Abstract
In digital environment, generating reports is an integral part of any business, and therefore there is a huge need for a tool for creating complex adaptive reports in investment, marketing activities, financial projects etc. The purpose of the paper is to formulate the requirements for GPL for the creation of custom reports in different business areas and build a software product that will use it. We have researched the possibilities of creating a universal language for building complex reports that is flexible enough to be used in any business domain. We have also identified the main requirements for such a language and the software product that would utilize it. We have paid particular attention to the peculiarities and problems associated with the creation and use of such a language, and have proposed ways to address them. As an experiment, we have created a prototype software module using a language based on mathematical formulas. The developed module can be used both for reports and for any calculations of companies engaged in product and business analytics.
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References
Palmer, B.: What Are International Financial Reporting Standards (IFRS)? (2022). https://www.investopedia.com/terms/i/ifrs.asp/
Kobets, V., Yatsenko, V., Buiak, L.: Bridging business analysts competence gaps: labor market needs versus education standards. Commun. Comput. Inf. Sci. 1308, 22–45 (2021). https://doi.org/10.1007/978-3-030-77592-6_2
Kobets, V., Yatsenko, V., Mazur, A., Zubrii, M.: Data analysis of personalized investment decision making using robo-advisers. Sci. Innov. 16(2), 80–93 (2020). https://doi.org/10.15407/SCINE16.02.080
Savchenko, S., Kobets, V.: Development of robo-advisor system for personalized investment and insurance portfolio generation. Commun. Comput. Inf. Sci. 1635, 213–228 (2022). https://doi.org/10.1007/978-3-031-14841-5_14
Kobets, V., Petrov, O., Koval, S.: Sustainable robo-advisor bot and investment advice-taking behavior. Lect. Notes Bus. Inf. Process. 465, 15–35 (2022). https://doi.org/10.1007/978-3-031-23012-7_2
Kobets, V., Tsiuriuta, N., Lytvynenko, V., Novikov, M., Chizhik, S., et al.: Recruitment web-service management system using competence-based approach for manufacturing enterprises. In: Ivanov, V., et al. (ed.) DSMIE 2019. LNME, pp. 138–148. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22365-6_14
Kenton, W.: Business Segment Reporting Definition, Importance, Example (2021). https://www.investopedia.com/terms/b/business-segment-reporting.asp.
El-khoury, J., Berezovskyi, A., Nyberg, M.: An industrial evaluation of data access techniques for the interoperability of engineering software tools. J. Ind. Inf. Integr. 15, 58–68 (2019). https://doi.org/10.1016/j.jii.2019.04.004
Lu, X.: Automatic analysis of syntactic complexity in second language writing. Int. J. Corpus Linguist. 15(4), 474–496 (2010). https://doi.org/10.1075/ijcl.15.4.02lu
Hayes, A.: eXtensible Business Reporting Language (XBRL): Investor's Guide (2022). https://www.investopedia.com/terms/x/xbrl.asp.
Bondar, S., Ruppert, C., Stjepandić, J.: Ensuring data quality beyond change management in virtual enterprise. Int. J. Agile Syst. Manag. 7(3–4), 304–323 (2014). https://doi.org/10.1504/IJASM.2014.065346
Nguyen, M.-T., Le, D.T., Le, L.: Transformers-based information extraction with limited data for domain-specific business documents. Eng. Appl. Artif. Intell. 97, 104100 (2021)
Seng, J.-L., Lai, J.T.: An Intelligent information segmentation approach to extract financial data for business valuation. Expert Syst. Appl. 37, 6515–6530 (2010). https://doi.org/10.1016/j.eswa.2010.02.134
Duque, J., Godinhob, A., Vasconceloscd, J.: Knowledge data extraction for business intelligence. Procedia Comput. Sci. 204, 131–139 (2022)
Giner-Miguelez, J., Gómez, A., Cabot, J.: A domain-specific language for describing machine learning datasets. J. Comput. Lang. 76, 101209 (2023)
Quintero, A.M.R., Pérez, S.M., Varela-Vaca, A.J., López, M.T.G., Cabot, J.: A domain-specific language for the specification of UCON policies. J. Inf. Secur. Appl. 64, 103006 (2022)
Vidal, M., Massoni, T., Ramalho, F.: A domain-specific language for verifying software requirement constraints. Sci. Comput. Program. 197, 102509 (2020)
Chavarriaga, E., Jurado, F., Rodríguez, F.D.: An approach to build JSON-based domain specific languages solutions for web applications. J. Comput. Lang. 75, 101203 (2023)
Rodrígueza, A., Macíasd, F., Duránc, F., Rutle, A., Wolter, U.: Composition of multilevel domain-specific modelling languages. J. Logical Algebr. Methods Program. 130, 100831 (2023)
Aysolmaz, B., Leopold, H., Reijers, H.A., Demirörs, O.: A semi-automated approach for generating natural language requirements documents based on business process models. Inf. Softw. Technol. 93, 14–29 (2018). https://doi.org/10.1016/j.infsof.2017.08.009
Enia, L.C.: Empirical research: exploring extensible business reporting language and views of Romanian accountants. Procedia Econ. Finan. 32, 1675–1699 (2015). https://doi.org/10.1016/S2212-5671(15)01495-1
Behera, R.K., Bala, P.K., Rana, N.P., Irani, Z.: Responsible natural language processing: a principlist framework for social benefits. Technol. Forecast. Soc. Chang. 188, 122306 (2023). https://doi.org/10.1016/j.techfore.2022.122306
Choia, J., Jeong, B., Yoonc, J.: Identification of emerging business areas for business opportunity analysis: an approach based on language model and local outlier factor. Comput. Ind. 140, 103677 (2022). https://doi.org/10.1016/j.compind.2022.103677
Kobeissi, M., Assy, N., Gaaloul, W., Defude, B., Benatallah, B., Haidar, B.: Natural language querying of process execution data. Inf. Syst. 116, 102227 (2023). https://doi.org/10.1016/j.is.2023.102227
Best, R.: Best Asset Management Software (2023). https://www.investopedia.com/best-asset-management-software-5090064
Carmody, B.: Best Tenant Screening Services (2023). https://www.investopedia.com/best-tenant-screening-services-5070361
Kenton, W.: Visual Basic for Applications (VBA): Definition, Uses, Examples (2022). https://www.investopedia.com/terms/v/visual-basic-for-applications-vba.asp.
Hicks, M., Levin, D.: CMSC 330: Organization of Programming Languages (2013). https://www.coursehero.com/file/178765173/org-of-Progpdf/
ANother Tool for Language Recognition. https://www.antlr.org/documentation.html. Accessed 29 May 2023
ANTLR. https://github.com/antlr/antlr4. Accessed 29 May 2023
JAVACC, https://javacc.github.io/javacc/documentation/. Accessed 29 May 2023
GNU Bison. https://www.gnu.org/software/bison/. Accessed 29 May 2023
Hibernate. https://hibernate.org/. Accessed 29 May 2023
Spring Data. https://spring.io/projects/spring-data. Accessed 29 May 2023
Apache POI. https://poi.apache.org/. Accessed 29 May 2023
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Iatsiuta, V., Kobets, V., Ivanov, O. (2023). Creating of a General Purpose Language for the Construction of Dynamic Reports. In: Maślankowski, J., Marcinkowski, B., Rupino da Cunha, P. (eds) Digital Transformation. PLAIS EuroSymposium 2023. Lecture Notes in Business Information Processing, vol 495. Springer, Cham. https://doi.org/10.1007/978-3-031-43590-4_2
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