Daniel Méndez

3.2k total citations · 1 hit paper
105 papers, 1.3k citations indexed

About

Daniel Méndez is a scholar working on Information Systems, Artificial Intelligence and Software. According to data from OpenAlex, Daniel Méndez has authored 105 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Information Systems, 30 papers in Artificial Intelligence and 20 papers in Software. Recurrent topics in Daniel Méndez's work include Software Engineering Techniques and Practices (78 papers), Software Engineering Research (71 papers) and Advanced Software Engineering Methodologies (27 papers). Daniel Méndez is often cited by papers focused on Software Engineering Techniques and Practices (78 papers), Software Engineering Research (71 papers) and Advanced Software Engineering Methodologies (27 papers). Daniel Méndez collaborates with scholars based in Germany, Sweden and Brazil. Daniel Méndez's co-authors include Marco Kuhrmann, Stefan Wagner, Henning Femmer, Maya Daneva, Nils Brede Moe, Darja Šmite, Jarle Hildrum, Andreas Vogelsang, Jonas Eckhardt and Marcos Kalinowski and has published in prestigious journals such as The Science of The Total Environment, IEEE Transactions on Software Engineering and Medical Physics.

In The Last Decade

Daniel Méndez

97 papers receiving 1.2k citations

Hit Papers

Work-from-home is here to stay: Call for flexibility in p... 2022 2026 2023 2024 2022 40 80 120
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Work-from-home is here to stay: Call for flexibility in post-pandemic work policies
    2022 129 citations Daniel Méndez et al. Journal of Systems and Software profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Méndez Germany 18 907 320 203 192 147 105 1.3k
Shuib Basri Malaysia 21 767 0.8× 350 1.1× 229 1.1× 179 0.9× 184 1.3× 97 1.3k
Óscar Dieste Spain 18 902 1.0× 370 1.2× 211 1.0× 154 0.8× 131 0.9× 80 1.2k
Rialette Pretorius United Kingdom 6 600 0.7× 234 0.7× 144 0.7× 187 1.0× 124 0.8× 8 1.1k
Emilio Insfrán Spain 18 973 1.1× 426 1.3× 342 1.7× 249 1.3× 136 0.9× 81 1.4k
Πάνος Λουρίδας Greece 19 761 0.8× 332 1.0× 298 1.5× 283 1.5× 86 0.6× 59 1.4k
Mojtaba Shahin Australia 16 787 0.9× 300 0.9× 152 0.7× 402 2.1× 138 0.9× 58 1.2k
Silvia Abrahão Spain 21 1.1k 1.2× 428 1.3× 440 2.2× 267 1.4× 136 0.9× 111 1.6k
Geir Kjetil Hanssen Norway 13 577 0.6× 208 0.7× 152 0.7× 156 0.8× 130 0.9× 45 840
María José Escalona Spain 23 1.1k 1.2× 303 0.9× 353 1.7× 218 1.1× 310 2.1× 134 1.7k
Barbara Paech Germany 20 946 1.0× 484 1.5× 307 1.5× 196 1.0× 179 1.2× 136 1.3k

Countries citing papers authored by Daniel Méndez

Since Specialization
Citations

This map shows the geographic impact of Daniel Méndez'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 Daniel Méndez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Méndez more than expected).

Fields of papers citing papers by Daniel Méndez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Méndez. 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 Daniel Méndez. The network helps show where Daniel Méndez may publish in the future.

Co-authorship network of co-authors of Daniel Méndez

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Méndez. A scholar is included among the top collaborators of Daniel Méndez 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 Daniel Méndez. Daniel Méndez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Méndez, Daniel, et al.. (2025). Exploring the use of LLMs for the selection phase in systematic literature studies. Information and Software Technology. 184. 107757–107757. 2 indexed citations
2.
Kalinowski, Marcos, Daniel Méndez, Görkem Giray, et al.. (2025). Naming the Pain in machine learning-enabled systems engineering. Information and Software Technology. 187. 107866–107866. 1 indexed citations
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4.
Günther, Matthias, Joel Greenyer, Carsten Wolff, et al.. (2024). Model‐based analysis and specification of functional requirements and tests for complex automotive systems. Systems Engineering. 27(4). 728–744. 2 indexed citations
5.
6.
Gorschek, Tony, et al.. (2024). Adversarial Machine Learning in Industry: A Systematic Literature Review. Computers & Security. 145. 103988–103988. 8 indexed citations
7.
Kalinowski, Marcos, et al.. (2024). Identifying concerns when specifying machine learning-enabled systems: A perspective-based approach. Journal of Systems and Software. 213. 112053–112053. 7 indexed citations
8.
Méndez, Daniel, et al.. (2024). The upper bound of information diffusion in code review. Empirical Software Engineering. 30(1).
9.
Gorschek, Tony, et al.. (2024). A natural language-based method to specify privacy requirements: an evaluation with practitioners. Requirements Engineering. 29(3). 279–301. 3 indexed citations
10.
Unterkalmsteiner, Michael, et al.. (2022). A Live Extensible Ontology of Quality Factors for Textual Requirements. arXiv (Cornell University). 274–280. 9 indexed citations
11.
Franch, Xavier, Martin Glinz, Daniel Méndez, & Norbert Seyff. (2021). A Study About the Knowledge and Use of Requirements Engineering Standards in Industry. IEEE Transactions on Software Engineering. 48(9). 3310–3325. 6 indexed citations
12.
Franch, Xavier, Daniel Méndez, Andreas Vogelsang, et al.. (2020). How do Practitioners Perceive the Relevance of Requirements Engineering Research?. IEEE Transactions on Software Engineering. 48(6). 1947–1964. 11 indexed citations
13.
Lenarduzzi, Valentina, Davide Fucci, & Daniel Méndez. (2020). On the perceived harmfulness of requirement smells : An empirical study. KTH Publication Database DiVA (KTH Royal Institute of Technology). 2584. 2 indexed citations
14.
Ameller, David, Xavier Franch, Cristina Gómez, et al.. (2019). Dealing with Non-Functional Requirements in Model-Driven Development: A Survey. IEEE Transactions on Software Engineering. 47(4). 818–835. 29 indexed citations
15.
16.
Prechelt, Lutz, Daniel Graziotin, & Daniel Méndez. (2017). On the Status and Future of Peer Review in Software Engineering. arXiv (Cornell University). 2 indexed citations
17.
Eckhardt, Jonas, Andreas Vogelsang, & Daniel Méndez. (2016). Are "non-functional" requirements really non-functional?: an investigation of non-functional requirements in practice. arXiv (Cornell University). 832–842. 41 indexed citations
18.
Vetrò, Antonio, et al.. (2015). Fast feedback cycles in empirical software engineering research. International Conference on Software Engineering. 2. 583–586. 6 indexed citations
19.
Kuhrmann, Marco, Daniel Méndez, & Jürgen Münch. (2013). Teaching software process modeling. arXiv (Cornell University). 1138–1147. 11 indexed citations
20.
Méndez, Daniel, et al.. (2004). Fish schools: PDES Simulation and real time 3D animation. 3019. 505–512. 1 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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