The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
How can i improve my app? Classifying user reviews for software maintenance and evolution
Open accessAbstract
App Stores, such as Google Play or the Apple Store, allow users to provide feedback on apps by posting review comments and giving star ratings. These platforms constitute a useful electronic mean in which application developers and users can productively exchange information about apps. Previous research showed that users feedback contains usage scenarios, bug reports and feature requests, that can help app developers to accomplish software maintenance and evolution tasks. However, in the case of the most popular apps, the large amount of received feedback, its unstructured nature and varying quality can make the identification of useful user feedback a very challenging task. In this paper we present a taxonomy to classify app reviews into categories relevant to software maintenance and evolution, as well as an approach that merges three techniques: (1) Natural Language Processing, (2) Text Analysis and (3) Sentiment Analysis to automatically classify app reviews into the proposed categories. We show that the combined use of these techniques allows to achieve better results (a precision of 75% and a recall of 74%) than results obtained using each technique individually (precision of 70% and a recall of 67%).
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Martin, W., Sarro, F., Jia, Y., Zhang, Y., & Harman, M. (2017) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2016.2630689 · Cited by 459
Ensemble Methods for App Review Classification: An Approach for Software Evolution (N)
Guzman, E., El-Haliby, M., & Bruegge, B. (2015) · 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE) · doi:10.1109/ase.2015.88 · Cited by 143
Self-citationRazzaq, A., Buckley, J., Lai, Q., Yu, T., & Botterweck, G. (2025) · ACM Computing Surveys · doi:10.1145/3687299 · Cited by 36
An Empirical Study on Using Large Language Models to Analyze Software Supply Chain Security Failures
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Metadata
- Authors
- Panichella, S., Di Sorbo, A., Guzman, E., Visaggio, C. A., Canfora, G., & Gall, H. C.
- Venue
- 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME)
- Publisher
- IEEE
- Published
- 2015-09
- Pages
- 281-290
- OpenAlex
- W2126574721
- Cited by
- 455
- References
- 43
- FWCI
- 30.99
- Type
- conference paper
- Language
- en
- Open access
- green
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- Panichella, S., Di Sorbo, A., Guzman, E., Visaggio, C. A., Canfora, G., & Gall, H. C. (2015). How can i improve my app? Classifying user reviews for software maintenance and evolution. 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME). https://doi.org/10.1109/icsm.2015.7332474
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