Megha Khanna

426 citations
25 papers · 312 indexed · h-index 10
Topics
Software Engineering Research (21 papers)Software Reliability and Analysis Research (18 papers)Software Engineering Techniques and Practices (8 papers)
Journals
SHILAP Revista de lepidopterologíaKnowledge-Based SystemsInformation and Software Technology
Partner nations
IndiaUnited StatesSpain

In The Last Decade

Megha Khanna

23 papers receiving 307 citations

Peers

Megha Khanna
Comparison fields: 5 of 33
  • Information Systems 278
  • Software 243
  • Artificial Intelligence 85
  • Computer Networks and Communications 79
  • Signal Processing 14
Replace Mariza A. S. Bigonha with:
Mariza A. S. Bigonha Brazil
Chu-Pan Wong United States
Nadia Alshahwan United Kingdom
Andy Kellens Belgium
Aryaz Eghbali Germany
Vijayaraghavan Murali United States
Guillaume Pothier Chile
Tijs van der Storm Netherlands
Alexandru Marginean United Kingdom
Ziying Dai China
Megha Khanna relative to Mariza A. S. Bigonha Brazil Mariza A. S. Bigonha's profile →
Citations per field
00.5×2.6×
Mariza A. S. Bigonha · 1×
Citations per year

Countries citing papers authored by Megha Khanna

Since Specialization
Citations

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

Fields of papers citing papers by Megha Khanna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Megha Khanna

This figure shows the co-authorship network connecting the top 25 collaborators of Megha Khanna. A scholar is included among the top collaborators of Megha Khanna 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 Megha Khanna. Megha Khanna 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
#WorkIndexed citations
1 2
2 0
3 0
4 3
5 4
6 2
7 14
8 14
9
An empirical study to evaluate the relationship of object-oriented metrics and change proneness.
1
10 13
11 7
12 6
13 52
14 36
15 33
16 13
17
The Ability of Search-Based Algorithms to Predict Change-Prone Classes
7
18 2
19 3
20 54

About Megha Khanna

Megha Khanna is a scholar working on Software, Information Systems and Computer Science Applications, having authored 25 papers that have together received 312 indexed citations. Recurring topics across this work include Software Engineering Research (21 papers), Software Reliability and Analysis Research (18 papers) and Software Engineering Techniques and Practices (8 papers). The work is most often cited by research in Software (243 citations), Information Systems (278 citations) and Computer Networks and Communications (79 citations). Megha Khanna has collaborated with scholars based in India, United States and Spain. Frequent co-authors include Ruchika Malhotra, Rajeev R. Raje, Mehak Aggarwal, Nikhil Kumar Rajput and Vrinda Gupta. Their work appears in journals such as SHILAP Revista de lepidopterología, Knowledge-Based Systems and Information and Software Technology.

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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