Investigating Computational Solutions for Metadata Processing in Software Engineering Experiments
Resumo
Metadata consists of elements that describe specific data content. When structured according to standards, metadata improves data interoperability. In this context, it is understood that adopting metadata could contribute to describing experiments in Software Engineering. Furthermore, the use of tools can help in the management. Considering the context, this study includes a Systematic Mapping to identify solutions for the computational processing of metadata in SE experiments. Following the execution of the search strategy, a total of 31 studies were reviewed. The mapping did not achieve satisfactory results. Consequently, a Non-Systematic Review was conducted. In this case, a set of solutions were found.
Palavras-chave:
metadata, dublin core, tools for metadata, experiments
Referências
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Cao, S., Gao, Y., Gao, X., and Chen, G. (2019). Adam. Cha, M.-H., Kim, D.-O., Kim, H.-Y., and Kim, Y.-K. (2016). Adaptive metadata rebalance in exascale file system. The Journal of Supercomputing, 73(4):1337–1359.
Cha, M.-H., Lee, S.-M., Kim, H.-Y., and Kim, Y.-K. (2019). Effective metadata management in exascale file system. The Journal of Supercomputing, 75(11):7665–7689.
Chen, Z.-G., Liu, Y.-B., Wang, Y.-F., and Lu, Y.-T. (2021). A gpu-accelerated in-memory metadata management scheme for large-scale parallel file systems. Journal of Computer Science and Technology, 36(1):44–55.
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Dai, M. and Zhu, D. (2018). An effective grouping method for unstructured data based on swift.
Dong, D., Carns, P., Ross, R., Jenkins, J., Blauer, K., and Chen, Y. (2015). Graphtrek: Asynchronous graph traversal for property graph-based metadata management.
Dong, D., Carns, P., Ross, R., Jenkins, J., Muirhead, N., and Chen, Y. (2016). An asynchronous traversal engine for graph-based rich metadata management. Parallel Computing, 58:140–156.
Feng, L. and Jonker, W. (2003). Efficient processing of secured xml metadata. In Meersman, R. and Tari, Z., editors, On The Move to Meaningful Internet Systems 2003: OTM 2003 Workshops, pages 704–717, Berlin, Heidelberg. Springer Berlin Heidelberg.
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Gao, Y., Gao, X., Yang, X., Liu, J., and Chen, G. (2019). An efficient ring-based metadata management policy for large-scale distributed file systems. IEEE Transactions on Parallel and Distributed Systems, 30(9):1962–1974.
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Rao, J., Ao, T., Dai, K., and Zou, X. (2019). Arce: Towards code pointer integrity on embedded processors using architecture-assisted run-time metadata management. IEEE Computer Architecture Letters, 18(2):115–118.
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Santana, F., Cordeiro, A., and OliveiraJr, E. (2023a). Dublin core for recording metadata of experiments in software engineering: A survey. In Anais da VII Escola Regional de Engenharia de Software, pages 169–177, Porto Alegre, RS, Brasil. SBC.
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Santana, F., Cordeiro, A., and OliveiraJr, E. (2023c). Use of the dublin core standard to express open metadata related to software engineering experiments. In Anais do III Workshop de Práticas de Ciência Aberta para Engenharia de Software, pages 1–5, Porto Alegre, RS, Brasil. SBC.
Varga, J., Romero, O., Pedersen, T. B., and Thomsen, C. (2018). Analytical metadata modeling for next generation bi systems. Journal of Systems and Software, 144:240–254.
Wazlawick, R. S. (2013). Engenharia de Software. Elsevier, Rio de Janeiro, Brazil, 1st edition.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M., Regnell, B., and Wesslén, A. (2012). Experimentation in Software Engineering. Computer Science. Springer Berlin Heidelberg.
Xiong, J., Hu, Y., Li, G., Tang, R., and Fan, Z. (2011). Metadata distribution and consistency techniques for large-scale cluster file systems. IEEE Transactions on Parallel and Distributed Systems, 22(5):803–816.
Zeng, Y. and Veeravalli, B. (2014). Optimal metadata replications and request balancing strategy on cloud data centers. The Journal of Supercomputing, 74(11):4512–4525.
Zhou, C., Li, X., and Zhou, C. (2019). Efficient metadata management and intelligent scheduling in exascale systems. Future Generation Computer Systems, 82:100–108.
Ampatzoglou, A. et al. (2019). Identifying, categorizing and mitigating threats to validity in software engineering secondary studies. Information and Software Technology, 106:201–230.
Bhanuse, S. S., Kamble, S. D., and Kakde, S. M. (2016). Text mining using metadata for generation of side information. Procedia Computer Science, 78:807–814.
Cao, S., Gao, Y., Gao, X., and Chen, G. (2019). Adam. Cha, M.-H., Kim, D.-O., Kim, H.-Y., and Kim, Y.-K. (2016). Adaptive metadata rebalance in exascale file system. The Journal of Supercomputing, 73(4):1337–1359.
Cha, M.-H., Lee, S.-M., Kim, H.-Y., and Kim, Y.-K. (2019). Effective metadata management in exascale file system. The Journal of Supercomputing, 75(11):7665–7689.
Chen, Z.-G., Liu, Y.-B., Wang, Y.-F., and Lu, Y.-T. (2021). A gpu-accelerated in-memory metadata management scheme for large-scale parallel file systems. Journal of Computer Science and Technology, 36(1):44–55.
Colace, F., Santo, M. D., Molinara, M., and Percannella, G. (2003). An automatic learning contents selector based on metadata standards. In Proceedings of the ITRE, volume 1, pages 431–435, Newark, USA. IEEE.
Cristina, R. (2010). Metadados como elementos do processo de catalogação. Aleph UCLA Undergraduate Research Journal for the Humanities and Social Sciences.
Dai, M. and Zhu, D. (2018). An effective grouping method for unstructured data based on swift.
Dong, D., Carns, P., Ross, R., Jenkins, J., Blauer, K., and Chen, Y. (2015). Graphtrek: Asynchronous graph traversal for property graph-based metadata management.
Dong, D., Carns, P., Ross, R., Jenkins, J., Muirhead, N., and Chen, Y. (2016). An asynchronous traversal engine for graph-based rich metadata management. Parallel Computing, 58:140–156.
Feng, L. and Jonker, W. (2003). Efficient processing of secured xml metadata. In Meersman, R. and Tari, Z., editors, On The Move to Meaningful Internet Systems 2003: OTM 2003 Workshops, pages 704–717, Berlin, Heidelberg. Springer Berlin Heidelberg.
Formenton, D. et al. (2018). Os padrões de metadados como recursos tecnológicos para a garantia da preservação digital. Biblios: Journal of Librarianship and Information Science, (68):82–95.
Gao, Y., Gao, X., Yang, X., Liu, J., and Chen, G. (2019). An efficient ring-based metadata management policy for large-scale distributed file systems. IEEE Transactions on Parallel and Distributed Systems, 30(9):1962–1974.
Guerra, E., Alves, F., Kulesza, U., and Fernandes, C. (2013). A reference architecture for organizing the internal structure of metadata-based frameworks. Journal of Systems and Software, 86(5):1239–1256.
Ha, Y.-g. and Jang, B.-s. (2015). Efficient tva metadata encoding for mobile and ubiquitous content services. Pervasive and Mobile Computing, 24:91–100.
Hayslett, M. (2023). Libguides: Metadata for data management: A tutorial: Intro. [link].
Hong, K., Hu, J., and Chen, X. (2010). Research on information metadata standards of knowledge organization - a case study of chinese digital library. Proceedings of the International Conference on Computer and Information Science (ICIS).
Huang, X., Gao, Y., Zhou, X., Gao, X., and Chen, G. (2023). An adaptive metadata management scheme based on deep reinforcement learning for large-scale distributed file systems. IEEE/ACM Transactions on Networking, 31(6):2840–2853.
ISO (2011). Iso/iec 25010:2011 - systems and software engineering – systems and software quality requirements and evaluation (square) – system and software quality models. Accessed: 2024-08-30.
Kitchenham, B. et al. (2007). Guidelines for performing systematic literature reviews in software engineering.
Lorist, H. H. J. and van der Meer, K. (2001). Standards for digital libraries and archives: Digital longevity. pages 89–98.
Motelet, O., Baloian, N., and Pino, J. A. (2008). Taking advantage of metadata semantics: the case of learning-object-based lesson graphs. Knowledge and Information Systems, 20(3):323–348.
Nakagawa, E. Y. et al. (2017). Revisão sistemática da literatura em engenharia de software: teoria e prática.
Nguyen, M. C., Won, H., Son, S., Gil, M.-S., and Moon, Y.-S. (2017). Prefetching-based metadata management in advanced multitenant hadoop. The Journal of Supercomputing, 75(2):533–553.
NISO (2017). Understanding metadata: What is metadata, and what is it for?: A primer — niso website. [link].
Petersen, K. et al. (2008). Systematic mapping studies in software engineering. In 12th International Conference on Evaluation and Assessment in Software Engineering (EASE) 12, pages 1–10.
Pfeiffer, R.-H. (2020). What constitutes software? an empirical, descriptive study of artifacts. In Proceedings of the 17th International Conference on Mining Software Repositories, MSR ’20, page 481–491, New York, NY, USA. Association for Computing Machinery.
Pöttker, L. M. V., Ferneda, E., and Moreiro-González, J. A. (2018). Mapeamento relacional entre padrões de metadados educacionais. Perspectivas em Ciência da Informação, 23(3):25–38.
Rao, J., Ao, T., Dai, K., and Zou, X. (2019). Arce: Towards code pointer integrity on embedded processors using architecture-assisted run-time metadata management. IEEE Computer Architecture Letters, 18(2):115–118.
Rehak, D. R. and Mason, R. (2003). Engaging with the learning object economy. In Littlejohn, A., editor, Reusing online resources: a sustainable approach to e-learning, pages 22–30. Kogan Page, London.
Rocha, L., Sales, L., and Sayão, L. (2017). Descrever para preservar: metadados como ferramenta para gestão de dados de pesquisa. ISKO Brasil, 5(2):194–201.
Santana, F., Cordeiro, A., and OliveiraJr, E. (2023a). Dublin core for recording metadata of experiments in software engineering: A survey. In Anais da VII Escola Regional de Engenharia de Software, pages 169–177, Porto Alegre, RS, Brasil. SBC.
Santana, F., Cordeiro, A., and OliveiraJr, E. (2023b). Metadata standards: a review towards modeling experiments. In Anais da VII Escola Regional de Engenharia de Software, pages 159–168, Porto Alegre, RS, Brasil. SBC.
Santana, F., Cordeiro, A., and OliveiraJr, E. (2023c). Use of the dublin core standard to express open metadata related to software engineering experiments. In Anais do III Workshop de Práticas de Ciência Aberta para Engenharia de Software, pages 1–5, Porto Alegre, RS, Brasil. SBC.
Varga, J., Romero, O., Pedersen, T. B., and Thomsen, C. (2018). Analytical metadata modeling for next generation bi systems. Journal of Systems and Software, 144:240–254.
Wazlawick, R. S. (2013). Engenharia de Software. Elsevier, Rio de Janeiro, Brazil, 1st edition.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M., Regnell, B., and Wesslén, A. (2012). Experimentation in Software Engineering. Computer Science. Springer Berlin Heidelberg.
Xiong, J., Hu, Y., Li, G., Tang, R., and Fan, Z. (2011). Metadata distribution and consistency techniques for large-scale cluster file systems. IEEE Transactions on Parallel and Distributed Systems, 22(5):803–816.
Zeng, Y. and Veeravalli, B. (2014). Optimal metadata replications and request balancing strategy on cloud data centers. The Journal of Supercomputing, 74(11):4512–4525.
Zhou, C., Li, X., and Zhou, C. (2019). Efficient metadata management and intelligent scheduling in exascale systems. Future Generation Computer Systems, 82:100–108.
Publicado
11/11/2024
Como Citar
SANTANA, Filipe A.; CORDEIRO, André F. R.; OLIVEIRAJR, Edson.
Investigating Computational Solutions for Metadata Processing in Software Engineering Experiments. In: ESCOLA REGIONAL DE ENGENHARIA DE SOFTWARE (ERES), 8. , 2024, Santiago/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 1-10.
DOI: https://doi.org/10.5753/eres.2024.4283.
