Martin von Löwis

Context-oriented programming: beyond layers

While many software systems today have to be aware of the context in which they are executing, there is still little support for structuring a program with respect to context. A first step towards better context-orientation was the introduction of method layers. This paper proposes two additional language concepts, namely the implicit activation of method layers, and the introduction of dynamic variables.

NQueens on CUDA: Optimization Issues

Todays commercial off-the-shelf computer systems are multicore computing systems as a combination of CPU, graphic processor (GPU) and custom devices. In comparison with CPU cores, graphic cards are capable to execute hundreds up to thousands compute units in parallel. To benefit from these GPU computing resources, applications have to be parallelized and adapted to the target architecture. In this paper we show our experience in applying the NQueens puzzle solution on GPUs using Nvidias CUDA (Compute Unified Device Architecture) technology. Using the example of memory usage and memory access, we demonstrate that optimizations of CUDA programs may have contrary results on different CUDA architectures. Evaluation results will point out, that it is not sufficient to use new programming languages or compilers to achieve best results with emerging graphic card computing.

A hybrid artificial intelligence system for assistance in remote monitoring of heart patients

Advancements in the development of medical apparatuses and in the ubiquitous availability of data networks make it possible to equip more patients with telemonitoring devices. As a consequence, interpreting the collected data becomes an increasing challenge. Medical observations traditionally have been interpreted in two competing ways: using established theories in a rule-based manner, and statistically (possibly leading to new theories). In this paper, we study a hybrid approach that allows both evaluation of a fixed set of rules as well as machine learning to coexist. We reason that this hybrid approach helps to increase the level of trust that doctors have in our system, by reducing the risk of false negatives.

NTrace: Function Boundary Tracing for Windows on IA-32

For a long time, dynamic tracing has been an enabling technique for reverse engineering tools. Tracing can not only be used to record the control flow of a particular component such as a piece of malware itself, it is also a way to analyze the interactions of a component and their impact on the rest of the system. Unlike Unix-based systems, for which several dynamic tracing tools are available, Windows has been lacking appropriate tools. From a reverse engineering perspective, however, Windows may be considered the most relevant OS, particularly with respect to malware analysis. In this paper, we present NTrace, a dynamic tracing tool for the Windows kernel, drivers, system libraries, and applications that supports function boundary tracing. NTrace incorporates 2 novel approaches: (1) a way to integrate with Windows Structured Exception Handling and (2) a technique to instrument binary code on IA-32 architectures that is both safe and more efficient than DTrace.

Live Streaming of Medical Data - The Fontane Architecture for Remote Patient Monitoring and Its Experimental Evaluation

Demographic transition and the decreasing number of medical experts in rural areas create a growing demand for tele-medicine systems that allow remote patient monitoring. Especially in the context of heart diseases, the possibility to transmit electrocardiograph (ECG) data in a streaming mode is of high interest. However, available cellular networks with protocols like GPRS, EDGE or UMTS are highly unreliable due to frequent connection interruptions and high bandwidth variations for data traffic. In this paper, we present a system suitable for live ECG-streaming over UMTS. We describe a usability experiment of the system within the context of the Berlin-Marathon, a huge event with 40.000 participants - 5 of them carrying devices with our software for live ECG streaming. The systems successfully demonstrated the use of near-field Bluetooth communication between electronic health care devices and a home broker in conjunction with mobile communication via UMTS. The forthcoming Fontane system builds upon experiences collected with the current prototype. We present these experiences and discusses some of the challenges of live streaming of medical data across unreliable heterogeneous networks.

Towards a real-time implementation of the ECMA Common Language Infrastructure

In the development of embedded systems, higher-level programming languages have become popular because they often induce higher developer productivity. Tool developers desiring to offer support for such languages need to solve various problems; in particular, they need to support the creation of realtime systems. In this paper, we present an approach for supporting real-time capabilities in C# and, consequently, the Common Language Infrastructure

Scaling youth development training in IT using an xMOOC platform

The paper at hand evaluates the Massive Open Online Course (MOOC) Spielend Programmieren Lernen (Playfully learning to program), an effort to scale the youth development program at the Hasso Plattner Institute (HPI) for a larger audience. The HPI has a strong tradition in attracting children and adolescents to take their first steps towards a career in IT at an early age. The Schülerakademie, the Schülerkolleg, the Schülerklub, and the support for the CoderDojo in Potsdam are some of the regular activities in this context to take youngsters by the hand and supply them with material and guidance in their mother tongue. With the emergence of MOOCs and the success of HPIs own MOOC Platform - openHPI - it was a natural step to develop a course to address an audience that is only marginally represented in openHPIs regular courses: school children and adolescents. A further novelty for openHPI in this course was the focus on teaching programming with a high percentage of obligatory hands-on tasks. Particularly for this course, a standalone tool allowing participants to write and evaluate code directly in the browser - without the need to install additional software - has been developed. We will compare this tool to a small selection of similar approaches on other platforms. As it will be shown, the course attracted a far more diverse audience than expected, and therefore, also needs to be seen in the context of spreading digital literacy amongst wider parts of society. In this context we also will discuss the significant differences in the usage of the forum between the course Spielend Programmieren Lernen and the course In-Memory Databases, a more traditional openHPI course.

KStruct: preserving consistency through C annotations

Debuggers and instrumentation tools have been proven valuable for understanding the inner workings of software systems. Although these tools are essential for various people, e.g., system administrators, developers, or teachers, they have one major drawback, especially in multi-threaded environments: They completely ignore data races. Within this paper, we present KStruct, a holistic approach for inspecting state information of a system while running. We therefore use a multi-level approach: First KStruct Access, our domain-specific language, can be used to model lock dependencies. Second, based on that model, we generate an access driver that dynamically attaches to the system under investigation and leverages that model to access state information. Our proposed approach can therefore improve quality in two dimensions: The code by making locking first-class primitives, and second the retrieved data is more reliable to be consistent.

The Grid-Occam Project

We present a new implementation of the old Occam language, using Microsoft .NET as the target platform. We show how Occam can be used to develop cluster and grid applications, and how such applications can be deployed. In particular, we discuss automatic placement of Occam processes onto processing nodes.

Feature salience for neural networks: comparing algorithms

One of the key problems in the field of telemedicine is the prediction of the patients health state change based on incoming non-invasively measured vital data. Artificial Neural Networks (ANN) are a powerful statistical modeling tool suitable for this problem. Feature salience algorithms for ANN provide information about feature importance and help selecting relevant input variables. Looking for a reliable salience analysis algorithm, we found a relatively wide range of possible approaches. However, we have also found numerous methodological weaknesses in corresponding evaluations. Perturb [11][7] and Connection Weight (CW) [1] are two of the most promising algorithms. In this paper, we propose an improvement for Connection Weight and evaluate it along with Perturb and the original CW. We use three independent datasets with already known feature salience rankings as well as varying topologies and random feature ranking results to estimate the usability of the tested approaches for feature salience assessment in complex multi-layer perceptrons.