Justyna Petke

2.5k total citations · 1 hit paper
70 papers, 1.3k citations indexed

About

Justyna Petke is a scholar working on Software, Information Systems and Artificial Intelligence. According to data from OpenAlex, Justyna Petke has authored 70 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Software, 47 papers in Information Systems and 20 papers in Artificial Intelligence. Recurrent topics in Justyna Petke's work include Software Testing and Debugging Techniques (46 papers), Software Engineering Research (42 papers) and Software Reliability and Analysis Research (23 papers). Justyna Petke is often cited by papers focused on Software Testing and Debugging Techniques (46 papers), Software Engineering Research (42 papers) and Software Reliability and Analysis Research (23 papers). Justyna Petke collaborates with scholars based in United Kingdom, United States and Australia. Justyna Petke's co-authors include Mark Harman, William B. Langdon, Myra B. Cohen, Yue Jia, Carol Hanna, Martin Briesch, Shin Yoo, Dominik Sobania, Earl T. Barr and David R. White and has published in prestigious journals such as ACM Computing Surveys, IEEE Transactions on Software Engineering and IEEE Transactions on Evolutionary Computation.

In The Last Decade

Justyna Petke

60 papers receiving 1.2k citations

Hit Papers

align trajectories

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.

An Analysis of the Automatic Bug Fixing Performance of ChatGPT

2023 178 citations Dominik Sobania, Martin Briesch et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Justyna Petke United Kingdom	17	754	673	471	179	164	70	1.3k
Zhangyin Feng China	8	609 0.8×	1.3k 1.9×	1.1k 2.3×	323 1.8×	417 2.5×	10	2.1k
Xiaoyuan Xie China	19	1.0k 1.4×	814 1.2×	353 0.7×	377 2.1×	120 0.7×	69	1.5k
Linjun Shou China	14	521 0.7×	1.1k 1.6×	1.2k 2.6×	269 1.5×	351 2.1×	39	2.0k
Vincent J. Hellendoorn United States	15	535 0.7×	812 1.2×	436 0.9×	235 1.3×	194 1.2×	26	1.2k
Martin Monperrus Sweden	19	1.4k 1.8×	1.4k 2.1×	357 0.8×	412 2.3×	336 2.0×	73	1.9k
Hridesh Rajan United States	21	512 0.7×	1.3k 2.0×	998 2.1×	628 3.5×	197 1.2×	140	1.9k
Yihao Li China	11	1.0k 1.4×	890 1.3×	190 0.4×	381 2.1×	84 0.5×	41	1.4k
Sarah Nadi Canada	19	441 0.6×	1.0k 1.5×	563 1.2×	410 2.3×	278 1.7×	66	1.3k
Fabiano Cutigi Ferrari Brazil	17	479 0.6×	686 1.0×	438 0.9×	205 1.1×	57 0.3×	67	1.0k
Michel Wermelinger United Kingdom	22	630 0.8×	1.2k 1.8×	853 1.8×	446 2.5×	145 0.9×	100	1.6k

Countries citing papers authored by Justyna Petke

Since Specialization

Citations

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

Fields of papers citing papers by Justyna Petke

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Justyna Petke

This figure shows the co-authorship network connecting the top 25 collaborators of Justyna Petke. A scholar is included among the top collaborators of Justyna Petke 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 Justyna Petke. Justyna Petke 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:

20 of 20 papers shown

1.

Sarro, Federica, et al.. (2025). Behind the Hot Fix: Demystifying Hot Fixing Industrial Practices at Zühlke and Beyond. 411–421. 1 indexed citations

2.

Williams, D. A., James P. Callan, Serkan Kırbaş, et al.. (2024). User-Centric Deployment of Automated Program Repair at Bloomberg. 81–91. 2 indexed citations

3.

Petke, Justyna, Matías Martínez, Maria Kechagia, Aldeida Aleti, & Federica Sarro. (2024). The Patch Overfitting Problem in Automated Program Repair: Practical Magnitude and a Baseline for Realistic Benchmarking. Monash University Research Portal (Monash University). 452–456. 1 indexed citations

4.

Martínez, Matías, et al.. (2024). Test-based patch clustering for automatically-generated patches assessment. Empirical Software Engineering. 29(5). 116–116. 3 indexed citations

5.

Clark, David, et al.. (2024). Mining for Mutation Operators for Reduction of Information Flow Control Violations. 2324–2328.

6.

Sobania, Dominik, Justyna Petke, Martin Briesch, & Franz Rothlauf. (2024). A Comparison of Large Language Models and Genetic Programming for Program Synthesis. IEEE Transactions on Evolutionary Computation. 29(4). 1434–1448.

7.

Callan, James P. & Justyna Petke. (2024). Multi-objective improvement of Android applications. Automated Software Engineering. 32(1). 2–2.

8.

Callan, James P., William B. Langdon, & Justyna Petke. (2024). On Reducing Network Usage with Genetic Improvement. 23–30.

9.

Petke, Justyna, et al.. (2023). Program transformation landscapes for automated program modification using Gin. Empirical Software Engineering. 28(4). 4 indexed citations

10.

Langdon, William B., et al.. (2023). Genetically Improved Software with fewer Data Cache Misses. SPIRE - Sciences Po Institutional REpository. 799–802. 1 indexed citations

11.

Sobania, Dominik, Martin Briesch, Carol Hanna, & Justyna Petke. (2023). An Analysis of the Automatic Bug Fixing Performance of ChatGPT. 23–30. 178 indexed citations breakdown →

12.

Clark, David, et al.. (2022). Keeping Secrets: Multi-objective Genetic Improvement for Detecting and Reducing Information Leakage. 1–12. 4 indexed citations

13.

Callan, James P., et al.. (2022). How do Android developers improve non-functional properties of software?. Empirical Software Engineering. 27(5). 113–113. 6 indexed citations

14.

Petke, Justyna, et al.. (2021). Table of Contents. 5–6. 1 indexed citations

15.

Brownlee, Alexander E. I., et al.. (2019). Gin. Proceedings of the Genetic and Evolutionary Computation Conference. 985–993. 26 indexed citations

16.

Wu, Huayao, Changhai Nie, Justyna Petke, Yue Jia, & Mark Harman. (2019). Comparative Analysis of Constraint Handling Techniques for Constrained Combinatorial Testing. IEEE Transactions on Software Engineering. 47(11). 2549–2562. 13 indexed citations

17.

Jiang, He, Ke Tang, Justyna Petke, & Mark Harman. (2017). Search Based Software Engineering [Guest Editorial]. IEEE Computational Intelligence Magazine. 12(2). 23–71. 4 indexed citations

18.

Petke, Justyna & Tim Menzies. (2017). Search Based Software Engineering. Lecture notes in computer science. 16 indexed citations

19.

Langdon, William B., Brian Lam, Justyna Petke, & Mark Harman. (2015). Improving CUDA DNA Analysis Software with Genetic Programming. 1063–1070. 36 indexed citations

20.

Jeavons, Peter & Justyna Petke. (2009). Tractable Benchmarks For Constraint Programming. 2 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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