Interaction-aware development environments: recording, mining, and leveraging IDE interactions to analyze and support the development flow

Nowadays, software development is largely carried out using Integrated Development Environments, or IDEs. An IDE is a collection of tools and facilities to support the most diverse software engineering activities, such as writing code, debugging, and program understanding. The fact that they are integrated enables developers to find all the tools needed for the development in the same place. Each activity is composed of many basic events, such as clicking on a menu item in the IDE, opening a new user interface to browse the source code of a method, or adding a new statement in the body of a method. While working, developers generate thousands of these interactions, that we call fine-grained IDE interaction data. We believe this data is a valuable source of information that can be leveraged to enable better analyses and to offer novel support to developers. However, this data is largely neglected by modern IDEs. In this dissertation we propose the concept of "Interaction-Aware Development Environments": IDEs that collect, mine, and leverage the interactions of developers to support and simplify their workflow. We formulate our thesis as follows: Interaction-Aware Development Environments enable novel and in- depth analyses of the behavior of software developers and set the ground to provide developers with effective and actionable support for their activities inside the IDE. For example, by monitoring how developers navigate source code, the IDE could suggest the program entities that are potentially relevant for a particular task. Our research focuses on three main directions: 1. Modeling and Persisting Interaction Data. The first step to make IDEs aware of interaction data is to overcome its ephemeral nature. To do so we have to model this new source of data and to persist it, making it available for further use. 2. Interpreting Interaction Data. One of the biggest challenges of our research is making sense of the millions of interactions generated by developers. We propose several models to interpret this data, for example, by reconstructing high-level development activities from interaction histories or measure the navigation efficiency of developers. 3. Supporting Developers with Interaction Data. Novel IDEs can use the potential of interaction data to support software development. For example, they can identify the UI components that are potentially unnecessary for the future and suggest developers to close them, reducing the visual cluttering of the IDE

Augmenting IDEs with Runtime Information for Software Maintenance

Object-oriented language features such as inheritance, abstract types, late-binding, or polymorphism lead to distributed and scattered code, rendering a software system hard to understand and maintain. The integrated development environment (IDE), the primary tool used by developers to maintain software systems, usually purely operates on static source code and does not reveal dynamic relationships between distributed source artifacts, which makes it difficult for developers to understand and navigate software systems. Another shortcoming of today's IDEs is the large amount of information with which they typically overwhelm developers. Large software systems encompass several thousand source artifacts such as classes and methods. These static artifacts are presented by IDEs in views such as trees or source editors. To gain an understanding of a system, developers have to open many such views, which leads to a workspace cluttered with different windows or tabs. Navigating through the code or maintaining a working context is thus difficult for developers working on large software systems. In this dissertation we address the question how to augment IDEs with dynamic information to better navigate scattered code while at the same time not overwhelming developers with even more information in the IDE views. We claim that by first reducing the amount of information developers have to deal with, we are subsequently able to embed dynamic information in the familiar source perspectives of IDEs to better comprehend and navigate large software spaces. We propose means to reduce or mitigate the information by highlighting relevant source elements, by explicitly representing working context, and by automatically housekeeping the workspace in the IDE. We then improve navigation of scattered code by explicitly representing dynamic collaboration and software features in the static source perspectives of IDEs. We validate our claim by conducting empirical experiments with developers and by analyzing recorded development sessions

Code Park: A New 3D Code Visualization Tool

We introduce Code Park, a novel tool for visualizing codebases in a 3D game-like environment. Code Park aims to improve a programmer's understanding of an existing codebase in a manner that is both engaging and intuitive, appealing to novice users such as students. It achieves these goals by laying out the codebase in a 3D park-like environment. Each class in the codebase is represented as a 3D room-like structure. Constituent parts of the class (variable, member functions, etc.) are laid out on the walls, resembling a syntax-aware "wallpaper". The users can interact with the codebase using an overview, and a first-person viewer mode. We conducted two user studies to evaluate Code Park's usability and suitability for organizing an existing project. Our results indicate that Code Park is easy to get familiar with and significantly helps in code understanding compared to a traditional IDE. Further, the users unanimously believed that Code Park was a fun tool to work with.Comment: Accepted for publication in 2017 IEEE Working Conference on Software Visualization (VISSOFT 2017); Supplementary video: https://www.youtube.com/watch?v=LUiy1M9hUK

Programming tools for intelligent systems

Les outils de programmation sont des programmes informatiques qui aident les humains à programmer des ordinateurs. Les outils sont de toutes formes et tailles, par exemple les éditeurs, les compilateurs, les débogueurs et les profileurs. Chacun de ces outils facilite une tâche principale dans le flux de travail de programmation qui consomme des ressources cognitives lorsqu’il est effectué manuellement. Dans cette thèse, nous explorons plusieurs outils qui facilitent le processus de construction de systèmes intelligents et qui réduisent l’effort cognitif requis pour concevoir, développer, tester et déployer des systèmes logiciels intelligents. Tout d’abord, nous introduisons un environnement de développement intégré (EDI) pour la programmation d’applications Robot Operating System (ROS), appelé Hatchery (Chapter 2). Deuxièmement, nous décrivons Kotlin∇, un système de langage et de type pour la programmation différenciable, un paradigme émergent dans l’apprentissage automatique (Chapter 3). Troisièmement, nous proposons un nouvel algorithme pour tester automatiquement les programmes différenciables, en nous inspirant des techniques de tests contradictoires et métamorphiques (Chapter 4), et démontrons son efficacité empirique dans le cadre de la régression. Quatrièmement, nous explorons une infrastructure de conteneurs basée sur Docker, qui permet un déploiement reproductible des applications ROS sur la plateforme Duckietown (Chapter 5). Enfin, nous réfléchissons à l’état actuel des outils de programmation pour ces applications et spéculons à quoi pourrait ressembler la programmation de systèmes intelligents à l’avenir (Chapter 6).Programming tools are computer programs which help humans program computers. Tools come in all shapes and forms, from editors and compilers to debuggers and profilers. Each of these tools facilitates a core task in the programming workflow which consumes cognitive resources when performed manually. In this thesis, we explore several tools that facilitate the process of building intelligent systems, and which reduce the cognitive effort required to design, develop, test and deploy intelligent software systems. First, we introduce an integrated development environment (IDE) for programming Robot Operating System (ROS) applications, called Hatchery (Chapter 2). Second, we describe Kotlin∇, a language and type system for differentiable programming, an emerging paradigm in machine learning (Chapter 3). Third, we propose a new algorithm for automatically testing differentiable programs, drawing inspiration from techniques in adversarial and metamorphic testing (Chapter 4), and demonstrate its empirical efficiency in the regression setting. Fourth, we explore a container infrastructure based on Docker, which enables reproducible deployment of ROS applications on the Duckietown platform (Chapter 5). Finally, we reflect on the current state of programming tools for these applications and speculate what intelligent systems programming might look like in the future (Chapter 6)

Developers' Visuo-spatial Mental Model and Program Comprehension

Previous works from research and industry have proposed a spatial representation of code in a canvas, arguing that a navigational code space confers developers the freedom to organise elements according to their understanding. By allowing developers to translate logical relatedness into spatial proximity, this code representation could aid in code navigation and comprehension. However, the association between developers' code comprehension and their visuo-spatial mental model of the code is not yet well understood. This mental model is affected on the one hand by the spatial code representation and on the other by the visuo-spatial working memory of developers. We address this knowledge gap by conducting an online experiment with 20 developers following a between-subject design. The control group used a conventional tab-based code visualization, while the experimental group used a code canvas to complete three code comprehension tasks. Furthermore, we measure the participants' visuo-spatial working memory using a Corsi Block test at the end of the tasks. Our results suggest that, overall, neither the spatial representation of code nor the visuo-spatial working memory of developers has a significant impact on comprehension performance. However, we identified significant differences in the time dedicated to different comprehension activities such as navigation, annotation, and UI interactions.Comment: To appear in 2023 International Conference on Software Engineering (ICSE 2023). Authors' version of the wor

Source Code Interaction on Touchscreens

Direct interaction with touchscreens has become a primary way of using a device. This work seeks to devise interaction methods for editing textual source code on touch-enabled devices. With the advent of the “Post-PC Era”, touch-centric interaction has received considerable attention in both research and development. However, various limitations have impeded widespread adoption of programming environments on modern platforms. Previous attempts have mainly been successful by simplifying or constraining conventional programming but have only insufficiently supported source code written in mainstream programming languages. This work includes the design, development, and evaluation of techniques for editing, selecting, and creating source code on touchscreens. The results contribute to text editing and entry methods by taking the syntax and structure of programming languages into account while exploiting the advantages of gesture-driven control. Furthermore, this work presents the design and software architecture of a mobile development environment incorporating touch-enabled modules for typical software development tasks

Adaptive model-driven user interface development systems

Adaptive user interfaces (UIs) were introduced to address some of the usability problems that plague many software applications. Model-driven engineering formed the basis for most of the systems targeting the development of such UIs. An overview of these systems is presented and a set of criteria is established to evaluate the strengths and shortcomings of the state-of-the-art, which is categorized under architectures, techniques, and tools. A summary of the evaluation is presented in tables that visually illustrate the fulfillment of each criterion by each system. The evaluation identified several gaps in the existing art and highlighted the areas of promising improvement

Human-Centric Tools for Navigating Code

All software failures are fundamentally the fault of humansthe software\u27s design was flawed. The high cost of such failures ultimately results in developers having to design, implement, and test fixes, which all take considerable time and effort, and may result in more failures. As developers work on software maintenance tasks, they must navigate enormous codebases that may comprise millions of lines of code organized across thousands of modules. However, navigating code carries with it a plethora of problems for developers. In the hopes of addressing these navigation barriers, modern code editor and development environments provide a variety of features to aid in navigation; however, they are not without their limitations. Code navigations take many forms, and in this work I focus on three key types of code navigation in modern software development: navigating the working set, navigating among versions of code, and navigating the code structure. To address the challenges of navigating code, I designed three novel software development tools, one to enhance each type of navigation. First, I designed and implemented Patchworks, a code editor interface to support developers in navigating the working set. Patchworks aims to make these more efficient by providing a fixed grid of open code fragments that developers can quickly navigate. Second, I designed and implemented Yestercode, a code editor extension to support navigating among versions of code. Yestercode does so by providing a comparison view of the current code and a previous version of the same code. Third, I designed and implemented Wandercode, a code editor extension to enable developers to efficiently navigate the structure of their code. Wandercode aims to do so by providing a visualization of the code\u27s call graph overlayed on the code editor. My approach to designing these tools for more efficient code navigation was a human-centric onethat is, based on the needs of actual developers performing real software development tasks. Through user study evaluations, I found that these tools significantly improved developer productivity by reducing developers\u27 time spent navigating and mental effort during software maintenance tasks