260,951 research outputs found
Bridging the Experimental Gap: Applying Continuous Experimentation to the Field of Cyber-Physical Systems, in the Example of the Automotive Domain
In the software world frequent updates and fast delivery of new features are needed by companies to bring value to customers and not lag behind competition. When in cyber-physical systems the software functionality dominates in importance the hardware capabilities, the same speed in creating new value is needed by the product owners to differentiate their products and attract customers. The automotive field is an example of a domain that will face this challenge as the industry races to achieve self-driving vehicles, which will necessarily be software-intensive highly complex cyber-physical systems. A software engineering practice capable of accelerating and guiding the software production process using real-world data is Continuous Experimentation. This practice proved to be valuable in software-intensive web-based systems, allowing data-driven software evolution. It involves the use of experiments, which are instrumented versions of the software to be tested, deployed to the actual systems and executed in a limited way alongside the official software version. Valuable data on the future behavior of the prospective feature is collected in this way as it was fed the same real-world data it would encounter once approved and deployed. Additionally, in those cases where an experimental software version can be run as a replacement for the official version, relevant data regarding the system-user interaction can be gathered. In this thesis, the field of cyber-physical systems and the automotive practitioners\u27 perspective on Continuous Experimentation are sampled employing a literature review and a series of case studies. A set of necessary architectural characteristics are defined and possible methods to overcome the issue of resource constraints in cyber-physical systems are proposed in two exploratory studies. Finally, a design study shows and analyses a prototype of a Continuous Experimentation cycle that was designed and executed in a project partnered by Revere, the Chalmers University of Technology\u27s laboratory for vehicle research
How software engineering research aligns with design science: A review
Background: Assessing and communicating software engineering research can be
challenging. Design science is recognized as an appropriate research paradigm
for applied research but is seldom referred to in software engineering.
Applying the design science lens to software engineering research may improve
the assessment and communication of research contributions. Aim: The aim of
this study is 1) to understand whether the design science lens helps summarize
and assess software engineering research contributions, and 2) to characterize
different types of design science contributions in the software engineering
literature. Method: In previous research, we developed a visual abstract
template, summarizing the core constructs of the design science paradigm. In
this study, we use this template in a review of a set of 38 top software
engineering publications to extract and analyze their design science
contributions. Results: We identified five clusters of papers, classifying them
according to their alignment with the design science paradigm. Conclusions: The
design science lens helps emphasize the theoretical contribution of research
output---in terms of technological rules---and reflect on the practical
relevance, novelty, and rigor of the rules proposed by the research.Comment: 32 pages, 10 figure
NPEFix: Automatic Runtime Repair of Null Pointer Exceptions in Java
Null pointer exceptions, also known as null dereferences are the number one
exceptions in the field. In this paper, we propose 9 alternative execution
semantics when a null pointer exception is about to happen. We implement those
alternative execution strategies using code transformation in a tool called
NPEfix. We evaluate our prototype implementation on 11 field null dereference
bugs and 519 seeded failures and show that NPEfix is able to repair at runtime
10/11 and 318/519 failures
Grand Challenges of Traceability: The Next Ten Years
In 2007, the software and systems traceability community met at the first
Natural Bridge symposium on the Grand Challenges of Traceability to establish
and address research goals for achieving effective, trustworthy, and ubiquitous
traceability. Ten years later, in 2017, the community came together to evaluate
a decade of progress towards achieving these goals. These proceedings document
some of that progress. They include a series of short position papers,
representing current work in the community organized across four process axes
of traceability practice. The sessions covered topics from Trace Strategizing,
Trace Link Creation and Evolution, Trace Link Usage, real-world applications of
Traceability, and Traceability Datasets and benchmarks. Two breakout groups
focused on the importance of creating and sharing traceability datasets within
the research community, and discussed challenges related to the adoption of
tracing techniques in industrial practice. Members of the research community
are engaged in many active, ongoing, and impactful research projects. Our hope
is that ten years from now we will be able to look back at a productive decade
of research and claim that we have achieved the overarching Grand Challenge of
Traceability, which seeks for traceability to be always present, built into the
engineering process, and for it to have "effectively disappeared without a
trace". We hope that others will see the potential that traceability has for
empowering software and systems engineers to develop higher-quality products at
increasing levels of complexity and scale, and that they will join the active
community of Software and Systems traceability researchers as we move forward
into the next decade of research
Dynamic Mutant Subsumption Analysis using LittleDarwin
Many academic studies in the field of software testing rely on mutation
testing to use as their comparison criteria. However, recent studies have shown
that redundant mutants have a significant effect on the accuracy of their
results. One solution to this problem is to use mutant subsumption to detect
redundant mutants. Therefore, in order to facilitate research in this field, a
mutation testing tool that is capable of detecting redundant mutants is needed.
In this paper, we describe how we improved our tool, LittleDarwin, to fulfill
this requirement
Speech-Gesture Mapping and Engagement Evaluation in Human Robot Interaction
A robot needs contextual awareness, effective speech production and
complementing non-verbal gestures for successful communication in society. In
this paper, we present our end-to-end system that tries to enhance the
effectiveness of non-verbal gestures. For achieving this, we identified
prominently used gestures in performances by TED speakers and mapped them to
their corresponding speech context and modulated speech based upon the
attention of the listener. The proposed method utilized Convolutional Pose
Machine [4] to detect the human gesture. Dominant gestures of TED speakers were
used for learning the gesture-to-speech mapping. The speeches by them were used
for training the model. We also evaluated the engagement of the robot with
people by conducting a social survey. The effectiveness of the performance was
monitored by the robot and it self-improvised its speech pattern on the basis
of the attention level of the audience, which was calculated using visual
feedback from the camera. The effectiveness of interaction as well as the
decisions made during improvisation was further evaluated based on the
head-pose detection and interaction survey.Comment: 8 pages, 9 figures, Under review in IRC 201
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