Software Visualization Today - Systematic Literature Review

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Anna-Liisa Mattila; Petri Ihantola; Terhi Kilamo; Antti Luoto; Mikko Nurminen; Heli Väätäjä, Tampere University of Technology

Technology

Software Visualization Today
Results of literature review
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Research Design
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Research questions
• What is the focus of software visualization (SV) research?
– Why software is visualized?
– What are the visualization methods used in SV?
– What are the data sources used in SV?
• What is the maturity of SV research field?
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Research process
Defining
research goals
Selecting
sources of
literature
Screening of
literature
Conducting
searches
Defining
classification
scheme
Testing data
extraction form
Qalitative
analysis
Quantitative
analysis
Synthesis
Testing search
terms
Data extraction
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Analysis
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Example Visualizations
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Code City
https://wettel.github.io/
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Polymetric Views
http://xray.inf.usi.ch/xray.php
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Seesoft, line based code visualization
http://www.cs.umd.edu/class/spring2001/cmsc838b/Project/Parija_Spacco/old_viewtips.html
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Disk Usage Utilities
https://softvis.wordpress.com/2011/03/23/disk-usage-utilities/
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Dependency Structure Matrix
http://www.softviscollection.org/vis/dependency-structure-matrix/
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto,
Mikko Nurminen, Heli Väätäjä

Code Ownership Distribution Map
http://www.softviscollection.org/vis/code-ownership-distribution-map/
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Results
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Why software is visualized?
• To understand software structure
• To understand software behavior
• To understand software evolution
• For optimizing different aspects of software
• For project management purposes
• To understand how developers work
• For requirements management
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Visualization methods used in SV
Visualization types
• Trees and graphs
• Geometric projection techniques
• Text based visualizations
• Timelines
• Info graphics
Visualization attributes
• Color
• Spatial position
• Size
• Shape
• Animation
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Data in SV
Data sources
• Source code
• Software execution data
• Change data (e.g. from version
control system)
• Static code analysis data
• Software usage data
• Software related documents and
models
• Data from testing of software
Data attributes
• Hierarchies and dependencies
• Time and duration
• Object oriented metrics
• Version and change related
attributes
• Execution traces
• Text
• Similarity
• Etc.
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Studied aspects Structure Execution Evolution Management Development Requirements Optimization Rendering Other
Amount of studies 37 25 15 6 3 3 3 3 2
Data sources x studied aspects Structure Execution Evolution Management Development RE Optimization Rendering Other Total
Source code 33 6 11 5 0 1 0 2 0 46
Software execution data 7 22 1 0 0 0 2 1 1 28
Change / version data 5 1 10 3 2 0 1 0 1 17
Static code analysis data 8 5 2 1 0 0 2 0 0 15
Usage data 1 2 2 0 1 0 0 0 0 5
Documents and models 2 0 0 0 0 3 0 0 1 5
Test data 1 2 1 1 0 0 0 0 0 4
Other 2 1 1 0 0 0 0 0 0 4
Not relevant / Not stated clearly 4 0 3 2 1 0 0 2 0 9
Visualization formats x studied aspects Structure Execution Evolution Management Development Requirements Optimization Rendering Other Total
Hierarchical and Graph-Based Techniques 31 17 11 3 2 2 1 3 2 61
Geometric projection techniques 12 12 5 2 0 0 2 1 0 26
Timelines 1 9 5 3 3 0 1 0 0 18
Info graphics 7 6 4 3 1 0 1 0 0 17
Icon-based techniques 6 3 4 0 0 0 1 0 0 12
Text based visualizations 5 1 2 0 0 0 0 0 0 7
Tag- and word-clouds 2 0 3 1 0 0 0 1 0 5
Pixel-oriented techniques 1 3 0 0 0 0 0 0 0 4
Other 3 4 4 3 0 1 1 0 0 11
Not stated clearly in the article 1 0 0 0 0 0 0 0 0 1
Multiple views used x studied aspects Structure Execution Evolution Management Development RE Optimization Rendering Other Total
Used 16 14 12 5 2 0 2 0 0 43
Not used 21 11 3 1 1 3 1 3 3 40
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Maturity of SV research
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Conclusion
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

Questions?
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

THANK YOU!
Anna-Liisa Mattila, Petri Ihantola, Terhi Kilamo, Antti Luoto, Mikko Nurminen, Heli Väätäjä

This document summarizes findings from multiple studies on how working from home during the COVID-19 pandemic impacted software developer productivity and job satisfaction. The studies found that working from home generally provided more free time but also increased distractions, work interruptions, and communication friction. Developers experienced both increased focus time and family interruptions. Collaboration and team cohesion decreased while use of communication tools, commits, and merges increased. Impacts on performance were mixed, with some studies finding fewer bugs but others finding impactful work decreased. Developer satisfaction and well-being were influenced by both upsides like flexible hours and downsides like loneliness and ergonomic issues. Overall, the document uses the SPACE framework to categorize how working from home influenced

Towards a Theory of Developer Satisfaction and Productivity

Margaret-Anne Storey

Presentation of IEEE TSE Journal First paper at ICSE 2020 Abstract: Developer satisfaction and work productivity are important considerations for software companies. Enhanced developer satisfaction may improve the attraction, retention and health of employees, while higher productivity should reduce costs and increase customer satisfaction through faster software improvements. Many researchers and companies assume that perceived productivity and job satisfaction are related and may be used as proxies for one another, but these claims are a current topic of debate. There are also many social and technical factors that may impact satisfaction and productivity, but which factors have the most impact is not clear, especially for specific development contexts. Through our research, we developed a theory articulating a bidirectional relationship between software developer job satisfaction and perceived productivity, and identified what additional social and technical factors, challenges and work context variables influence this relationship. The constructs and relationships in our theory were derived in part from related literature in software engineering and knowledge work, and we validated and extended these concepts through a rigorously designed survey instrument. We instantiate our theory with a large software company, which suggests a number of propositions about the relative impact of various factors and challenges on developer satisfaction and perceived productivity. Our survey instrument and analysis approach can be applied to other development settings, while our findings lead to concrete recommendations for practitioners and researchers. Authors: Margaret-Anne Storey, Tom Zimmermann, Chris Bird, Jacek Czerwonka, Brendan Murphy and Eirini Kalliamvakou

Information Needs for Software Development Analytics

Ray Buse

This document summarizes the results of a survey conducted at Microsoft to understand the information needs for software development analytics. Some key findings include: - Managers rely more on data when making decisions, while developers rely more on their experience. - Respondents said the most important questions to answer relate to quality, dependencies, and defects. - Code-related artifacts like code complexity and test coverage were seen as most important to measure. - Commonly used and desired indicators included bugs, code churn, complexity, and test coverage. - Analytics could help with decisions around targeting testing, refactoring, and resource allocation.

The Medium of Visualization for Software Comprehension

Leonel Merino

Leonel Merino is defending his PhD thesis on the medium of visualization for software comprehension. The document reviews literature on software visualization and different visualization mediums like standard screens, wall displays, virtual reality, and augmented reality. It presents results from a survey of software visualization tools showing that the majority use standard screens and the medium has not been widely considered as a factor in effectiveness. The thesis argues that the medium is an important factor and different mediums may improve effectiveness, outlining experiments comparing 3D visualizations on standard screens versus augmented reality.

Msr14 tutorial 4upload

Walid Maalej

Toward supporting decision-making under uncertainty in digital humanities wit...

Technological Ecosystems for Enhancing Multiculturality

Visual Analytics in Omics - why, what, how?

Jan Aerts

This document discusses visual analytics in omics data. It begins by noting the shift from hypothesis-driven to data-driven research due to large datasets. Visual analytics can help explore these data by opening the "black box" of algorithms and enabling researchers to develop hypotheses. Effective visualization leverages human perception through techniques like preattentive vision and Gestalt laws. Challenges to visual analytics include scalability issues for large datasets and identifying interesting patterns for further analysis. Examples demonstrate data exploration, filtering, and user-guided analysis in genomic applications.

The document provides guidance on conducting empirical research for a PhD study. It discusses defining research questions, choosing appropriate research methods like interviews and surveys, collecting and analyzing data, and iterating on the research design. The speaker emphasizes starting with exploratory qualitative methods like interviews to understand phenomena before employing explanatory quantitative methods such as surveys to evaluate solutions. Examples are provided for combining methods through a multi-phase study.

Dagstuhl14 intro-v1

CS, NcState

From Raw Data to Deployed Product. Fast & Agile with CRISP-DM

Michał Łopuszyński

The document summarizes the Cross Industry Standard Process for Data Mining (CRISP-DM), which is the most popular methodology for data-centric projects. It walks through each step of the CRISP-DM process, including business understanding, data understanding, data preparation, modelling, evaluation, and deployment. For each step, it provides examples and highlights important dos and don'ts, such as thoroughly understanding the problem and data quality before modelling, automating repetitive data preparation tasks, and guarding against overfitting and data leakage during evaluation. The overall document serves as a guide to successfully applying the CRISP-DM process from raw data to deployed product.

Promise notes

CS, NcState

The document discusses issues with traditional software engineering and data mining research and proposes new directions for the field. It notes that simply predicting outcomes is no longer sufficient and that research should aim to develop controllers and management methods. It asks why there is so much focus on software engineering and data mining, and argues it is due to an information explosion in software projects. The document calls for research that addresses broader issues and questions in the field, such as understanding the impact of data mining tools and techniques. It also stresses the importance of industry relevance and addressing conclusion instability in research.

Agile Research in Information Systems Field: Analysis from Knowledge Transfor...

Ilia Bider

Presentation at the 8th IADIS International Conference on Information systems. Pre-proceedings available at: http://bit.ly/1QPEZS5 Due to the relative success of agile methods in software development, the idea of having agile processes started to be tested in other areas, for example, agile business process development. This trend already reached the research community and there have appeared some materials that suggest using agility in research projects. Analysis of these suggestions, however, shows that they do not go beyond finding superficial analogy between the concepts of the software development and research projects. The paper presents a deeper analysis of the concept of agile research in Information Systems (IS) based on the analysis of the research projects from the knowledge transformation perspective. As a basis for analysis, the SECI model of Nonaka is used. Based on this analysis, several suggestions are made on how to conduct agile research in IS, e.g. prioritize relevance over vigor, test early for a practical purpose, use own experience and reflections, etc. It is also shown that some research types, like action research and design science, are more suitable for conducting agile research than others. The paper also gives analysis of risks of non-agile research, and presents an example where they are revealed.

CRISP-DM - Agile Approach To Data Mining Projects

Michał Łopuszyński

This document summarizes Michał Łopuszyński's presentation on using an agile approach based on the CRISP-DM methodology for data mining projects. It discusses the key phases of CRISP-DM including business understanding, data understanding, data preparation, modelling, evaluation, and deployment. For each phase, it provides examples of best practices and challenges, with an emphasis on spending sufficient time on data understanding and preparation, developing models with the deployment context in mind, and carefully evaluating results against business objectives.

Quantitative Analysis of Infant’s Computer-supported Sketch and Design of Dra...

Mohd Syahmi

This study analyzed infants' computer-supported drawing behavior quantitatively and compared it to traditional paper and crayon drawing. Researchers conducted experiments where infants drew their favorite animals using different tools: paper and crayon, and drawing software with varying levels of features. The infants' drawing actions were recorded on video and analyzed using time and event sampling observation methods. The results showed that drawing software with small color palettes made color selection difficult for infants and limited creative stimulation. The study proposes that drawing software for infants should have large color palettes and easily movable coloring tools to reduce mental load and promote creativity.

Lecture 6 Teaching Computational Thinking 2016

Jason Zagami

This document discusses teaching computational thinking through technologies education. It emphasizes developing students' thinking skills like design thinking, computational thinking, systems thinking and futures thinking through project-based learning. The document outlines curriculum outcomes, contexts, challenges and expectations for developing solutions across different year levels. It also discusses integrating different models of thinking, evaluating solutions, and the importance of creativity, innovation and accepting failure in the learning process.

Lecture 2 Teaching Digital Technologies 2016

Jason Zagami

This document provides an overview of key concepts related to teaching digital technologies, including computational thinking, systems thinking, design thinking, and futures thinking. It discusses important problems in the world like global warming, armed conflicts, and overpopulation that could be addressed through computational thinking. The document also outlines key concepts for different year levels, including creating interactive games, databases, and computer systems. It provides examples of concepts like algorithms, binary search, and the travelling salesman problem.

[台灣人工智慧學校] 主題演講 - 張智威總經理 (President of HTC DeepQ)

台灣資料科學年會

The document discusses various topics related to artificial intelligence including: 1) It defines AI and machine learning, discusses the recent hype around AI, and some applications and requirements of AI systems. 2) It covers different types of neural networks including deep learning, recurrent neural networks, and how neural networks can be used for tasks like machine translation. 3) It discusses challenges in developing AI systems like acquiring large datasets, interpreting data to select the right machine learning model, building scalable infrastructure, and training skilled personnel.

User experience design portfolio, Harry Brenton

Harry Brenton

1) The document contains 5 case studies from the portfolio of Harry Brenton, a user experience designer. The case studies describe projects developing digital products for music annotation, medical education, stroke simulation, emergency medicine training, and dance visualization. 2) The first case study describes developing an interface called the "Social Timeline" to allow musicians to collaboratively annotate audio and video recordings. 3) The second case study involved creating a 3D anatomy tutorial using dynamic linking to demonstrate body systems and functions to medical students. 4) Another case study developed a virtual patient for stroke assessment training using speech, gestures and gaze as inputs for clinicians to diagnose the simulated patient.

應用行動科技紀錄與研究人們日常生活行為與脈絡

Stanley Chang

1) The document discusses trends in using mobile technologies to record and study people's daily behaviors and contexts. 2) It describes traditional survey and diary study methods and their limitations in capturing real-world behaviors. 3) Mobile sensing and experience sampling methods enabled by mobile devices can overcome these limitations by collecting data in situ. 4) Recent trends include combining mobile logging with diary studies, using wearable cameras for lifelogging, context-triggered experience sampling, and leveraging mobile data for anticipatory systems and behavior change interventions.

Software Quality Visualization

STX Next

Software development process, in-house or outsourced, might be a challenge. It is important to choose a vendor or hire a team of professionals who understand that quality of source code directly impacts the overall cost of your project. You most probably want to find a vendor who knows how to reveal all the risk hidden behind low quality code. Tricky part in revealing risk and possible quality issues is that you have to know how to do this at the time of development, not when it’s already too late. Author: Łukasz Koczwara - Software Development Manager @ STX Next

Perspectives on Software Visualization

Förderverein Technische Fakultät

Software visualization addresses the visual representation of software systems, their dynamic execution, and their development process. In this context, diagrams can help software developers, software architects, or researchers understand and analyze the system, to finally improve the software and development process. Those different roles, however, come along with different perspectives and requirements for visualization tools. In my talk, I will give recent examples from my own work how those diverging perspectives can be addressed: On the one hand, high-level visualizations showing complete software systems and their evolution might be leveraged by architects and researchers. On the other hand, small visualizations embedded in the code could support developers in their daily work extending and optimizing the code. Finally, I want to conclude by giving an outlook on future perspectives on software visualization.

Software Visualization 101+

Michele Lanza

This document provides an overview of software visualization. It discusses how visualization can facilitate understanding of software through the use of design, animation, interaction and graphics. It also discusses how people are visual beings and process information visually through iconic memory and short-term memory by recognizing visual patterns and attributes pre-attentively. Effective software visualization leverages how the human brain perceives and processes visual information.

Software Visualization - Promises & Perils

Michele Lanza

Visualization for Software Analytics

Margaret-Anne Storey

This document discusses visualization for software analytics and identifies three key trends: 1) developers moving from solo coders to social coders, 2) software development shifting from code-centric to data-centric, and 3) visualization becoming ubiquitous rather than standalone. It provides examples of visualizations for software design, code, dynamic behavior, architecture, and human activities. It discusses how visualization can provide insights, support tasks, and communicate knowledge. It also outlines opportunities and challenges for visual analytics and ubiquitous visualization in software engineering.

Software Evolution Visualization

Manoel Mendonca

This document discusses software evolution visualization (SEV). It begins by introducing software visualization and how information visualization techniques can be applied to software. SEV aims to facilitate software comprehension by visualizing how software systems evolve over time. The document reviews the state of the field, including common data sources, metrics, perspectives, strategies, and goals of SEV research. It also presents examples of SEV tools and discusses challenges in the area, such as evaluating SEV approaches. Finally, it outlines the goals of the author's own SEV research group, which are to help developers build InfoVis tools and help analysts use such tools for software maintenance.

Source code visualization (SourceViz)

Anas Bilal

The document outlines an agenda for a presentation on source code visualization. It discusses the problem of complex software systems being intangible and invisible. As a solution, it proposes visualizing source code elements and metrics to provide insight. It reviews related work using graphs, charts and cityscapes. It then introduces SourceViz, a tool that extracts metrics from Java source code and visualizes class relations, complexity and other metrics at the package, class and method level using various techniques. The conclusions state that visualization provides an efficient way to understand structure and interpret metrics. Future work includes evaluating and visualizing reusability, refactoring and re-engineering opportunities.

Software Visualization Today - Systematic Literature Review

Software Visualization Today - Systematic Literature Review

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Software Visualization Today - Systematic Literature Review