Simply the best – A systematic evaluation approach for third-party libraries based on mobile app quality attributes

Abstract Mobile device applications (apps) are complex because they rely on integrating multiple third-party libraries (TPLs). Yet, TPLs ease app development by offering implementations of specific functionality. For example, app developers often use advertising libraries to generate revenue, integrate social networking libraries to simplify login, or include crash reporting libraries to monitor/report crashes in their apps. However, there are multiple TPLs with similar functionalities from which to choose, and developers often cannot foresee all the consequences of using these libraries in their apps. The sizes of apps grow with the addition and usage of TPLs, and so does the number of required permissions and resource consumption. Thus, TPLs may degrade the quality of apps and developers need help measuring and comparing them. We propose EQuAT, an approach for Evaluating Quality Attributes of TPLs that eases the comparison of TPLs. EQuAT takes as input minimal apps that integrate TPLs and playable scenarios to simulate user interaction while exercising a particular functionality of the included TPL. By collecting quality metrics and comparing them using plots, we provide app developers with a systematic approach to rank TPLs based on their preferences. We show how EQuAT helps developers make informed decisions about which libraries to integrate into their apps by validating them against nine TPLs across three categories.

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Publication Details

Journal
Empirical Software Engineering
Published
2026-05-08
DOI
https://doi.org/10.1007/s10664-026-10872-w
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Simply the best – A systematic evaluation approach for third-party libraries based on mobile app quality attributes

Rodrigo Morales, Yann‐Gaël Guéhéneuc, Foutse Khomh, Romain Rouvoy et al.
Empirical Software Engineering
Advanced Malware Detection Techniques
article

Simply the best – A systematic evaluation approach for third-party libraries based on mobile app quality attributes

Rodrigo Morales, Yann‐Gaël Guéhéneuc, Foutse Khomh, Romain Rouvoy, Rémy Raes, Rubén Saborido
article en

Abstract

Abstract Mobile device applications (apps) are complex because they rely on integrating multiple third-party libraries (TPLs). Yet, TPLs ease app development by offering implementations of specific functionality. For example, app developers often use advertising libraries to generate revenue, integrate social networking libraries to simplify login, or include crash reporting libraries to monitor/report crashes in their apps. However, there are multiple TPLs with similar functionalities from which to choose, and developers often cannot foresee all the consequences of using these libraries in their apps. The sizes of apps grow with the addition and usage of TPLs, and so does the number of required permissions and resource consumption. Thus, TPLs may degrade the quality of apps and developers need help measuring and comparing them. We propose EQuAT, an approach for Evaluating Quality Attributes of TPLs that eases the comparison of TPLs. EQuAT takes as input minimal apps that integrate TPLs and playable scenarios to simulate user interaction while exercising a particular functionality of the included TPL. By collecting quality metrics and comparing them using plots, we provide app developers with a systematic approach to rank TPLs based on their preferences. We show how EQuAT helps developers make informed decisions about which libraries to integrate into their apps by validating them against nine TPLs across three categories.

Empirical Software EngineeringVol. 31(5)
Centre National de la Recherche Scientifique (FR), Université de Lille (FR), Mila - Quebec Artificial Intelligence Institute (CA), Concordia University (CA), Universidad de Málaga (ES)
Universidad de Málaga, Natural Sciences and Engineering Research Council of Canada, European Regional Development Fund, Agencia Estatal de Investigación
Decent work and economic growth
Openalex Percentile: Top 5%
Advanced Malware Detection Techniques
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