Ruchika Malhotra

5.7k total citations · 1 hit paper
199 papers, 4.0k citations indexed

About

Ruchika Malhotra is a scholar working on Information Systems, Software and Computer Networks and Communications. According to data from OpenAlex, Ruchika Malhotra has authored 199 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 156 papers in Information Systems, 141 papers in Software and 50 papers in Computer Networks and Communications. Recurrent topics in Ruchika Malhotra's work include Software Engineering Research (147 papers), Software Reliability and Analysis Research (138 papers) and Software System Performance and Reliability (47 papers). Ruchika Malhotra is often cited by papers focused on Software Engineering Research (147 papers), Software Reliability and Analysis Research (138 papers) and Software System Performance and Reliability (47 papers). Ruchika Malhotra collaborates with scholars based in India, United States and Spain. Ruchika Malhotra's co-authors include Yogesh Singh, Arvinder Kaur, James F. Rusling, J. Silvio Gutkind, Vyomesh Patel, Megha Khanna, K.K. Aggarwal, Anuradha Chug, Ankita Jain and José P. Vaqué and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Analytical Chemistry.

In The Last Decade

Ruchika Malhotra

187 papers receiving 3.7k citations

Hit Papers

A systematic review of machine learning techniques for so... 2014 2026 2018 2022 2014 100 200 300 400
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. A systematic review of machine learning techniques for software fault prediction
    2014 432 citations Ruchika Malhotra profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ruchika Malhotra India 34 2.3k 2.0k 841 821 617 199 4.0k
Stefan Wagner Germany 28 1.4k 0.6× 736 0.4× 482 0.6× 193 0.2× 637 1.0× 241 3.3k
Ting Chen China 33 2.5k 1.1× 266 0.1× 922 1.1× 150 0.2× 1.1k 1.9× 167 4.8k
Xinyu Wang China 26 1.8k 0.8× 768 0.4× 641 0.8× 105 0.1× 754 1.2× 108 2.6k
Hao Zhong China 28 1.2k 0.5× 844 0.4× 490 0.6× 82 0.1× 412 0.7× 225 2.9k
W. K. Chan Hong Kong 38 1.8k 0.8× 2.1k 1.0× 1.6k 1.9× 86 0.1× 618 1.0× 242 5.1k
Tom Chen United States 30 654 0.3× 153 0.1× 1.5k 1.8× 150 0.2× 515 0.8× 209 3.3k
Kai Chen China 28 1.6k 0.7× 639 0.3× 1.1k 1.3× 206 0.3× 1.5k 2.4× 184 3.9k
Sooyong Park South Korea 26 2.2k 0.9× 241 0.1× 776 0.9× 96 0.1× 976 1.6× 189 3.5k
Ziming Zhao United States 30 795 0.3× 225 0.1× 1.2k 1.4× 35 0.0× 567 0.9× 142 2.9k
Gang Huang China 33 1.4k 0.6× 166 0.1× 1.3k 1.6× 249 0.3× 1.0k 1.6× 251 3.7k

Countries citing papers authored by Ruchika Malhotra

Since Specialization
Citations

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

Fields of papers citing papers by Ruchika Malhotra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruchika Malhotra

This figure shows the co-authorship network connecting the top 25 collaborators of Ruchika Malhotra. A scholar is included among the top collaborators of Ruchika Malhotra 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 Ruchika Malhotra. Ruchika Malhotra 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.
Malhotra, Ruchika, et al.. (2025). Software defect prediction based on multi-filter wrapper feature selection and deep neural network with attention mechanism. Neural Computing and Applications. 37(27). 22621–22648.
2.
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Malhotra, Ruchika, et al.. (2024). A novel software defect prediction model using two-phase grey wolf optimisation for feature selection. Cluster Computing. 27(9). 12185–12207. 3 indexed citations
4.
Malhotra, Ruchika, et al.. (2024). Text mining based an automatic model for software vulnerability severity prediction. International Journal of Systems Assurance Engineering and Management. 15(8). 3706–3724. 2 indexed citations
5.
Malhotra, Ruchika, et al.. (2024). Handwritten Amharic Word Recognition With Additive Attention Mechanism. IEEE Access. 12. 114645–114657. 3 indexed citations
6.
Pandey, A.K., et al.. (2024). Deep learning in neglected vector-borne diseases: a systematic review. International Journal of Systems Assurance Engineering and Management. 2 indexed citations
7.
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Malhotra, Ruchika, et al.. (2023). Software defect prediction using hybrid techniques: a systematic literature review. Soft Computing. 27(12). 8255–8288. 16 indexed citations
9.
Malhotra, Ruchika, et al.. (2022). Comparison of Hidden Markov Model with other Machine Learning Techniques in Software Defect Prediction. 2022 IEEE 7th International conference for Convergence in Technology (I2CT). 1–5. 2 indexed citations
10.
11.
Malhotra, Ruchika, et al.. (2022). License Plate Recognition System using Yolov5 and CNN. 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS). 372–377. 21 indexed citations
12.
Malhotra, Ruchika, et al.. (2021). Mining Non-Functional Requirements using Machine Learning Techniques. SHILAP Revista de lepidopterología. 15(1). 6 indexed citations
13.
Malhotra, Ruchika & Kusum Lata. (2020). An empirical study to investigate the impact of data resampling techniques on the performance of class maintainability prediction models. Neurocomputing. 459. 432–453. 6 indexed citations
14.
Malhotra, Ruchika, et al.. (2019). Estimating the threshold of software metrics for web applications. International Journal of Systems Assurance Engineering and Management. 10(1). 110–125. 1 indexed citations
15.
Malhotra, Ruchika & Megha Khanna. (2018). An empirical study to evaluate the relationship of object-oriented metrics and change proneness.. The International Arab Journal of Information Technology. 15. 1016–1023. 1 indexed citations
16.
Malhotra, Ruchika, et al.. (2018). Bug localization in software using NSGA-II. 428–433. 3 indexed citations
17.
Malhotra, Ruchika & Anuradha Chug. (2016). Comparative analysis of agile methods and iterative enhancement model in assessment of software maintenance. International Conference on Computing for Sustainable Global Development. 1271–1276. 7 indexed citations
18.
Malhotra, Ruchika. (2013). Prediction of High-, Medium-, and Low-Severity Faults Using Software Metrics. 15. 2 indexed citations
19.
Malhotra, Ruchika, et al.. (2012). Assessment of Code Smells for Predicting Class Change Proneness. 15.
20.
Singh, Yogesh, Arvinder Kaur, & Ruchika Malhotra. (2007). Application of Logistic Regression and Artificial Neural Network for Predicting Software Quality Models.. Software Engineering Research and Practice. 664–670. 3 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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