Conference. SciPy, 2021. http://dx.doi.org/10.25080/majora-1b6fd038-00c.

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Udler, Nadia. "Global optimization software library for research and education." In Python in Science Conference. SciPy, 2022. http://dx.doi.org/10.25080/majora-212e5952-019.

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Politz, Joe Gibbs, Alejandro Martinez, Matthew Milano, et al. "Python." In SPLASH '13: Conference on Systems, Programming, and Applications: Software for Humanity. ACM, 2013. http://dx.doi.org/10.1145/2509136.2509536.

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Benthall, Sebastian, Travis Pinney, JC Herz, and Kit Plummer. "An Ecological Approach to Software Supply Chain Risk Management." In Python in Science Conference. SciPy, 2016. http://dx.doi.org/10.25080/majora-629e541a-012.

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Reports on the topic "Software python"

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Sterbenz, James P., Mohammed Alenazi, Santosh A. Gogi, Dongsheng Zhang, Egemen K. Cetinkaya, and Justin P. Rohrer. ANTP Protocol Suite Software Implementation Architecture in Python. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada544633.

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McKnight, C., Drew Loney, and Kevin Winters. Watershed and catchment meshing Python tool utilizing the XmsMesh meshing software. Engineer Research and Development Center (U.S.), 2019. http://dx.doi.org/10.21079/11681/34323.

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Benoit, Jerome, Luke Scime, and Vincent Paquit. Peregrine Software Development: Report on the Code Conversion From Python to C++. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2472683.

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Ayoul-Guilmard, Q., R. Badia, J. Ejarque, et al. D1.3 First public Release of the solver. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.007.

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This deliverable presents the software release of Kratos Multiphysics, together with the XMC library, Hyperloom and PyCOMPSs API definition [8]. This report is meant to serve as a supplement to the public release of the software. Kratos is “a framework for building parallel, multi-disciplinary simulation software, aiming at modularity, extensibility, and high performance. Kratos is written in C++, and counts with an extensive Python interface”. XMC is a python library for hierarchical Monte Carlo algorithms. Hyperloom and PyCOMPSs are environments for enabling parallel and distributed computat
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May, Trent, Thomas Clement, John Miller, Charles Carleton, Aaron Webber, and Samuel Williams. From research to production : lessons learned and best practices. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49197.

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This paper provides an overview of best practices to assist individuals and teams in transitioning software from a research product into a production environment. The information contained in this paper consists of best practices and lessons learned from an assignment consisting of transitioning a science-based research suite of programs into a more modern software format with appropriate preparations and considerations to be deployed in a production environment. The original software suite was written using both MATLAB and Python programming languages, and the new production version was writt
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Ayoul-Guilmard, Q., S. Ganesh, F. Nobile, et al. D1.4 Final public Release of the solver. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.009.

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This deliverable presents the final software release of Kratos Multiphysics, together with the XMC library, Hyperloom and PyCOMPSs API definitions [13]. This release also contains the latest developements on MPI parallel remeshing in ParMmg. This report is meant to serve as a supplement to the public release of the software. Kratos is “a framework for building parallel, multi-disciplinary simulation software, aiming at modularity, extensibility, and high performance. Kratos is written in C++, and counts with an extensive Python interface”. XMC is “a Python library for parallel, adaptive, hiera
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Torres Londoño, Carlos Ignacio, Francy Yaneth Patiño-Martínez, and Yerson Ferney Porras García. Uso de entornos virtuales para el desarrollo de aplicaciones en Python. Ediciones Universidad Cooperativa de Colombia, 2023. https://doi.org/10.16925/gcgp.112.

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Los ambientes virtuales en Python, o venv, son fundamentales en el desarrollo de software, ya que permiten crear entornos de trabajo aislados para cada proyecto, garantizando la estabilidad y evitando conflictos entre dependencias. Son ampliamente utilizados en la industria, donde su implementación mejora la productividad y permite a los desarrolladores gestionar múltiples proyectos sin afectar el entorno general de desarrollo. En el ámbito académico, también son valiosos, ya que permiten a los estudiantes trabajar en proyectos individuales o colaborativos sin preocuparse por la compatibilidad
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Urban, Peter, and Eva Peschke. Multibeam echo grid simulator - Short description of the research software. GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany, 2023. http://dx.doi.org/10.3289/sw_3_2023.

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This repository contains the simulation code (python) for reproducing the results of the accepted paper "Echo grid integration: A novel method for preprocessing multibeam water column data to quantify underwater gas bubble emissions." by Urban et. al. 2023 (Accepted) The program simulates multibeam water column images for virtual surveys over individual targets or target clouds and allows for testing the effects of different echo grid integration methods. (See Urban et. al 2023 for more details)
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Tosi, R., R. Amela, M. Nuñez, et al. D1.2 First realease of the softwares. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.011.

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This deliverable presents the software release of the Kratos Multiphysics software [3], ”a framework for building parallel, multi-disciplinary simulation software, aiming at modularity, extensibility, and high performance. Kratos is written in C++, and counts with an extensive Python interface”. In this deliverable we focus on the development of Uncertainty Quantification inside Kratos. This takes place in the MultilevelMonteCarloApplication, a recent development inside the software that allows to deal with uncertainty quantification.
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10

Gerosa, Marco, David A. Wheeler, and Stephen Hendrick. Secure Software Development Education 2024 Survey: Understanding Current Needs. The Linux Foundation, 2024. https://doi.org/10.70828/cadl1649.

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How can we improve education on secure software development? The OpenSSF commissioned a study to hear directly from the software security community on the perceived gaps in their training, and how we can better support the securing of the software supply chain from an educational perspective. Key findings from the report indicate that an important minority of developers are not familiar with secure software development, and many identified a lack of training or a lack of awareness around the courses available. Python was highly rated by respondents for increased training, and ultimately securi
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