18,153 research outputs found

    Assessing Traceability of Software Engineering Artifacts

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    The generation of traceability links or traceability matrices is vital to many software engineering activities. It is also person-power intensive, time-consuming, error-prone, and lacks tool support. The activities that require traceability information include, but are not limited to, risk analysis, impact analysis, criticality assessment, test coverage analysis, and verification and validation of software systems. Information Retrieval (IR) techniques have been shown to assist with the automated generation of traceability links by reducing the time it takes to generate the traceability mapping. Researchers have applied techniques such as Latent Semantic Indexing (LSI), vector space retrieval, and probabilistic IR and have enjoyed some success. This paper concentrates on examining issues not previously widely studied in the context of traceability: the importance of the vocabulary base used for tracing and the evaluation and assessment of traceability mappings and methods using secondary measures. We examine these areas and perform empirical studies to understand the importance of each to the traceability of software engineering artifacts

    Collaborative traceability management: a multiple case study from the perspectives of organization, process, and culture

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    Traceability is crucial for many activities in software and systems engineering including monitoring the development progress, and proving compliance with standards. In practice, the use and maintenance of trace links are challenging as artifacts undergo constant change, and development takes place in distributed scenarios with multiple collaborating stakeholders. Although traceability management in general has been addressed in previous studies, there is a need for empirical insights into the collaborative aspects of traceability management and how it is situated in existing development contexts. The study reported in this paper aims to close this gap by investigating the relation of collaboration and traceability management, based on an understanding of characteristics of the development effort. In our multiple exploratory case study, we conducted semi-structured interviews with 24 individuals from 15 industrial projects. We explored which challenges arise, how traceability management can support collaboration, how collaboration relates to traceability management approaches, and what characteristics of the development effort influence traceability management and collaboration. We found that practitioners struggle with the following challenges: (1) collaboration across team and tool boundaries, (2) conveying the benefits of traceability, and (3) traceability maintenance. If these challenges are addressed, we found that traceability can facilitate communication and knowledge management in distributed contexts. Moreover, there exist multiple approaches to traceability management with diverse collaboration approaches, i.e., requirements-centered, developer-driven, and mixed approaches. While traceability can be leveraged in software development with both agile and plan-driven paradigms, a certain level of rigor is needed to realize its benefits and overcome challenges. To support practitioners, we provide principles of collaborative traceability management. The main contribution of this paper is empirical evidence of how culture, processes, and organization impact traceability management and collaboration, and principles to support practitioners with collaborative traceability management. We show that collaboration and traceability management have the potential to be mutually beneficial—when investing in one, also the other one is positively affected

    Collaborative traceability management: a multiple case study from the perspectives of organization, process, and culture

    Get PDF
    Traceability is crucial for many activities in software and systems engineering including monitoring the development progress, and proving compliance with standards. In practice, the use and maintenance of trace links are challenging as artifacts undergo constant change, and development takes place in distributed scenarios with multiple collaborating stakeholders. Although traceability management in general has been addressed in previous studies, there is a need for empirical insights into the collaborative aspects of traceability management and how it is situated in existing development contexts. The study reported in this paper aims to close this gap by investigating the relation of collaboration and traceability management, based on an understanding of characteristics of the development effort. In our multiple exploratory case study, we conducted semi-structured interviews with 24 individuals from 15 industrial projects. We explored which challenges arise, how traceability management can support collaboration, how collaboration relates to traceability management approaches, and what characteristics of the development effort influence traceability management and collaboration. We found that practitioners struggle with the following challenges: (1) collaboration across team and tool boundaries, (2) conveying the benefits of traceability, and (3) traceability maintenance. If these challenges are addressed, we found that traceability can facilitate communication and knowledge management in distributed contexts. Moreover, there exist multiple approaches to traceability management with diverse collaboration approaches, i.e., requirements-centered, developer-driven, and mixed approaches. While traceability can be leveraged in software development with both agile and plan-driven paradigms, a certain level of rigor is needed to realize its benefits and overcome challenges. To support practitioners, we provide principles of collaborative traceability management. The main contribution of this paper is empirical evidence of how culture, processes, and organization impact traceability management and collaboration, and principles to support practitioners with collaborative traceability management. We show that collaboration and traceability management have the potential to be mutually beneficial—when investing in one, also the other one is positively affected

    Grand Challenges of Traceability: The Next Ten Years

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    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

    Full text link
    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

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    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

    An analysis of the requirements traceability problem

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    In this paper1, we investigate and discuss the underlying nature of the requirements traceability problem. Our work is based on empirical studies, involving over 100 practitioners, and an evaluation of current support. We introduce the distinction between pre-requirements specification (pre-RS) traceability and post-requirements specification (post-RS) traceability, to demonstrate why an all-encompassing solution to the problem is unlikely, and to provide a framework through which to understand its multifaceted nature. We report how the majority of the problems attributed to poor requirements traceability are due to inadequate pre-RS traceability and show the fundamental need for improvements here. In the remainder of the paper, we present an analysis of the main barriers confronting such improvements in practice, identify relevant areas in which advances have been (or can be) made, and make recommendations for research

    An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development

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    In this paper, we investigate model-driven engineering, reporting on an exploratory case-study conducted at a large automotive company. The study consisted of interviews with 20 engineers and managers working in different roles. We found that, in the context of a large organization, contextual forces dominate the cognitive issues of using model-driven technology. The four forces we identified that are likely independent of the particular abstractions chosen as the basis of software development are the need for diffing in software product lines, the needs for problem-specific languages and types, the need for live modeling in exploratory activities, and the need for point-to-point traceability between artifacts. We also identified triggers of accidental complexity, which we refer to as points of friction introduced by languages and tools. Examples of the friction points identified are insufficient support for model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe

    A framework for the successful implementation of food traceability systems in China

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    Implementation of food traceability systems in China faces many challenges due to the scale, diversity and complexity of China’s food supply chains. This study aims to identify critical success factors specific to the implementation of traceability systems in China. Twenty-seven critical success factors were identified in the literature. Interviews with managers at four food enterprises in a pre-study helped identify success criteria and five additional critical success factors. These critical success factors were tested through a survey of managers in eighty-three food companies. This study identifies six dimensions for critical success factors: laws, regulations and standards; government support; consumer knowledge and support; effective management and communication; top management and vendor support; and information and system quality
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