Relevant bibliographies by topics / Language code

Contents

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

Academic literature on the topic 'Language code'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Language code"

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HAN, YO-SUB, and KAI SALOMAA. "OVERLAP-FREE LANGUAGES AND SOLID CODES." International Journal of Foundations of Computer Science 22, no. 05 (2011): 1197–209. http://dx.doi.org/10.1142/s0129054111008647.

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Solid codes have a nice property called synchronization property, which is useful in data transmission. The property is derived from infix-freeness and overlap-freeness of solid codes. Since a code is a language, we look at solid codes from formal language viewpoint. In particular, we study regular solid codes (that are solid codes and regular). We first tackle the solid code decidability problem for regular languages and propose a polynomial time algorithm. We, then, investigate the decidability of the overlap-freeness property and show that it is decidable for regular languages but is undeci
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Amin, Mujid Farihul. "Wujud Campur Kode Takserumpun dalam Wacana Berita Daerah Harian Suara Merdeka." Nusa: Jurnal Ilmu Bahasa dan Sastra 13, no. 4 (2018): 590. http://dx.doi.org/10.14710/nusa.13.4.590-603.

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Language events that often occur in daily interactions are the mixing of a code/ element of language into the code/element of another language. These linguistic events in sociolinguistics are known as mixed codes. Based on the language of the source, the mixed code in the Suara Merdeka daily news discourse can be divided into two types, namely the cognate mixed code and the noncognate mixed code. In this paper, only the noncognate mixed code. In the noncognate mixed code, between the source language and the target language have no relationship, both geographically and genetically. So, geograph
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Fauzan, Achmad, and Ratna Dewi Kartikasari. "ANALISIS PENGGUNAAN KODE BAHASA DALAM KOMUNIKASI RUANG LINGKUP MAHASISWA FIP UMJ." Jurnal Komposisi 6, no. 1 (2023): 51. http://dx.doi.org/10.53712/jk.v6i1.1784.

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The large variety of languages used by FIP UMJ students are bilingual and multilingual. This led to the selection of codes used in the utterances of UMJ FIP students. The purpose of this study was to describe the selection of codes used by UMJ FIP students. Based on the Betawi students' speech, the code selection was (1) single language, which includes non-formal Indonesian, Betawi language, and Sundanese language; (2) code switching; and (3) code mix.
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Mileh, I. Nengah. "CAMPUR KODE PEMAKAIAN BAHASA INDONESIA PADA WACANA IKLAN." KULTURISTIK: Jurnal Bahasa dan Budaya 4, no. 1 (2020): 35. http://dx.doi.org/10.22225/kulturistik.4.1.1560.

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This study is entitled "Mixing Indonesian Language Codes in Advertising Discourse". The use of Indonesian in discourse advertisements has taken place in another language, namely local languages and foreign languages. This study examines the factors that cause code mixing, the types and forms / forms of code mixing, and the social meaning that is caused by the code mixing. The study uses the method of observation (observation) and data collection techniques, descriptive qualitative methods used in analyzing data, and informal methods used to collect the results of the analysis. In this study fo
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Li, Wen, Junfei Xu, and Qi Chen. "Knowledge Distillation-Based Multilingual Code Retrieval." Algorithms 15, no. 1 (2022): 25. http://dx.doi.org/10.3390/a15010025.

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Semantic code retrieval is the task of retrieving relevant codes based on natural language queries. Although it is related to other information retrieval tasks, it needs to bridge the gaps between the language used in the code (which is usually syntax-specific and logic-specific) and the natural language which is more suitable for describing ambiguous concepts and ideas. Existing approaches study code retrieval in a natural language for a specific programming language, however it is unwieldy and often requires a large amount of corpus for each language when dealing with multilingual scenarios.
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Retnaningtyas, Hanova Rani Eka, Mangatur Rudolf Nababan, and Dwi Purnanto. "Language Code Choice of Male Abdi Dalem of Karaton Ngayogyakarta Hadiningrat." Lingua Cultura 13, no. 2 (2019): 99. http://dx.doi.org/10.21512/lc.v13i1.5326.

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This research aimed to show the language code choices of male abdi dalem of Karaton Ngayogyakarta Hadiningrat because each community had its own language code choice in their daily lives, including every individual. This research was a descriptive qualitative study conducted to determine the language code choice of abdi dalem Karaton Ngayogyakarta Hadiningrat. Data were taken using questionnaires. The form of questions used was closed questions to find out the language codes choice. In addition, the open questions were used to find out the reason for selecting particular language codes. The da
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Köster, Marcel, Roland Leißa, Sebastian Hack, Richard Membarth, and Philipp Slusallek. "Code Refinement of Stencil Codes." Parallel Processing Letters 24, no. 03 (2014): 1441003. http://dx.doi.org/10.1142/s0129626414410035.

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A straightforward implementation of an algorithm in a general-purpose programming language does usually not deliver peak performance: Compilers often fail to automatically tune the code for certain hardware peculiarities like memory hierarchy or vector execution units. Manually tuning the code is firstly error-prone as well as time-consuming and secondly taints the code by exposing those peculiarities to the implementation. A popular method to avoid these problems is to implement the algorithm in a Domain-Specific Language (DSL). A DSL compiler can then automatically tune the code for the targ
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Du, Yangkai, Tengfei Ma, Lingfei Wu, Xuhong Zhang, and Shouling Ji. "AdaCCD: Adaptive Semantic Contrasts Discovery Based Cross Lingual Adaptation for Code Clone Detection." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 16 (2024): 17942–50. http://dx.doi.org/10.1609/aaai.v38i16.29749.

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Code Clone Detection, which aims to retrieve functionally similar programs from large code bases, has been attracting increasing attention. Modern software often involves a diverse range of programming languages. However, current code clone detection methods are generally limited to only a few popular programming languages due to insufficient annotated data as well as their own model design constraints. To address these issues, we present AdaCCD, a novel cross-lingual adaptation method that can detect cloned codes in a new language without annotations in that language. AdaCCD leverages languag
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Sarah Evelyn Samosir, Ririn Marpaung, Anisa Berti Tua Ambarita, Hanna Sitohang, Friska Maria, and Eka Putri Saptari Wulan. "Analisis Penggunaan Campur Kode Dan Ahli Kode Dalam Kata Sambutan." Semantik : Jurnal Riset Ilmu Pendidikan, Bahasa dan Budaya 2, no. 1 (2023): 58–68. http://dx.doi.org/10.61132/semantik.v2i1.189.

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Code switching and code mixing are various variations of language by a person or certain community groups, for example in schools, offices, housing and traditional markets. Traditional markets themselves can be said to be centers of interaction and transactions that allow speakers and speech partners to come from various regions with different backgrounds, statuses and mastery of languages. Differences in social backgrounds in speech communities in traditional market environments result in greater opportunities for the emergence of code-switching and code-mixing phenomena, and are interesting
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PRYGOZHEV, Oleksandr. "LANGUAGE INDEPENDENT SOFTWARE CODE REPOSITORY." Herald of Khmelnytskyi National University. Technical sciences 309, no. 3 (2022): 221–28. http://dx.doi.org/10.31891/2307-5732-2022-309-3-221-228.

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The article considers the construction of a language-independent repository of program code, which is based on a new model of program code representation based on a multigraph with tokens of the subject area. The main analogues of the system and the models on which they are based are considered: finite state machines, Petri nets, P-schemes. A comparative analysis of similar solutions is given. During the analysis, three main indicators were used: the ability to model the implementation of the program step by step (“white box”), the ability to build an interface in natural language, isomorphism
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Dissertations / Theses on the topic "Language code"

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Premtoon, Varot. "Multi-language code search." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123209.

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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 74-75).<br>Searching for specified code patterns is a common component in many types of programming tools for any language. Unfortunately, there is no code search approach that produces application-friendly search results and
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Tsai, Michael J. (Michael Jordan) 1979. "Code generation for the IOA language." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/87839.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.<br>Includes bibliographical references (leaves 171-174).<br>by Michael J. Tsai.<br>M.Eng.
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Lecerf, Jason. "Designing language-agnostic code transformation engines." Thesis, Lille 1, 2019. http://www.theses.fr/2019LIL1I077.

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Les transformations automatiques de code apparaissent dans diverses situations, les refactorings, les migrations inter-langages ou encore la spécialisation de code. Les moteurs supportant ces transformations cherchent dans le code source les occurrences de motifs spécifiés par l’utilisateur, puis les réécrivent grâce à une transformation. Cette transformation peut soit modifier les occurrences elles-mêmes, des éléments de la représentation intermédiaire (IR) du langage, en nouveaux éléments ou réécrire leur code source. Nous nous concentrons sur la réécriture de code source qui offre une meill
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Smith-Kocamahhul, Joan. "Language choice, code-switching and language shift in Antakya, Turkey." Thesis, University of Canterbury. School of Languages, Cultures and Linguistics, 2003. http://hdl.handle.net/10092/2839.

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Although Arabic is one of the world's ten largest languages in terms of numbers of speakers, the Arabic language in Turkey is in decline. This is due to the position of Turkish as the sole official language there and to other factors of social change (significantly migration). This thesis presents one of the first pieces of research into the shift from Arabic to Turkish in Turkey, focused on the city of Antakya (Antioch). The thesis has multiple goals. Firstly, it sketches the background of the Arabic-speaking community as it relates to the history of the language in the area. Secondly, it pre
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Youkhana, Sana. "Code-switching in the foreign language classroom." Thesis, Högskolan för lärande och kommunikation, Högskolan i Jönköping, HLK, Ämnesforskning, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-14779.

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It is a frequently observed phenomenon that language learners often turn to their native language in the foreign language classroom, i.e. they code-switch, but why is it so? In order to investigate this, this study had two aims; the first aim was about trying to see if the frequency of code-switching differed depending on the questions’ levels of difficulty. This study was conducted on three different upper-secondary schools and involved 24 pupils. The pupils’ age varied from 16 to 19. The hypotheses were that pupils code-switch less when answering basic level questions and more when answering
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Hodges, Steve. "Revealing code what can language teach software? /." Thesis, Available online, Georgia Institute of Technology, 2004:, 2004. http://etd.gatech.edu/theses/available/etd-03292004-211229/unrestricted/hodges%5Fsteven%5F200405%5Fms.pdf.

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Thesis (M.S.)--Literature, Communication, and Culture, Georgia Institute of Technology, 2004.<br>Eugene Thacker, Committee Chair ; Xin Wei Sha, Committee Member ; Stephen Mamber, Committee Member ; Jay Bolter, Committee Member. Includes bibliographical references (leaves 87-89).
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Zirker, Kelly Ann Hill. "Intrasentential vs. Intersentential Code Switching in Early and Late Bilinguals." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1885.pdf.

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Blomquist, Linda. "Language and Identity : Attitudes towards code-switching in the immigrant language classroom." Thesis, Umeå University, Department of language studies, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-23411.

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<p>Although many studies have been conducted on second language acquisition and bilingual education, little is known about the role of language in the formation of identity by adolescent immigrants in the language classroom. More specifically, this study aims to investigate the use of code-switching by immigrant and refugee students learning Swedish and English in a high school preparatory program. Furthermore, this study investigates the relationship between students’ and teachers’ attitudes towards code-switching and language as a resource, and theories on language as a marker of identity. Q
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Byström, Adam. "From Intent to Code : Using Natural Language Processing." Thesis, Uppsala universitet, Avdelningen för datalogi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325238.

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Programming and the possibility to express one’s intent to a machine is becoming a very important skill in our digitalizing society. Today, instructing a machine, such as a computer to perform actions is done through programming. What if this could be done with human language? This thesis examines how new technologies and methods in the form of Natural Language Processing can be used to make programming more accessible by translating intent expressed in natural language into code that a computer can execute. Related research has studied using natural language as a programming language and usin
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Kohan, Carolyn Mae. "The code of war, William Blake's secret language." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ37349.pdf.

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Books on the topic "Language code"

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Schmid, Monika S. Language attrition. Cambridge University Press, 2011.

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Electronica, Ars, ed. Code: The language of our time : code = law, code = art, code = life. MIT, 2003.

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Mahootian, Shahrzad, Mark Sebba, and Carla Jonsson. Language mixing and code-switching in writing: Approaches to mixed-language written discourse. Routledge, 2012.

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Gerfried, Stocker, and Schöpf Christine, eds. Ars electronica: Code-the language of our time : code=law code=art code=life. Hatje Cantz, 2003.

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W, Martin Peter, Oz̊óg Conrad, and Poedjosoedarmo Gloria R. 1943-, eds. Language use and language change in Brunei Darussalam. Ohio University Center for International Studies, 1996.

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Martinez, Victor Soto. Identifying and Modeling Code-Switched Language. [publisher not identified], 2020.

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ill, Maestro Giulio, ed. Train whistles: A language in code. Lothrop, Lee & Shepard Books, 1985.

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Abrash, Michael. Zen of code optimization. Coriolis Group Books, 1994.

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Library of Congress. Network Development and MARC Standards Office., ed. MARC code list for languages. 2nd ed. Library of Congress, Cataloging Distribution Service, 2000.

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Vézina, Alain. Code grammatical fondamental. Mondia, 1989.

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Book chapters on the topic "Language code"

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Weik, Martin H. "language code." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_9922.

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Barbieri, Marcello. "Origins of Language." In Code Biology. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14535-8_8.

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Muysken, Pieter. "Code-switching processes." In Language Choices. John Benjamins Publishing Company, 1997. http://dx.doi.org/10.1075/impact.1.25muy.

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Berton, Luca. "Ansible Language Code." In Ansible for Kubernetes by Example. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9285-3_2.

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Auer, Peter, and Carol M. Eastman. "Code-switching." In Society and Language Use. John Benjamins Publishing Company, 2010. http://dx.doi.org/10.1075/hoph.7.06aue.

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Keller, Mareike L. "Understanding the Grammar of Mixed Language." In Code-Switching. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34667-6_2.

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Smith, Stephen. "Thumb Code." In Raspberry Pi Assembly Language Programming. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5287-1_15.

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Smith, Stephen. "Optimizing Code." In RISC-V Assembly Language Programming. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0137-2_12.

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Smith, Stephen. "Hacking Code." In RISC-V Assembly Language Programming. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0137-2_14.

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Mišeska Tomić, Olga. "Language contact, language system and language code." In Yugoslav General Linguistics. John Benjamins Publishing Company, 1989. http://dx.doi.org/10.1075/llsee.26.21mis.

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Conference papers on the topic "Language code"

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Sun, Tao, Linzheng Chai, Jian Yang, et al. "UniCoder: Scaling Code Large Language Model via Universal Code." In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.acl-long.100.

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He, Hongkui, Jiexin Wang, Liuwen Cao, and Yi Cai. "CLCoSum: Curriculum Learning-Based Code Summarization for Code Language Models." In 2025 IEEE/ACM 33rd International Conference on Program Comprehension (ICPC). IEEE, 2025. https://doi.org/10.1109/icpc66645.2025.00035.

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Lalith, Pecheti Charan, Sujal Goel, Misha Kakkar, and Seema Sharma. "Simplifying code translation: Custom syntax language to C language transpiler." In 2025 2nd International Conference on Computational Intelligence, Communication Technology and Networking (CICTN). IEEE, 2025. https://doi.org/10.1109/cictn64563.2025.10932385.

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Kadosh, Tal, Niranjan Hasabnis, Vy A. Vo, et al. "MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks." In 2024 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2024. https://doi.org/10.1109/hpec62836.2024.10938441.

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Pyda, Srivishnu, Daniel Nichols, and Abhinav Bhatele. "The Shortcomings of Code LLMs in Modeling Code Properties." In 2025 IEEE/ACM International Workshop on Large Language Models for Code (LLM4Code). IEEE, 2025. https://doi.org/10.1109/llm4code66737.2025.00029.

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Abid, Muhammad Salman, Mrigank Pawagi, Sugam Adhikari, et al. "GlueTest: Testing Code Translation via Language Interoperability." In 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 2024. https://doi.org/10.1109/icsme58944.2024.00061.

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Na�r, Marwa, Kamel Yamani, Lynda Lhadj, and Riyadh Baghdadi. "Curriculum Learning for Small Code Language Models." In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.acl-srw.44.

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Juhász, Levente Zsolt. "Large Language Models, Fine Tuning, Code Generation." In 2024 IEEE 7th International Conference and Workshop Óbuda on Electrical and Power Engineering (CANDO-EPE). IEEE, 2024. https://doi.org/10.1109/cando-epe65072.2024.10772760.

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Khati, Dipin. "Trustworthiness of Large Language Models for Code." In 2025 IEEE/ACM 47th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion). IEEE, 2025. https://doi.org/10.1109/icse-companion66252.2025.00063.

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Puerto, Haritz, Martin Tutek, Somak Aditya, Xiaodan Zhu, and Iryna Gurevych. "Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.629.

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Reports on the topic "Language code"

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Schneider, Fred B., Dexter Kozen, Greg Morrisett, and Andrew Myers. Language-Based Security for Malicious Mobile Code. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada404325.

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Schneider, Fred B., Dexter Kozen, Greg Morrisett, and Andrew Myers. Language-Based Security for Malicious Mobile Code. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada427018.

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Tratz, Stephen C. Arabic Natural Language Processing System Code Library. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada603814.

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Schneider, Fred B. Language-Based Security for Malicious Mobile Code. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada475236.

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Lee, Benjamin Yen Kit. Automated neuron explanation for code-trained language models. Iowa State University, 2024. http://dx.doi.org/10.31274/cc-20240624-267.

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Zhao, Xiaoquan. Latent space analysis and alignment for cross-Language code translation. Iowa State University, 2024. https://doi.org/10.31274/cc-20250502-39.

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Yi, Qing, Richard Clint Whaley, Apan Qasem, and Daniel Quinlan. Final Report A Multi-Language Environment For Programmable Code Optimization and Empirical Tuning. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1124136.

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Tesink, K., and R. Fox. A Uniform Resource Name (URN) Namespace for the Common Language Equipment Identifier (CLEI) Code. RFC Editor, 2005. http://dx.doi.org/10.17487/rfc4152.

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Spielauer, Martin. The "LifeCourse" model, a competing risk cohort microsimulation model: source code and basic concepts of the generic microsimulation programming language Modgen. Max Planck Institute for Demographic Research, 2006. http://dx.doi.org/10.4054/mpidr-wp-2006-046.

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Gruber, Peter. Using ChatGPT and Copilot for Efficient Data Analysis in R. Instats Inc., 2023. http://dx.doi.org/10.61700/0lgrq7wtqjztt469.

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This workshop provides a 21st-century introduction to [b]Statistical Analysis with R,[/b] focusing on the efficient use of [b]AI assistants[/b] such as Github Copilot and ChatGPT. Participants will learn step by step how to install AI tools and how to harness their power. They will be able to create R code in the blink of an eye and with unprecedented ease of use. They will learn the principles of the R language, an important fundament for competently assessing and using AI-generated code. An official Instats certificate of completion is provided at the conclusion of the seminar along with 2 E
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