SEMar 8, 2019

Mobile-App Analysis and Instrumentation Techniques Reimagined with DECREE

arXiv:1903.03277v1
Originality Synthesis-oriented
AI Analysis

This addresses reproducibility and usability issues for researchers and developers in mobile-app analysis, though it is incremental as it builds on existing techniques.

The paper tackles the problem of mobile-app analysis and instrumentation techniques being difficult to extract, reuse, reproduce, and compare by introducing DECREE, an infrastructure that makes these techniques reproducible, practical, and easy to adopt, enabling unbiased evaluation and replication studies.

A large number of mobile-app analysis and instrumentation techniques have emerged in the past decade. However, those techniques' components are difficult to extract and reuse outside their original tools, their evaluation results are hard to reproduce, and the tools themselves are hard to compare. This paper introduces DECREE, an infrastructure intended to guide such techniques to be reproducible, practical, reusable, and easy to adopt in practice. DECREE allows researchers and developers to easily discover existing solutions to their needs, enables unbiased and reproducible evaluation, and supports easy construction and execution of replication studies. The paper describes DECREE's three modules and its potential to fundamentally alter how research is conducted in this area.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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