How Lisp systems look different

Many reverse engineering approaches have been developed to analyze software systems written in different languages like C/C++ or Java. These approaches typically rely on a meta-model, that is either specific for the language at hand or language independent (e.g. UML). However, one language that was hardly addressed is Lisp. While at first sight it can be accommodated by current language independent meta-models, Lisp has some unique features (e.g. macros, CLOS entities) that are crucial for reverse engineering Lisp systems. In this paper we propose a suite of new visualizations that reveal the special traits of the Lisp language and thus help in understanding complex Lisp systems. To validate our approach we apply them on several large Lisp case studies, and summarize our experience in terms of a series of recurring visual patterns that we have detected.

Workshop on FAMIX and Moose in Software Reengineering (FAMOOSr 2008)

The increasing amount of data available about software systems poses new challenges for re- and reverse engineering research, as the proposed approaches need to scale. In this context, concerns about meta-modeling and analysis techniques need to be augmented by technical concerns about how to reuse and how to build upon the efforts of previous research. Moose is an extensive infrastructure for reverse engineering evolved for over 10 years that promotes the reuse of engineering efforts in research. Moose accommodates various types of data modeled in the FAMIX family of meta-models. The goal of this half-day workshop is to strengthen the community of researchers and practitioners who are working in re- and reverse engineering, by providing a forum for building future research starting from Moose and FAMIX as shared infrastructure.

Test Blueprints - Exposing Side Effects in Execution Traces to Support Writing Unit Tests

Writing unit tests for legacy systems is a key maintenance task. When writing tests for object-oriented programs, objects need to be set up and the expected effects of executing the unit under test need to be verified. If developers lack internal knowledge of a system, the task of writing tests is non-trivial. To address this problem, we propose an approach that exposes side effects detected in example runs of the system and uses these side effects to guide the developer when writing tests. We introduce a visualization called Test Blueprint, through which we identify what the required fixture is and what assertions are needed to verify the correct behavior of a unit under test. The dynamic analysis technique that underlies our approach is based on both tracing method executions and on tracking the flow of objects at runtime. To demonstrate the usefulness of our approach we present results from two case studies.

Query Technologies and Applications for Program Comprehension

Industrial software systems are large and complex, both in terms of the software entities and their relationships. Consequently, understanding how a software system works requires the ability to pose queries over the design-level entities of the system. Traditionally, this task has been supported by simple tools (e.g., grep) combined with the programmer's intuition and experience. Recently, however, specialized code query technologies have matured to the point where they can be used in industrial situations, providing more intelligent, timely, and efficient responses to developer queries. This working session aims to explore the state of the art in code query technologies, and discover new ways in which these technologies may be useful in program comprehension. The session brings together researchers and practitioners. We survey existing techniques and applications, trying to understand the strengths and weaknesses of the various approaches, and sketch out new frontiers that hold promise.

Workshop on FAMIX and Moose in Software Reengineering (FAMOOSr 2009)

The increasing amount of data available about software systems poses new challenges for re- and reverse engineering research, as the proposed approaches need to scale. In this context, concerns about meta-modeling and analysis techniques need to be augmented by technical concerns about how to reuse and how to build upon the efforts of previous research. MOOSE is an extensive infrastructure for reverse engineering evolved for over 10 years that promotes the reuse of engineering efforts in research. MOOSE accommodates various types of data modeled in the FAMIX family of meta-models. The goal of this half-day workshop is to strengthen the community of researchers and practitioners who are working in re- and reverse engineering, by providing a forum for building future research starting from MOOSE and FAMIX as shared infrastructure.

Exploiting Runtime Information in the IDE

Developers rely on the mechanisms provided by their IDE to browse and navigate a large software system. These mechanisms are usually based purely on a system's static source code. The static perspective, however, is not enough to understand an object-oriented program's behavior, in particular if implemented in a dynamic language. We propose to enhance IDEs with a program's runtime information (eg. message sends and type information) to support program comprehension through precise navigation and informative browsing. To precisely specify the type and amount of runtime data to gather about a system under development, dynamically and on demand, we adopt a technique known as partial behavioral reflection. We implemented navigation and browsing enhancements to an IDE that exploit this runtime information in a prototype called Hermion. We present preliminary validation of our experimental enhanced IDE by asking developers to assess its usefulness to understand an unfamiliar software system.

Automatic Labeling of Software Components and their Evolution using Log-Likelihood Ratio of Word Frequencies in Source Code

As more and more open-source software components become available on the internet we need automatic ways to label and compare them. For example, a developer who searches for reusable software must be able to quickly gain an understanding of retrieved components. This understanding cannot be gained at the level of source code due to the semantic gap between source code and the domain model. In this paper we present a lexical approach that uses the log-likelihood ratios of word frequencies to automatically provide labels for software components. We present a prototype implementation of our labeling/comparison algorithm and provide examples of its application. In particular, we apply the approach to detect trends in the evolution of a software system.

Assigning Bug Reports using a Vocabulary-Based Expertise Model of Developers

For popular software systems, the number of daily submitted bug reports is high. Triaging these incoming reports is a time consuming task. Part of the bug triage is the assignment of a report to a developer with the appropriate expertise. In this paper, we present an approach to automatically suggest developers who have the appropriate expertise for handling a bug report. We model developer expertise using the vocabulary found in their source code contributions and compare this vocabulary to the vocabulary of bug reports. We evaluate our approach by comparing the suggested experts to the persons who eventually worked on the bug. Using eight years of Eclipse development as a case study, we achieve 33.6\% top-1 precision and 71.0\% top-10 recall.

Consistent Layout for Thematic Software Maps

Software visualizations can provide a concise overview of a complex software system. Unfortunately, since software has no physical shape, there is no “natural“ mapping of software to a two-dimensional space. As a consequence most visualizations tend to use a layout in which position and distance have no meaning, and consequently layout typical diverges from one visualization to another. We propose a consistent layout for software maps in which the position of a software artifact reflects its \emph{vocabulary}, and distance corresponds to similarity of vocabulary. We use Latent Semantic Indexing (LSI) to map software artifacts to a vector space, and then use Multidimensional Scaling (MDS) to map this vector space down to two dimensions. The resulting consistent layout allows us to develop a variety of thematic software maps that express very different aspects of software while making it easy to compare them. The approach is especially suitable for comparing views of evolving software, since the vocabulary of software artifacts tends to be stable over time.

Supporting Task-oriented Navigation in IDEs with Configurable HeatMaps

Mainstream IDEs generally rely on the static structure of a software project to support browsing and navigation. We propose HeatMaps, a simple but highly configurable technique to enrich the way an IDE displays the static structure of a software system with additional kinds of information. A heatmap highlights software artifacts according to various metric values, such as bright red or pale blue, to indicate their potential degree of interest. We present a prototype system that implements heatmaps, and we describe an initial study that assesses the degree to which different heatmaps effectively guide developers in navigating software.

Augmenting Static Source Views in IDEs with Dynamic Metrics

Mainstream IDEs such as Eclipse support developers in managing software projects mainly by offering static views of the source code. Such a static perspective neglects any information about runtime behavior. However, object-oriented programs heavily rely on polymorphism and late-binding, which makes them difficult to understand just based on their static structure. Developers thus resort to debuggers or profilers to study the system's dynamics. However, the information provided by these tools is volatile and hence cannot be exploited to ease the navigation of the source space. In this paper we present an approach to augment the static source perspective with dynamic metrics such as precise runtime type information, or memory and object allocation statistics. Dynamic metrics can leverage the understanding for the behavior and structure of a system. We rely on dynamic data gathering based on aspects to analyze running Java systems. By solving concrete use cases we illustrate how dynamic metrics directly available in the IDE are useful. We also comprehensively report on the efficiency of our approach to gather dynamic metrics.