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

Software Engineers' Information Seeking Behavior in Change Impact Analysis - An Interview Study

Software engineers working in large projects must navigate complex information landscapes. Change Impact Analysis (CIA) is a task that relies on engineers' successful information seeking in databases storing, e.g., source code, requirements, design descriptions, and test case specifications. Several previous approaches to support information seeking are task-specific, thus understanding engineers' seeking behavior in specific tasks is fundamental. We present an industrial case study on how engineers seek information in CIA, with a particular focus on traceability and development artifacts that are not source code. We show that engineers have different information seeking behavior, and that some do not consider traceability particularly useful when conducting CIA. Furthermore, we observe a tendency for engineers to prefer less rigid types of support rather than formal approaches, i.e., engineers value support that allows flexibility in how to practically conduct CIA. Finally, due to diverse information seeking behavior, we argue that future CIA support should embrace individual preferences to identify change impact by empowering several seeking alternatives, including searching, browsing, and tracing.Comment: Accepted for publication in the proceedings of the 25th International Conference on Program Comprehensio

Determining the quality of mathematical software using reference data sets

This paper describes a methodology for evaluating the numerical accuracy of software that performs mathematical calculations. The authors explain how this methodology extends the concept of metrological traceability, which is fundamental to measurement, to include software quality. Overviews of two European Union-funded projects are also presented. The first project developed an infrastructure to allow software to be verified by testing, via the internet, using reference data sets. The primary focus of the project was software used within systems that make physical measurements. The second project, currently underway, explores using this infrastructure to verify mathematical software used within general scientific and engineering disciplines. Publications on using reference data sets for the verification of mathematical software are usually intended for a readership specialising in measurement science or mathematics. This paper is aimed at a more general readership, in particular software quality specialists and computer scientists. Further engagement with experts in these disciplines will be helpful to the continued development of this application of software quality

Information technology as boundary object for transformational learning

Collaborative work is considered as a way to improve productivity and value generation in construction. However, recent research demonstrates that socio-cognitive factors related to fragmentation of specialized knowledge may hinder team performance. New methods based on theories of practice are emerging in Computer Supported Collaborative Work and organisational learning to break these knowledge boundaries, facilitating knowledge sharing and the generation of new knowledge through transformational learning. According to these theories, objects used in professional practice play a key role in mediating interactions. Rules and methods related to these practices are also embedded in these objects. Therefore changing collaborative patterns demand reconfiguring objects that are at the boundary between specialized practices, namely boundary objects. This research is unique in presenting an IT strategy in which technology is used as a boundary object to facilitate transformational learning in collaborative design work

Blockchain For Food: Making Sense of Technology and the Impact on Biofortified Seeds

The global food system is under pressure and is in the early stages of a major transition towards more transparency, circularity, and personalisation. In the coming decades, there is an increasing need for more food production with fewer resources. Thus, increasing crop yields and nutritional value per crop is arguably an important factor in this global food transition. Biofortification can play an important role in feeding the world. Biofortified seeds create produce with increased nutritional values, mainly minerals and vitamins, while using the same or less resources as non-biofortified variants. However, a farmer cannot distinguish a biofortified seed from a regular seed. Due to the invisible nature of the enhanced seeds, counterfeit products are common, limiting wide-scale adoption of biofortified crops. Fraudulent seeds pose a major obstacle in the adoption of biofortified crops. A system that could guarantee the origin of the biofortified seeds is therefore required to ensure widespread adoption. This trust-ensuring immutable proof for the biofortified seeds, can be provided via blockchain technology

Model Based Development of Quality-Aware Software Services

Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration

The MegaM@Rt2 ECSEL project: MegaModelling at runtime-scalable model-based framework for continuous development and runtime validation of complex systems

A major challenge for the European electronic components and systems (ECS) industry is to increase productivity and reduce costs while ensuring safety and quality. Model-Driven Engineering (MDE) principles have already shown valuable capabilities for the development of ECSs but still need to scale to support real-world scenarios implied by the full deployment and use of complex electronic systems, such as Cyber-Physical Systems, and real-time systems. Moreover, maintaining efficient traceability, integration and communication between fundamental stages of the development lifecycle (i.e., design time and runtime) is another challenge to the scalability of MDE tools and techniques. This paper presents “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), an ECSEL–JU project whose main goal is to address the above mentioned challenges. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2aims to deliver a framework of tools and methods for: (i) system engineering/design and continuous development, (ii) related runtime analysis, and (iii) global model and traceability management.This project has received funding from the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No. 737494. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and from Sweden, France, Spain, Italy, Finland & Czech Republic

A Systematic Review of Tracing Solutions in Software Product Lines

Software Product Lines are large-scale, multi-unit systems that enable massive, customized production. They consist of a base of reusable artifacts and points of variation that provide the system with flexibility, allowing generating customized products. However, maintaining a system with such complexity and flexibility could be error prone and time consuming. Indeed, any modification (addition, deletion or update) at the level of a product or an artifact would impact other elements. It would therefore be interesting to adopt an efficient and organized traceability solution to maintain the Software Product Line. Still, traceability is not systematically implemented. It is usually set up for specific constraints (e.g. certification requirements), but abandoned in other situations. In order to draw a picture of the actual conditions of traceability solutions in Software Product Lines context, we decided to address a literature review. This review as well as its findings is detailed in the present article.Comment: 22 pages, 9 figures, 7 table