Niels Brouwers

Caiipa: automated large-scale mobile app testing through contextual fuzzing

Scalable and comprehensive testing of mobile apps is extremely challenging. Every test input needs to be run with a variety of contexts, such as: device heterogeneity, wireless network speeds, locations, and unpredictable sensor inputs. The range of values for each context, e.g. location, can be very large. In this paper we present Caiipa, a cloud service for testing apps over an expanded mobile context space in a scalable way. It incorporates key techniques to make app testing more tractable, including a context test space prioritizer to quickly discover failure scenarios for each app. We have implemented Caiipa on a cluster of VMs and real devices that can each emulate various combinations of contexts for tablet and phone apps. We evaluate Caiipa by testing 265 commercially available mobile apps based on a comprehensive library of real-world conditions. Our results show that Caiipa leads to improvements of 11.1x and 8.4x in the number of crashes and performance bugs discovered compared to conventional UI-based automation (i.e., monkey-testing).

Pogo, a middleware for mobile phone sensing

The smartphone revolution has brought ubiquitous, powerful, and connected sensing hardware to the masses. This holds great promise for a wide range of research fields. However, deployment of experiments onto a large set of mobile devices places technological, organizational, and sometimes financial burdens on researchers, making real-world experimental research cumbersome and difficult. We argue that a research infrastructure in the form of a large-scale mobile phone testbed is required to unlock the potential of this new technology. We aim to facilitate experimentation with mobile phone sensing by providing a pragmatic middleware framework that is easy to use and features fine-grained user-level control to guard the privacy of the volunteer smart-phone users. In this paper we describe the challenges and requirements for such a middleware, outline an architecture featuring a flexible, scriptable publish/subscribe framework, and report on our experience with an implementation running on top of the Android platform.

Incremental Wi-Fi scanning for energy-efficient localization

Wi-Fi based localization has proven to be a compelling alternative to GPS for mobile devices. But Wi-Fi scanning consumes a large amount of energy on smartphones because they perform full scans, i.e. all the channels in their band(s) are visited. This inefficient behavior greatly reduces battery life, raising the threshold for user acceptance. We propose a novel, incremental approach that reduces the energy consumption of Wi-Fi localization by scanning just a few selected channels. We evaluate our incremental scanning approach on eight Android devices using traces from five test subjects. Our results show that, compared to full scans, incremental scanning can reduce the energy consumption between 20.64% and 57.79%. The modern smartphones included in our study all show an energy reduction of at least 40%.

A Java compatible virtual machine for wireless sensor nodes

The Java programming language has potentially significant advantages for wireless sensor nodes but there is currently no feature-rich, open source virtual machine available. In this paper we present Darjeeling, a system comprising offline tools and a memory efficient run-time. The offline post-compiler tool analyzes, links and consolidates Java class files into loadable modules. The runtime implements a modified Java VM that supports multithreading and is designed specifically to operate in constrained execution environments such as wireless sensor network nodes and supports inheritance, threads, garbage collection, and loadable modules. We have demonstrated Java running on AVR128 and MSP430 microcontrollers at speeds of up to 70,000 JVM instructions per second.

Dwelling in the canyons: Dwelling detection in Urban Environments Using GPS, Wi-Fi, and Geolocation

Abstract A fundamental part of studying human mobility is to detect dwelling. When we dwell we are not necessarily stationary, but move around in a confined area. Most of our significant places are indoors, which hampers the detection using GPS. In this work, we discuss three different sensor sources when used for dwelling detection in urban environments: GPS, Wi-Fi and geolocation. Our study is based on data collected on mobile phones in cities of various sizes in four European countries. Based on this data, we compare several methods (i) for classifying whether a user was dwelling and (ii) for determining dwelling locations.

Prototypes for automated architectural 3D-layout

Prototypes for automated spatial layout in architecture focus on approaches, which define occupiable space as an orthogonal 2D-grid and use algorithms to allocate each rectangle of the grid to a particular function. However, these approaches are limiting the design to 2D spatial layouts. Based on SAT solving techniques, the prototype presented in this paper proposes a methodology for automated 3D-space planning for voxelized curvilinear geometries.

Characterization of Human Mobility in Networked Virtual Environments

The design and tuning of networked virtual environments (NVEs), such as World of Warcraft (WoW), require understanding the in-NVE mobility characteristics of their citizens. Although many mobility-aware NVE systems already exist, their validation and further development have been hampered by the lack of public datasets and of comparison studies based on multiple datasets. To address these two issues, in this work we collect from WoW mobility traces for over 30,000 virtual citizens, and compare these traces with traces collected from Second Life (SL) where the environment is designed and changed significantly by the citizens themselves. Furthermore, motivated by the existence of numerous studies and models of networked real-world environments (NRE), we systematically compare the characteristics of two NVE and two NRE mobility traces. Our comparative study reveals that long-tail distributions characterize well various mobility characteristics, that the invisible boundary of human movement also appears for NVEs, and that area-visitation shows personal preferences. We also find several differences between NVE and NRE mobility characteristics.