Pub Date : 2019-11-14DOI: 10.1109/VISSOFT.2019.00017
P. Seipel, Adrian Stock, S. Santhanam, Artur Baranowski, N. Hochgeschwender, A. Schreiber
Exploring of software architectures with software visualization in Augmented Reality (AR) is possible with different interaction methods, such gesture, gaze, and speech. For interaction with speech (i.e., natural language), we present an architecture and an implementation of conversational interfaces for the Microsoft HoloLens device. We aim to remedy some peculiarities of AR devices, but also enhancing the exploration task at hand. To implement the conversational interface different natural language processing (NLP) components such as natural language generation and intent recognition are typically required. Our proposed architecture integrates conversational components with the AR-based software visualization. We describe its implementation based on different user utterances, where the system provides information about the to-be-explored component-based software architecture in the form of adjusted visualizations and speech-based results. We apply out tool to explore OSGi-based software architectures.
{"title":"Speak to your Software Visualization—Exploring Component-Based Software Architectures in Augmented Reality with a Conversational Interface","authors":"P. Seipel, Adrian Stock, S. Santhanam, Artur Baranowski, N. Hochgeschwender, A. Schreiber","doi":"10.1109/VISSOFT.2019.00017","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00017","url":null,"abstract":"Exploring of software architectures with software visualization in Augmented Reality (AR) is possible with different interaction methods, such gesture, gaze, and speech. For interaction with speech (i.e., natural language), we present an architecture and an implementation of conversational interfaces for the Microsoft HoloLens device. We aim to remedy some peculiarities of AR devices, but also enhancing the exploration task at hand. To implement the conversational interface different natural language processing (NLP) components such as natural language generation and intent recognition are typically required. Our proposed architecture integrates conversational components with the AR-based software visualization. We describe its implementation based on different user utterances, where the system provides information about the to-be-explored component-based software architecture in the form of adjusted visualizations and speech-based results. We apply out tool to explore OSGi-based software architectures.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123286960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/VISSOFT.2019.00010
Carol V. Alexandru, Sebastian Proksch, Pooyan Behnamghader, H. Gall
Understanding the evolution of a project is crucial in reverse-engineering, auditing and otherwise understanding existing software. Visualizing how software evolves can be challenging, as it typically abstracts a multi-dimensional graph structure where individual components undergo frequent but localized changes. Existing approaches typically consider either only a small number of revisions or they focus on one particular aspect, such as the evolution of code metrics or architecture. Approaches using a static view with a time axis (such as line charts) are limited in their expressiveness regarding structure, and approaches visualizing structure quickly become cluttered with an increasing number of revisions and components. We propose a novel trade-off between displaying global structure over a large time period with reduced accuracy and visualizing fine-grained changes of individual components with absolute accuracy. We demonstrate how our approach displays changes by blending redundant visual features (such as scales or repeating data points) where they are not expressive. We show how using this approach to explore software evolution can reveal ephemeral information when familiarizing oneself with a new project. We provide a working implementation as an extension to our open-source library for fine-grained evolution analysis, LISA.
{"title":"Evo-Clocks: Software Evolution at a Glance","authors":"Carol V. Alexandru, Sebastian Proksch, Pooyan Behnamghader, H. Gall","doi":"10.1109/VISSOFT.2019.00010","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00010","url":null,"abstract":"Understanding the evolution of a project is crucial in reverse-engineering, auditing and otherwise understanding existing software. Visualizing how software evolves can be challenging, as it typically abstracts a multi-dimensional graph structure where individual components undergo frequent but localized changes. Existing approaches typically consider either only a small number of revisions or they focus on one particular aspect, such as the evolution of code metrics or architecture. Approaches using a static view with a time axis (such as line charts) are limited in their expressiveness regarding structure, and approaches visualizing structure quickly become cluttered with an increasing number of revisions and components. We propose a novel trade-off between displaying global structure over a large time period with reduced accuracy and visualizing fine-grained changes of individual components with absolute accuracy. We demonstrate how our approach displays changes by blending redundant visual features (such as scales or repeating data points) where they are not expressive. We show how using this approach to explore software evolution can reveal ephemeral information when familiarizing oneself with a new project. We provide a working implementation as an extension to our open-source library for fine-grained evolution analysis, LISA.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127835249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-01DOI: 10.1109/VISSOFT.2019.00012
Juan Pablo Sandoval Alcocer, Harold Camacho Jaimes, D. Costa, Alexandre Bergel, Fabian Beck
Monitoring software performance evolution is a daunting and challenging task. This paper proposes a lightweight visualization technique that contrasts source code variation with the memory consumption and execution time of a particular benchmark. The visualization fully integrates with the commit graph as common in many software repository managers. We illustrate the usefulness of our approach with two application examples. We expect our technique to be beneficial for practitioners who wish to easily review the impact of source code commits on software performance.
{"title":"Enhancing Commit Graphs with Visual Runtime Clues","authors":"Juan Pablo Sandoval Alcocer, Harold Camacho Jaimes, D. Costa, Alexandre Bergel, Fabian Beck","doi":"10.1109/VISSOFT.2019.00012","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00012","url":null,"abstract":"Monitoring software performance evolution is a daunting and challenging task. This paper proposes a lightweight visualization technique that contrasts source code variation with the memory consumption and execution time of a particular benchmark. The visualization fully integrates with the commit graph as common in many software repository managers. We illustrate the usefulness of our approach with two application examples. We expect our technique to be beneficial for practitioners who wish to easily review the impact of source code commits on software performance.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124928917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-01DOI: 10.1109/VISSOFT.2019.00021
S. Levin, A. Yehudai
Lehman's Laws teach us that a software system will become progressively less satisfying to its users over time, unless it is continually adapted to meet new needs. A line of previous works sought to better understand software maintenance by studying how commits can be classified into three main software maintenance activities. Corrective: fault fixing; Perfective: system improvements; Adaptive: new feature introduction. In this work we suggest visualizations for exploring software maintenance activities in both project and individual developer scopes. We demonstrate our approach using a prototype we have built using the Shiny R framework. In addition, we have also published our prototype as an online demo. This demo allows users to explore the maintenance activities of a number of popular open source projects. We believe that the visualizations we provide can assist practitioners in monitoring and maintaining the health of software projects. In particular, they can be useful for identifying general imbalances, peaks, deeps and other anomalies in projects' and developers' maintenance activities.
{"title":"Visually Exploring Software Maintenance Activities","authors":"S. Levin, A. Yehudai","doi":"10.1109/VISSOFT.2019.00021","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00021","url":null,"abstract":"Lehman's Laws teach us that a software system will become progressively less satisfying to its users over time, unless it is continually adapted to meet new needs. A line of previous works sought to better understand software maintenance by studying how commits can be classified into three main software maintenance activities. Corrective: fault fixing; Perfective: system improvements; Adaptive: new feature introduction. In this work we suggest visualizations for exploring software maintenance activities in both project and individual developer scopes. We demonstrate our approach using a prototype we have built using the Shiny R framework. In addition, we have also published our prototype as an online demo. This demo allows users to explore the maintenance activities of a number of popular open source projects. We believe that the visualizations we provide can assist practitioners in monitoring and maintaining the health of software projects. In particular, they can be useful for identifying general imbalances, peaks, deeps and other anomalies in projects' and developers' maintenance activities.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116146760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-01DOI: 10.1109/VISSOFT.2019.00020
Jack Slater, C. Anslow, Jens Dietrich, Leonel Merino
We do not know fully understand how software violates metrics based principles, particularly in large systems. Systems are restricted by structural and static deficiencies that we can aim to reduce by providing developers with effective visualizations of their code. We developed CorpusVis a widget-based application to explore software metrics of Java software systems from the Qualitas Corpus. Through an evaluation of the visualization techniques we identified what visualizations were effective and which ones did not scale well for large software systems. Our application helps to reduce the structural and static deficiencies in developers code which enables developers to spend less time maintaining legacy systems and learn to develop more effective code for future systems.
{"title":"CorpusVis – Visualizing Software Metrics at Scale","authors":"Jack Slater, C. Anslow, Jens Dietrich, Leonel Merino","doi":"10.1109/VISSOFT.2019.00020","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00020","url":null,"abstract":"We do not know fully understand how software violates metrics based principles, particularly in large systems. Systems are restricted by structural and static deficiencies that we can aim to reduce by providing developers with effective visualizations of their code. We developed CorpusVis a widget-based application to explore software metrics of Java software systems from the Qualitas Corpus. Through an evaluation of the visualization techniques we identified what visualizations were effective and which ones did not scale well for large software systems. Our application helps to reduce the structural and static deficiencies in developers code which enables developers to spend less time maintaining legacy systems and learn to develop more effective code for future systems.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127273672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-01DOI: 10.1109/VISSOFT.2019.00013
Laure Bedu, Olivier Tinh, Fábio Petrillo
Software visualization (SV) allows us to visualize different aspects and artifacts related to software, thus helping engineers understanding its underlying design and functionalities in a more efficient and faster way. In this paper, we conducted a tertiary systematic literature review to identify, classify, and evaluate the current state of the art on software visualization from 48 software visualization secondary studies, following three perspectives: publication trends, software visualization topics and techniques, and issues related to research field. Hence, we summarized the main findings among popular sub-fields of SV, identifying potential research directions and fifteen shared recommendations for developers, instructors and researchers. Our main findings are the lack of rigorous evaluation or theories support to assess SV tools effectiveness, the disconnection between tool design and their scope, and the dispersal of the research community.
{"title":"A Tertiary Systematic Literature Review on Software Visualization","authors":"Laure Bedu, Olivier Tinh, Fábio Petrillo","doi":"10.1109/VISSOFT.2019.00013","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00013","url":null,"abstract":"Software visualization (SV) allows us to visualize different aspects and artifacts related to software, thus helping engineers understanding its underlying design and functionalities in a more efficient and faster way. In this paper, we conducted a tertiary systematic literature review to identify, classify, and evaluate the current state of the art on software visualization from 48 software visualization secondary studies, following three perspectives: publication trends, software visualization topics and techniques, and issues related to research field. Hence, we summarized the main findings among popular sub-fields of SV, identifying potential research directions and fifteen shared recommendations for developers, instructors and researchers. Our main findings are the lack of rigorous evaluation or theories support to assess SV tools effectiveness, the disconnection between tool design and their scope, and the dispersal of the research community.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131637169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-01DOI: 10.1109/VISSOFT.2019.00019
Ying Wang, Jorin Weatherston, M. Storey, D. Germán
Assembly code analysis is an intensive process undertaken by security analysts and reverse engineers to discover vulnerabilities in existing software when source code is unavailable. Kam1n0 is an efficient code clone search engine that facilitates assembly code analysis. However, Kam1n0 search results can contain millions of function-clone pairs, and efficiently exploring and comprehensively understanding the resulting data can be challenging. This paper presents a design study whereby we collaborated with analyst stakeholders to identify requirements for a tool that visualizes and scales to millions of function-clone pairs. These requirements led to the design of an interactive visual tool, CloneCompass, consisting of novel TreeMap Matrix and Adjacency Matrix visualizations to aid in the exploration of assembly code clones extracted from Kam1n0. We conducted a preliminary evaluation with the analyst stakeholders and show how CloneCompass enables these users to visually and interactively explore code clone data generated from software systems with suspected vulnerabilities.
{"title":"CloneCompass: Visualizations for Exploring Assembly Code Clone Ecosystems","authors":"Ying Wang, Jorin Weatherston, M. Storey, D. Germán","doi":"10.1109/VISSOFT.2019.00019","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00019","url":null,"abstract":"Assembly code analysis is an intensive process undertaken by security analysts and reverse engineers to discover vulnerabilities in existing software when source code is unavailable. Kam1n0 is an efficient code clone search engine that facilitates assembly code analysis. However, Kam1n0 search results can contain millions of function-clone pairs, and efficiently exploring and comprehensively understanding the resulting data can be challenging. This paper presents a design study whereby we collaborated with analyst stakeholders to identify requirements for a tool that visualizes and scales to millions of function-clone pairs. These requirements led to the design of an interactive visual tool, CloneCompass, consisting of novel TreeMap Matrix and Adjacency Matrix visualizations to aid in the exploration of assembly code clones extracted from Kam1n0. We conducted a preliminary evaluation with the analyst stakeholders and show how CloneCompass enables these users to visually and interactively explore code clone data generated from software systems with suspected vulnerabilities.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116068854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-01DOI: 10.1109/VISSOFT.2019.00018
A. Hori, M. Kawakami, M. Ichii
Derivative software development complicates the base software over the years of enhancement and maintenance. It reduces the source code readability, taking developers a long time to understand the software structure and its various parts. In software engineering, software is often compared to buildings. We propose to use this metaphor from a new prospective to help developers understand the existing software efficiently. In this paper, we present a tool called "CodeHouse" that visualizes the source code of the software in a VR space as if it were a house. By placing rooms, which represent modules of the software, on the inside of a virtual cylinder, the CodeHouse makes it possible for the developers to understand both the whole structure of the software and the details of individual program parts before they begin derivative development. The CodeHouse also links with a debugger and helps developers to understand the dynamic behaviors of the program.
{"title":"CodeHouse: VR Code Visualization Tool","authors":"A. Hori, M. Kawakami, M. Ichii","doi":"10.1109/VISSOFT.2019.00018","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00018","url":null,"abstract":"Derivative software development complicates the base software over the years of enhancement and maintenance. It reduces the source code readability, taking developers a long time to understand the software structure and its various parts. In software engineering, software is often compared to buildings. We propose to use this metaphor from a new prospective to help developers understand the existing software efficiently. In this paper, we present a tool called \"CodeHouse\" that visualizes the source code of the software in a VR space as if it were a house. By placing rooms, which represent modules of the software, on the inside of a virtual cylinder, the CodeHouse makes it possible for the developers to understand both the whole structure of the software and the details of individual program parts before they begin derivative development. The CodeHouse also links with a debugger and helps developers to understand the dynamic behaviors of the program.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124651468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-01DOI: 10.1109/VISSOFT.2019.00015
L. M. Kritzinger, Thomas Krismayer, Rick Rabiser, P. Grünbacher
Many requirements monitoring approaches have been proposed that check key properties of systems and their interactions at runtime. Some of these approaches also visualize monitoring results and provide details on requirements violations to end users. However, only few studies exist about the usefulness of requirements monitoring tools for practitioners, particularly regarding visualization. In this paper, we present a user study we have conducted with both industrial practitioners and researchers to assess the usefulness of visualization capabilities we have been developing for an event-based requirements monitoring tool. These capabilities allow users to monitor the status of the involved systems, to view trends and statistics, and to inspect the events and data that led to specific violations when diagnosing their root cause. We first performed a walkthrough of the tool using the cognitive dimensions of notations framework from the field of human-computer interaction. We then conducted a user study involving five software engineers of a large company from the automation software domain and four researchers. Using the tool's visualization capabilities all subjects succeeded in monitoring a real-world automation system and in diagnosing violations. Subjects regarded the visualization capabilities as essential for understanding the behavior of a complex system. Based on the study results we derive implications, opportunities, and risks of using visualization in requirements monitoring tools.
{"title":"A User Study on the Usefulness of Visualization Support for Requirements Monitoring","authors":"L. M. Kritzinger, Thomas Krismayer, Rick Rabiser, P. Grünbacher","doi":"10.1109/VISSOFT.2019.00015","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00015","url":null,"abstract":"Many requirements monitoring approaches have been proposed that check key properties of systems and their interactions at runtime. Some of these approaches also visualize monitoring results and provide details on requirements violations to end users. However, only few studies exist about the usefulness of requirements monitoring tools for practitioners, particularly regarding visualization. In this paper, we present a user study we have conducted with both industrial practitioners and researchers to assess the usefulness of visualization capabilities we have been developing for an event-based requirements monitoring tool. These capabilities allow users to monitor the status of the involved systems, to view trends and statistics, and to inspect the events and data that led to specific violations when diagnosing their root cause. We first performed a walkthrough of the tool using the cognitive dimensions of notations framework from the field of human-computer interaction. We then conducted a user study involving five software engineers of a large company from the automation software domain and four researchers. Using the tool's visualization capabilities all subjects succeeded in monitoring a real-world automation system and in diagnosing violations. Subjects regarded the visualization capabilities as essential for understanding the behavior of a complex system. Based on the study results we derive implications, opportunities, and risks of using visualization in requirements monitoring tools.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126316956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-01DOI: 10.1109/VISSOFT.2019.00016
Li Zhang, Jianxin Sun, Cole S. Peterson, Bonita Sharif, Hongfeng Yu
Eye tracking is a frequently used technique to collect data capturing users' strategies and behaviors in processing information. Understanding how programmers navigate through a large number of classes and methods to find bugs is important to educators and practitioners in software engineering. However, the eye tracking data collected on realistic codebases is massive compared to traditional eye tracking data on one static page. The same content may appear in different areas on the screen with users scrolling in an Integrated Development Environment (IDE). Hierarchically structured content and fluid method position compose the two major challenges for visualization. We present a dual-space analysis approach to explore eye tracking data by leveraging existing software visualizations and a new graph embedding visualization. We use the graph embedding technique to quantify the distance between two arbitrary methods, which offers a more accurate visualization of distance with respect to the inherent relations, compared with the direct software structure and the call graph. The visualization offers both naturalness and readability showing time-varying eye movement data in both the content space and the embedded space, and provides new discoveries in developers' eye tracking behaviors.
{"title":"Exploring Eye Tracking Data on Source Code via Dual Space Analysis","authors":"Li Zhang, Jianxin Sun, Cole S. Peterson, Bonita Sharif, Hongfeng Yu","doi":"10.1109/VISSOFT.2019.00016","DOIUrl":"https://doi.org/10.1109/VISSOFT.2019.00016","url":null,"abstract":"Eye tracking is a frequently used technique to collect data capturing users' strategies and behaviors in processing information. Understanding how programmers navigate through a large number of classes and methods to find bugs is important to educators and practitioners in software engineering. However, the eye tracking data collected on realistic codebases is massive compared to traditional eye tracking data on one static page. The same content may appear in different areas on the screen with users scrolling in an Integrated Development Environment (IDE). Hierarchically structured content and fluid method position compose the two major challenges for visualization. We present a dual-space analysis approach to explore eye tracking data by leveraging existing software visualizations and a new graph embedding visualization. We use the graph embedding technique to quantify the distance between two arbitrary methods, which offers a more accurate visualization of distance with respect to the inherent relations, compared with the direct software structure and the call graph. The visualization offers both naturalness and readability showing time-varying eye movement data in both the content space and the embedded space, and provides new discoveries in developers' eye tracking behaviors.","PeriodicalId":375862,"journal":{"name":"2019 Working Conference on Software Visualization (VISSOFT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132410717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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