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

Eye gaze and interaction contexts for change tasks – Observations and potential

The more we know about software developers’ detailed navigation behavior for change tasks, the better we are able to provide effective tool support. Currently, most empirical studies on developers performing change tasks are, however, limited to very small code snippets or limited by the granularity and detail of the data collected on developer’s navigation behavior. In our research, we extend this work by combining user interaction monitoring to gather interaction context – the code elements a developer selects and edits – with eye-tracking to gather more detailed and fine-granular gaze context-code elements a developer looked at. In a study with 12 professional and 10 student developers we gathered interaction and gaze contexts from participants working on three change tasks of an open source system. Based on an analysis of the data we found, amongst other results, that gaze context captures different aspects than interaction context and that developers only read small portions of code elements. We further explore the potential of the more detailed and fine-granular data by examining the use of the captured change task context to predict perceived task difficulty and to provide better and more fine-grained navigation recommendations. We discuss our findings and their implications for better tool support

VTrace-A Tool for Visualizing Traceability Links Among Software Artefacts for an Evolving System

Traceability Management plays a key role in tracing the life of a requirement through all the specifications produced during the development phase of a software project. A lack of traceability information not only hinders the understanding of the system but also will prove to be a bottleneck in the future maintenance of the system. Projects that maintain traceability information during the development stages somehow fail to upgrade their artefacts or maintain traceability among the different versions of the artefacts that are produced during the maintenance phase. As a result the software artefacts lose the trustworthiness and engineers mostly work from the source code for impact analysis. The goal of our research is on understanding the impact of visualizing traceability links on change management tasks for an evolving system. As part of our research we have implemented a Traceability Visualization Tool-VTrace that manages software artefacts and also enables the visualization of traceability links. The results of our controlled experiment show that subjects who used the tool were more accurate and faster on change management tasks than subjects that didn't use the tool

Understanding Eye Gaze Patterns in Code Comprehension

Program comprehension is a sub-field of software engineering that seeks to understand how developers understand programs. Comprehension acts as a starting point for many software engineering tasks such as bug fixing, refactoring, and feature creation. The dissertation presents a series of empirical studies to understand how developers comprehend software in realistic settings. The unique aspect of this work is the use of eye tracking equipment to gather fine-grained detailed information of what developers look at in software artifacts while they perform realistic tasks in an environment familiar to them, namely a context including both the Integrated Development Environment (Eclipse or Visual Studio) and a web browser (Google Chrome). The iTrace eye tracking infrastructure is used for certain eye tracking studies on large code files as it is able to handle page scrolling and context switching. The first study is a classroom-based study on how students actively trained in the classroom understand grouped units of C++ code. Results indicate students made many transitions between lines that were closer together, and were attracted the most to if statements and to a lesser extent assignment code. The second study seeks to understand how developers use Stack Overflow page elements to build summaries of open source project code. Results indicate participants focused more heavily on question and answer text, and the embedded code, more than they did the title, question tags, or votes. The third study presents a larger code summarization study using different information contexts: Stack Overflow, bug repositories and source code. Results show participants tended to visit up to two codebase files in either the combined or isolated codebase session, but visit more bug report pages, and spend longer time on new Stack Overflow pages they visited, when given either these two treatments in isolation. In the combined session, time spent on the one or two codebase files they viewed dominated the session time. Information learned from tracking developers\u27 gaze in these studies can form foundations for developer behavior models, which we hope can later inform recommendations for actions one might take to achieve workflow goals in these settings. Advisor: Bonita Shari

VTrace-A Tool for Visualizing Traceability Links among Software Artefacts for an Evolving System

Traceability Management plays a key role in tracing the life of a requirement through all the specifications produced during the development phase of a software project. A lack of traceability information not only hinders the understanding of the system but also will prove to be a bottleneck in the future maintenance of the system. Projects that maintain traceability information during the development stages somehow fail to upgrade their artefacts or maintain traceability among the different versions of the artefacts that are produced during the maintenance phase. As a result the software artefacts lose the trustworthiness and engineers mostly work from the source code for impact analysis. The goal of our research is on understanding the impact of visualizing traceability links on change management tasks for an evolving system. As part of our research we have implemented a Traceability Visualization Tool-VTrace that manages software artefacts and also enables the visualization of traceability links. The results of our controlled experiment show that subjects who used the tool were more accurate and faster on change management tasks than subjects that didn’t use the tool

On the Influence of Representation Type and Gender on Recognition Tasks of Program Comprehension

RÉSUMÉ L’objectif de la maintenance logicielle est d’améliorer les logiciels existants en préservant leur intégrité. La maintenance peut représenter jusqu’à 60% du budget d’un logiciel. Ainsi, améliorer la maintenabilité des logiciels est bénéfique aussi bien pour les fournisseurs que les utilisateurs de logiciels. Les développeurs de logiciels consacrent un effort considérable à la compréhension des programmes, qui est une étape primordiale à la maintenance logicielle. Nous faisons l’hypothèque que le genre des développeurs de logiciels et le type de représentation peut affecter leur effort et leur efficacité. Ces facteurs doivent être considérés et minutieusement analysés dans la mesure où ils peuvent cacher certains effets significatifs pouvant être identifiés en analysant le processus de compréhension. Dans cette thèse, nous nous inspirons de l’utilisation de l’occulomètre pour l’étude du processus cognitif lors de la résolution des problèmes. Nous avons effectué une étude fonctionnelle pour évaluer tous les travaux de recherche faisant usage de l’occulomètre en génie logiciel. Les résultats obtenus nous ont motivé à utiliser l’occulomètre pour effectuer un ensemble d’études afin analyser l’effet de deux facteurs importants sur la compréhension des programmes : le type de représentation (textuelle ou graphique) et le genre du développeur. Afin de comprendre comment les différents types de représentations et le genre influencent les stratégies de visualisation, nous avons étudié la différence de stratégie entre développeurs. Les résultats obtenus montrent que, comparé à une représentation graphique, la représentation sous forme de texte structuré aide mieux le développeur dans son processus cognitif lors de la compréhension des programmes de petite taille. Ainsi, la représentation textuelle requiert moins de temps et d’effort aux participants. Par contre, la représentation graphique est celle préférée par les développeurs. Nos résultats montrent que la structure topologique de la représentation graphique aide les développeurs à mémoriser l’emplacement des éléments et à retrouver plus rapidement les éléments pertinents comparé à la représentation textuelle. En plus, la structure hiérarchique de la représentation graphique guide les développeurs à suivre une stratégie de visualisation spécifique. Nous avons observé que les femmes et les hommes ont des stratégies de visualisation différentes lors de la lecture du code ou de la mémorisation des noms des identificateurs. Les femmes ont tendance à inspecter minutieusement toutes les options afin de procéder à l’élimination de la mauvaise réponse. Au contraire, les hommes ont tendance à inspecter brièvement certaines réponses. Pendant que les femmes consacrent plus de temps à analyser chaque type d’entité l’un après l’autre, les hommes alternent leur attention entre différents type d’entité.----------ABSTRACT The purpose of software maintenance is to correct and enhance an existing software system while preserving its integrity. Software maintenance can cost more than 60% of the budget of a software system, thus improving the maintainability of software is important for both the software industry and its customers. Program comprehension is the initial step of software maintenance that requires the major amount of maintenance’s time and effort. We conjuncture that developers’ gender and the type of representations that developers utilize to perform program comprehension impact their efficiency and effectiveness. These factors must be considered and carefully studied, because they may hide some significant effects to be found by analyzing the comprehension process. In this dissertation, inspired by the literature on the usefulness of eye-trackers to study the cognitive process involved in problem solving activities, we perform a mapping study and evaluate all research relevant to the use of eye-tracking technique in software engineering. The results motivate us to perform a set of eye-tracking studies to analyze the impact of two important factors on program comprehension: representation type (textual vs. graphical) and developers’ gender. Moreover, we investigate and compare viewing strategies variability amongst developers to understand how the representation type and gender differences influence viewing strategies. Overall, our results indicate that structured text provides more cognitive support for developers while performing program comprehension with small systems compared to a graphical representation. Developers spend less time and effort working with textual representations. However, developers mostly preferred to use graphical representations and our results confirm that the topological structure of graphical representations helps developers to memorize the location of the elements and to find the relevant ones faster in comparison with textual representation. Moreover, the hierarchical structure of the representation guides developers to follow specific viewing strategies while working with representations. Regarding the impact of gender, our results emphasize that male and female developers exploit different viewing strategies while reading source code or recalling the names of identifiers. Female developers seem to carefully weigh all options and rule out wrong answers, while male developers seem to quickly set their minds on some answers and move forward. Moreover, female developers spend more time on each source code entity and analyze it before going to the next one. In contrast, male developers utilize several attention switching strategies between different source code entities

Data Journeys in the Sciences

This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research