Ivan Machado

1.6k total citations
97 papers, 996 citations indexed

About

Ivan Machado is a scholar working on Information Systems, Artificial Intelligence and Software. According to data from OpenAlex, Ivan Machado has authored 97 papers receiving a total of 996 indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Information Systems, 47 papers in Artificial Intelligence and 45 papers in Software. Recurrent topics in Ivan Machado's work include Software Engineering Research (60 papers), Advanced Software Engineering Methodologies (43 papers) and Software Testing and Debugging Techniques (35 papers). Ivan Machado is often cited by papers focused on Software Engineering Research (60 papers), Advanced Software Engineering Methodologies (43 papers) and Software Testing and Debugging Techniques (35 papers). Ivan Machado collaborates with scholars based in Brazil, United States and Italy. Ivan Machado's co-authors include Eduardo Santana de Almeida, Paulo Anselmo da Mota Silveira Neto, John D. McGregor, Sílvio Romero de Lemos Meira, Yguaratã Cerqueira Cavalcanti, Eduardo Santana de Almeida, Per Runeson, Emelie Engström, Claes Wohlin and Heitor Costa and has published in prestigious journals such as IEEE Software, Journal of Systems and Software and Information and Software Technology.

In The Last Decade

Ivan Machado

85 papers receiving 958 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ivan Machado Brazil	14	710	470	444	204	87	97	996
Paola Spoletini Italy	17	484 0.7×	474 1.0×	201 0.5×	236 1.2×	52 0.6×	63	844
Robert C. Seacord United States	14	589 0.8×	421 0.9×	222 0.5×	226 1.1×	55 0.6×	35	791
Mehdi Mirakhorli United States	17	796 1.1×	406 0.9×	249 0.6×	278 1.4×	44 0.5×	78	957
Bente Anda Norway	16	984 1.4×	290 0.6×	496 1.1×	211 1.0×	175 2.0×	27	1.1k
Jens Grabowski Germany	16	734 1.0×	239 0.5×	609 1.4×	335 1.6×	52 0.6×	87	1.1k
Paulo Anselmo da Mota Silveira Neto Brazil	12	557 0.8×	344 0.7×	248 0.6×	177 0.9×	77 0.9×	37	764
Andrea Janes Italy	16	560 0.8×	185 0.4×	223 0.5×	236 1.2×	67 0.8×	72	733
Wenyun Zhao China	20	1.0k 1.4×	577 1.2×	329 0.7×	506 2.5×	119 1.4×	114	1.2k
Sílvio R. L. Meira Brazil	15	379 0.5×	242 0.5×	204 0.5×	119 0.6×	71 0.8×	67	651
Carlo A. Furia Switzerland	18	743 1.0×	261 0.6×	668 1.5×	223 1.1×	79 0.9×	61	1.1k

Countries citing papers authored by Ivan Machado

Since Specialization

Citations

This map shows the geographic impact of Ivan Machado's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ivan Machado with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Machado more than expected).

Fields of papers citing papers by Ivan Machado

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ivan Machado. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ivan Machado. The network helps show where Ivan Machado may publish in the future.

Co-authorship network of co-authors of Ivan Machado

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Machado. A scholar is included among the top collaborators of Ivan Machado based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ivan Machado. Ivan Machado is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Machado, Ivan, et al.. (2024). An empirical investigation into the capabilities of anomaly detection approaches for test smell detection. Journal of Systems and Software. 222. 112320–112320. 1 indexed citations

Machado, Ivan, et al.. (2024). Issue Labeling Dynamics in Open-Source Projects: A Comprehensive Analysis. 51–60. 1 indexed citations

Corrêa, Diego Rafael Nespeque, Frederico Araújo Dur�ão, Maycon Peixoto, et al.. (2024). A Case Study of Smart Home Development. IEEE Software. 42(6). 64–73.

Lucas, K., et al.. (2024). Evaluating Large Language Models in Detecting Test Smells. 672–678. 5 indexed citations

Dur�ão, Frederico Araújo, Cássio Prazeres, Maycon Peixoto, et al.. (2024). Unleashing the Future of Smart Homes: A Revelation of Cutting-Edge Distributed Architecture. 41–50.

Costa, Heitor, et al.. (2023). An empirical evaluation of RAIDE: A semi-automated approach for test smells detection and refactoring. Science of Computer Programming. 231. 103013–103013. 2 indexed citations

Costa, Heitor, et al.. (2023). Hearing the voice of experts: Unveiling Stack Exchange communities’ knowledge of test smells. 80–91. 2 indexed citations

Bezerra, Carla, et al.. (2022). Automating Feature Model maintainability evaluation using machine learning techniques. Journal of Systems and Software. 195. 111539–111539. 3 indexed citations

Machado, Ivan, et al.. (2021). GrumPy: an automated approach to simplify issue data analysis for newcomers. 33–38. 3 indexed citations

10.

Maciel, Paulo, et al.. (2021). Understanding practitioners’ strategies to handle test smells: a multi-method study. 49–53. 5 indexed citations

11.

Bezerra, Carla, et al.. (2020). Classifying Feature Models Maintainability based on Machine Learning Algorithms. 1–10. 2 indexed citations

12.

Souza, Renata M.C.R. de, et al.. (2019). Investigating Agile Practices in Software Startups. 317–321. 16 indexed citations

13.

Machado, Ivan, et al.. (2013). Analyzing the Effectiveness of a System Testing Tool for Software Product Line Engineering (S).. Software Engineering and Knowledge Engineering. 584–588. 1 indexed citations

14.

Neto, Paulo Anselmo da Mota Silveira, et al.. (2012). Risk management in software product lines: an industrial case study. 180–189. 8 indexed citations

15.

Machado, Ivan, et al.. (2012). Synthesizing Evidence on Risk Management: A Narrative Synthesis of two Mapping Studies.. Software Engineering and Knowledge Engineering. 641–646.

16.

Machado, Ivan, John D. McGregor, & Eduardo Santana de Almeida. (2012). Strategies for testing products in software product lines. ACM SIGSOFT Software Engineering Notes. 37(6). 1–8. 29 indexed citations

17.

Machado, Ivan, Paulo Anselmo da Mota Silveira Neto, Eduardo Santana de Almeida, & Sílvio Romero de Lemos Meira. (2011). RiPLE-TE: A Process for Testing Software Product Lines.. Software Engineering and Knowledge Engineering. 711–716. 11 indexed citations

18.

Machado, Ivan, et al.. (2011). Software Product Lines System Test Case Tool: A Proposal.. Software Engineering and Knowledge Engineering. 699–704. 4 indexed citations

19.

Cavalcanti, Yguaratã Cerqueira, et al.. (2011). Towards metamodel support for variability and traceability in software product lines. 49–57. 17 indexed citations

20.

Neto, Paulo Anselmo da Mota Silveira, Ivan Machado, John D. McGregor, Eduardo Santana de Almeida, & Sílvio Romero de Lemos Meira. (2010). A systematic mapping study of software product lines testing. Information and Software Technology. 53(5). 407–423. 172 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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