Geoffrey Hecht

My research interests include software engineering, software optimization, machine learning, virtual reality and the Android ecosystem. Always open to collaboration if we have research interests in common !

Since July 2018, I am a Postdoctoral fellow at University of Chile in the Intelligent Software Construction Laboratory (ISCLab) working with Alexandre Bergel on the optimization of Android Applications, in particular regarding ProGuard/R8 and Kotlin.

Before this, I was Postdoctoral fellow in Université du Québec à Montréal (UQAM) working on service-oriented software reengineering of legacy applications and static analysis of multilanguage software systems with Hafedh Mili.

I did my phd Thesis as Joint-thesis between UQAM (Canada) and Université Lille 1 (France), Under the supervision of Naouel Moha and Romain Rouvoy, in Latece laboratory and CRIStAL (Spirals team) on the detection and analysis of impact of code smells in mobile applications

Selected Publications

Tracking the software quality of android applications along their evolution (t)

Hecht, Geoffrey, Benomar, Omar, Rouvoy, Romain, Moha, Naouel, and Duchien, Laurence

In 30th IEEE/ACM International Conference on Automated Software Engineering (ASE) 2015

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Mobile apps are becoming complex software systems that must be developed quickly and evolve continuously to fit new user requirements and execution contexts. However, addressing these requirements may result in poor design choices, also known as antipatterns, which may incidentally degrade software quality and performance. Thus, the automatic detection and tracking of antipatterns in this apps are important activities in order to ease both maintenance and evolution. Moreover, they guide developers to refactor their applications and thus, to improve their quality. While antipatterns are well-known in object-oriented applications, their study in mobile applications is still in its infancy. In this paper, we analyze the evolution of mobile apps quality on 3, 568 versions of 106 popular Android applications downloaded from the Google Play Store. For this purpose, we use a tooled approach, called PAPRIKA, to identify 3 object-oriented and 4 Android-specific antipatterns from binaries of mobile apps, and to analyze their quality along evolutions.
Codifying Hidden Dependencies in Legacy J2EE Applications

Hecht, Geoffrey, Mili, Hafedh, El-Boussaidi, Ghizlane, Boubaker, Anis, Abdellatif, Manel, Guéhéneuc, Yann-Gaël, Shatnawi, Anas, Privat, Jean, and Moha, Naouel

In 2018 25th Asia-Pacific Software Engineering Conference (APSEC) 2018

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J2EE applications tend to be multi-tier and multi-language applications. They rely on the J2EE platform and containers that offer infrastructure and architectural services to ensure distributed, secure, safe, and scalable executions. These mechanisms hide many program dependencies, which helps development but hinders maintenance, evolution, and re-engineering of J2EE applications. In this paper, we study (i) the J2EE specifications to extract a declarative specification of the dependencies that are inherent in the services offered and that are not visible in the user code that uses them. Then, we introduce (ii) a codification of the dependencies into rules, and (iii) a tool that supports the specification of those dependencies and their detection in J2EE applications. We validate our approach and tool on a sample of 10 J2EE applications. We also compare our tool against JRipples, a state-of-the-art tool for change-impact analysis tasks. Results show that our tool adds, on average, 15% more call dependencies, which would have been missed otherwise. On change impact analysis tasks, our tool outperforms JRipples in all 10 applications, especially for the early iterations of change propagation exploration.
Vision: Alleviating Android Developer Burden on Obfuscation

Hecht, Geoffrey, Neverov, Cyprien, and Bergel, Alexandre

In Proceedings of the IEEE/ACM 7th International Conference on Mobile Software Engineering and Systems 2020

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Mobile applications (apps) have gained an increasing importance in the field of software engineering as they are becoming one of the most widely used type of software. In the Android ecosystem, obfuscation tools are available to optimize, reduce the size and protect the intellectual properties of apps. However, despite the clear advantages provided by obfuscation most apps do not use it, often because of the difficulties induced by the usage of obfuscation which requires writing rules to keep a usable app. In this paper, we identify the concrete challenges encountered by app developers who wish to use obfuscation in their apps. In addition, we propose an approach using crowdsourcing to automatically generate rules, when static analysis is not sufficient. With the knowledge gained from hundreds of projects, we hope to lighten the burden on developers when writing rules.