John Homer

737 total citations
12 papers, 431 citations indexed

About

John Homer is a scholar working on Information Systems, Computer Science Applications and Computer Networks and Communications. According to data from OpenAlex, John Homer has authored 12 papers receiving a total of 431 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Information Systems, 6 papers in Computer Science Applications and 3 papers in Computer Networks and Communications. Recurrent topics in John Homer's work include Teaching and Learning Programming (6 papers), Online Learning and Analytics (4 papers) and Software Engineering Research (4 papers). John Homer is often cited by papers focused on Teaching and Learning Programming (6 papers), Online Learning and Analytics (4 papers) and Software Engineering Research (4 papers). John Homer collaborates with scholars based in United States, Ireland and New Zealand. John Homer's co-authors include Raymond Pettit, Xinming Ou, James Prather, Anicia Peters, Maxine S. Cohen, Anoop Singhal, Susan Mengel, Su Zhang, S. Raj Rajagopalan and David Schmidt and has published in prestigious journals such as IEEE Journal on Selected Areas in Communications, Journal of Computer Security and Decision.

In The Last Decade

John Homer

11 papers receiving 412 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John Homer United States	10	239	237	130	122	82	12	431
Judith Bishop United States	11	200 0.8×	215 0.9×	127 1.0×	64 0.5×	76 0.9×	47	399
Marzieh Ahmadzadeh Iran	8	234 1.0×	186 0.8×	103 0.8×	104 0.9×	62 0.8×	23	442
Susan Mengel United States	12	143 0.6×	248 1.0×	73 0.6×	63 0.5×	32 0.4×	56	395
Sarah Heckman United States	14	205 0.9×	423 1.8×	292 2.2×	94 0.8×	90 1.1×	55	640
Monika Akbar United States	8	174 0.7×	97 0.4×	40 0.3×	45 0.4×	94 1.1×	33	345
Amey Karkare India	9	249 1.0×	254 1.1×	225 1.7×	59 0.5×	52 0.6×	30	489
Paul Gestwicki United States	12	191 0.8×	184 0.8×	90 0.7×	35 0.3×	114 1.4×	30	374
Oscar Karnalim Indonesia	14	201 0.8×	339 1.4×	115 0.9×	26 0.2×	44 0.5×	94	620
T. Dean Hendrix United States	11	205 0.9×	244 1.0×	126 1.0×	39 0.3×	53 0.6×	37	392
Dennis Brylow United States	11	154 0.6×	59 0.2×	56 0.4×	91 0.7×	44 0.5×	47	336

Countries citing papers authored by John Homer

Since Specialization

Citations

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

Fields of papers citing papers by John Homer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Homer

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Stomakhin, Alexey, et al.. (2023). Avatar: The Way of Hair, Cloth, and Coupled Simulation. 1–2.

2.

Denny, Paul, et al.. (2021). On Designing Programming Error Messages for Novices: Readability and its Constituent Factors. Research Repository UCD (University College Dublin). 1–15. 40 indexed citations

3.

Jessup, Ryan K., et al.. (2019). Hurry up and decide: Empirical tests of the choice overload effect using cognitive process models.. Decision. 7(2). 137–152. 6 indexed citations

4.

Prather, James, et al.. (2018). Metacognitive Difficulties Faced by Novice Programmers in Automated Assessment Tools. 41–50. 84 indexed citations

5.

Pettit, Raymond, et al.. (2017). Do Enhanced Compiler Error Messages Help Students?. Digital Commons - ACU (Abilene Christian University). 465–470. 51 indexed citations

6.

Prather, James, et al.. (2017). On Novices' Interaction with Compiler Error Messages. Digital Commons - ACU (Abilene Christian University). 74–82. 53 indexed citations

7.

Homer, John, et al.. (2016). Augmenting attack graphs to represent data link and network layer vulnerabilities. 1010–1015. 10 indexed citations

8.

Pettit, Raymond, et al.. (2015). Are Automated Assessment Tools Helpful in Programming Courses?. 26.230.1–26.230.20. 28 indexed citations

9.

Pettit, Raymond, et al.. (2015). An Empirical Study of Iterative Improvement in Programming Assignments. Digital Commons - ACU (Abilene Christian University). 410–415. 39 indexed citations

10.

Homer, John, Su Zhang, Xinming Ou, et al.. (2013). Aggregating vulnerability metrics in enterprise networks using attack graphs. Journal of Computer Security. 21(4). 561–597. 81 indexed citations

11.

Zhang, Su, Xinming Ou, Anoop Singhal, & John Homer. (2011). An Empirical Study of a Vulnerability Metric Aggregation Method. 562–568. 9 indexed citations

12.

Homer, John & Xinming Ou. (2009). SAT-solving approaches to context-aware enterprise network security management. IEEE Journal on Selected Areas in Communications. 27(3). 315–322. 30 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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