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

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

Launching the Grand Challenges for Ocean Conservation

The ten most pressing Grand Challenges in Oceans Conservation were identified at the Oceans Big Think and described in a detailed working document:A Blue Revolution for Oceans: Reengineering Aquaculture for SustainabilityEnding and Recovering from Marine DebrisTransparency and Traceability from Sea to Shore:  Ending OverfishingProtecting Critical Ocean Habitats: New Tools for Marine ProtectionEngineering Ecological Resilience in Near Shore and Coastal AreasReducing the Ecological Footprint of Fishing through Smarter GearArresting the Alien Invasion: Combating Invasive SpeciesCombatting the Effects of Ocean AcidificationEnding Marine Wildlife TraffickingReviving Dead Zones: Combating Ocean Deoxygenation and Nutrient Runof

Science for Global Ubiquitous Computing

This paper describes an initiative to provide theories that can underlie the development of the Global Ubiquitous Computer, the network of ubiquitous computing devices that will pervade the civilised world in the course of the next few decades. We define the goals of the initiative and the criteria for judging whether they are achieved; we then propose a strategy for the exercise. It must combine a bottom-up development of theories in directions that are currently pursued with success, together with a top-down approach in the form of collaborative projects relating these theories to engineered systems that exist or are imminent

3D printed muscle-powered bio-bots

Complex biological systems sense, process, and respond to a range of environmental signals in real-time. The ability of such systems to adapt their functional response to dynamic external signals motivates the use of biological materials in other engineering applications. Recent advances in 3D printing have enabled the manufacture of complex structures from biological materials. We have developed a projection stereolithographic 3D printing apparatus capable of patterning cells and biocompatible polymers at physiologically relevant length scales, on the order of single cells. This enables reverse engineering in vitro model systems that recreate the structure and function of native tissue for applications ranging from high-throughput drug testing to regenerative medicine. While reverse engineering native tissues and organs has important implications in biomedical engineering, the ability to “build with biology” presents the next generation of engineers with both a unique design challenge and opportunity. Specifically, we now have the ability to forward engineer bio-hybrid machines and robots (bio-bots) that harness the adaptive functionalities of biological materials to achieve more complex functional behaviors than machines composed of synthetic materials alone. Perhaps the most intuitive demonstration of a “living machine” is a system that can generate force and produce motion. To that end, we have designed and 3D printed locomotive bio-bots, powered by external electrical and optical stimuli. In addition to being the first demonstrations of untethered locomotion in skeletal musclepowered soft robots, these bio-hybrid machines have served as meso-scale models for studying tissue self-assembly, maturation, damage, remodeling, and healing in vitro. Bio-hybrid machines that can dynamically sense and adaptively respond to a range of environmental signals have broad applicability in healthcare applications such as dynamic implants or targeted drug delivery. Advanced research in exoskeletons and hyper-natural functionality could even extend the useful application of such machines to national defense and environmental cleanup. We have developed a modular skeletal muscle bioactuator that can serve as a fundamental building block for such machines, setting the stage for future generations of bio-hybrid machines that can self-assemble, self-heal, and perhaps even self-replicate to target grand engineering challenges. Furthermore, we present a robust optimized protocol for manufacturing 3D printed muscle-powered biological machines, and a mechanism to incorporate biological “building blocks” into the toolbox of the next generation of engineers and scientists

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Models in the Cloud: Exploring Next Generation Environmental Software Systems

There is growing interest in the application of the latest trends in computing and data science methods to improve environmental science. However we found the penetration of best practice from computing domains such as software engineering and cloud computing into supporting every day environmental science to be poor. We take from this work a real need to re-evaluate the complexity of software tools and bring these to the right level of abstraction for environmental scientists to be able to leverage the latest developments in computing. In the Models in the Cloud project, we look at the role of model driven engineering, software frameworks and cloud computing in achieving this abstraction. As a case study we deployed a complex weather model to the cloud and developed a collaborative notebook interface for orchestrating the deployment and analysis of results. We navigate relatively poor support for complex high performance computing in the cloud to develop abstractions from complexity in cloud deployment and model configuration. We found great potential in cloud computing to transform science by enabling models to leverage elastic, flexible computing infrastructure and support new ways to deliver collaborative and open science

Open problems in artificial life

This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated