Roberto Minelli

Software Analytics for Mobile Applications--Insights a Lessons Learned

Mobile applications, known as apps, are software systems running on handheld devices, such as smartphones and tablet PCs. The market of apps has rapidly expanded in the past few years into a multi-billion dollar business. Being a new phenomenon, it is unclear whether approaches to maintain and comprehend traditional software systems can be ported to the context of apps. We present a novel approach to comprehend apps from a structural and historical perspective, leveraging three factors for the analysis: source code, usage of third-party APIs, and historical data. We implemented our approach in a web-based software analytics platform named SAMOA. We detail our approach and the supporting tool, and present a number of findings obtained while investigating a corpus of mobile applications. Our findings reveal that apps differ significantly from traditional software systems in a number of ways, which calls for the development of novel approaches to maintain and comprehend them.

I know what you did last summer: an investigation of how developers spend their time

Developing software is a complex mental activity, requiring extensive technical knowledge and abstraction capabilities. The tangible part of development is the use of tools to read, inspect, edit, and manipulate source code, usually through an IDE (integrated development environment). Common claims about software development include that program comprehension takes up half of the time of a developer, or that certain UI (user interface) paradigms of IDEs offer insufficient support to developers. Such claims are often based on anecdotal evidence, throwing up the question of whether they can be corroborated on more solid grounds. We present an in-depth analysis of how developers spend their time, based on a fine-grained IDE interaction dataset consisting of ca. 740 development sessions by 18 developers, amounting to 200 hours of development time and 5 million of IDE events. We propose an inference model of development activities to precisely measure the time spent in editing, navigating and searching for artifacts, interacting with the UI of the IDE, and performing corollary activities, such as inspection and debugging. We report several interesting findings which in part confirm and reinforce some common claims, but also disconfirm other beliefs about software development.

Visualizing Developer Interactions

Integrated Development Environments (IDEs) have become the de facto standard vehicle to develop software systems. The user interface (UI) of an IDE offers a staggering amount of facilities to manipulate source code, such as inspectors, debuggers, recommenders, alternative viewers, etc. It is unclear how developers use the UI of an IDE and whether such UIs actually give appropriate support to the developers. We present a visual approach to understand and characterize development sessions from the UI perspective. The tool supporting our approach mines and processes the finest-grained UI-level events making up development sessions and presents them visually. We have collected, visualized, and analyzed hundreds of development sessions and report on our findings.

Visualizing the workflow of developers

Developers use the Integrated Development Environment (IDE) to develop a system at hand, by reading, understanding, and writing its source code. They do so by exploiting the tools and facilities provided by the IDE. This also allows them to build a mental model of the system to perform informed changes. It is however not clear how and when developers use which facility and tool, and to what extent the current services offered by the IDE appropriately support the navigation. We present an approach to visualize the activities of developers within the IDE, implemented in a tool: DFLow. DFLOW records all IDE interactions that occur during a development session and visualizes them through a web-based visualization platform.

SAMOA -- A Visual Software Analytics Platform for Mobile Applications

Mobile applications, also known as apps, are dedicated software systems that run on handheld devices, such as smartphones and tablet computers. The apps business has in a few years turned into a multi-billion dollar market. From a software engineering perspective apps represent a new phenomenon, and there is a need for tools and techniques to analyze apps. We present SAMOA, a visual web-based software analytics platform for mobile applications. It mines software repositories of apps and uses a set of visualization techniques to present the mined data. We describe SAMOA, detail the analyses it supports, and describe a methodology to understand apps from a structural and historical perspective. The website of SAMOA, containing the screen cast of the tool demo, is located at http://samoa.inf.usi.ch/about.

Taming the IDE with fine-grained interaction data

Integrated Development Environments (IDEs) lack effective support to browse complex relationships between source code elements. As a result, developers are often forced to exploit multiple user interface components at the same time, bringing the IDE into a complex, “chaotic” state. Keeping track of these relationships demands increased source code navigation and cognitive load, leading to productivity deficits documented in observational studies. Beyond small-scale studies, the amount and nature of the chaos experienced by developers in the wild is unclear, and more importantly it is unclear how to tame it. Based on a dataset of fine-grained interaction data, we propose several metrics to characterize and quantify the “level of chaos” of an IDE. Our results suggest that developers spend, on average, more than 30% of their time in a chaotic environment, and that this may affect their productivity. To support developers, we devise and evaluate simple strategies that automatically alter the UI of the IDE. We find that even simple strategies may considerably reduce the level of chaos both in terms of effective space occupancy and time spent in a chaotic environment.

Visual Storytelling of Development Sessions

Most development activities, like program understanding, source code navigation and editing, are supported by Integrated Development Environments (IDEs). They provide different tools and user interfaces (UI) to interact with the source code, such as browsers, debuggers, and inspectors. It is uncertain how and when programmers use different UI elements of an IDE and to what extent they appropriately support development. Previously we developed DFLOW, a tool that seamlessly records and processes interaction data. Our long-term goal is to assess to what extent the UIs of IDEs support the workflow of developers and whether they can be improved. As a first step we present our approach to analyze development sessions in the form of visual storytelling. We illustrate our initial catalogue of visualizations through two development stories.

Blended, not stirred: Multi-concern visualization of large software systems

While constructing and evolving software systems, developers generate directly and indirectly a large amount of data of diverse nature, such as source code changes, bug tracking information, IDE interactions, stack traces, etc. Often these diverse data sources are processed and visualized in isolation, leading to a partial view of systems. We present a blended approach to visualize several data “ingredients” at once, to give as complete an answer as possible to the question “What happened to the system in the last few days?”. The goal is to enable a quick and comprehensive assessment of what happened to a software system in any given time frame.

SODA: the stack overflow dataset almanac

Stack Overflow has become a fundamental resource for developers, becoming the de facto Question and Answer (Q&A) website, and one of the standard unstructured data sources for software engineering research to mine knowledge about development. We present SODA, the Stack Overflow Dataset Almanac, a tool that helps researchers and developers to better understand the trends of discussion topics in Stack Overflow, based on the available tagging system. SODA provides an effective visualization to support the analysis of topics in different time intervals and frames, leveraging single or co-occurrent tags. We show, through simple usage scenarios, how SODA can be used to find interesting peculiar moments in the evolution of Stack Overflow discussions that closely match specific recent events in the area of software development. SODA is available at http://rio.inf.usi.ch/soda/.

Measuring Navigation Efficiency in the IDE

While coding, developers construct and maintain mental models of software systems to support the task at hand. Although source code is the main product of software development, the process involves navigating and inspecting entities beyond the ones that are edited by the end of a task. Developers use various user interfaces (UI) offered by the Integrated Development Environment (IDE) to navigate the complex, and often hidden, relationships between program entities. These UIs impose fixed navigation costs, in terms of the number of interactions that a developer is required to perform to reach an entity of interest. It is unclear to what extent the actual navigation effort differs from an ideal setting, and if there is any room for actual improvement. We present a preliminary empirical study, where we analyzed a corpus of IDE interaction data coming from 6 developers totaling more than 20 days of development activity. To measure the navigation efficiency, we compute a combination of different ideal settings and compare them against the observed navigation events. Our findings reveal that, on average, developers perform 1.5 to 19 times more navigation events than the ideal case. While different factors make the ideal setting unfeasible, we believe that this calls for novel approaches to support the navigation in integrated development environments.