77 resultados para Software systems
Resumo:
Understanding large software systems is a challenging task, and to support it many approaches have been developed. Often, the result of these approaches categorize existing entities into new groups or associates them with mutually exclusive properties. In this paper we present the Distribution Map as a generic technique to visualize and analyze this type of result. Our technique is based on the notion of focus, which shows whether a property is well-encapsulated or cross-cutting, and the notion of spread, which shows whether the property is present in several parts of the system. We present a basic visualization and complement it with measurements that quantify focus and spread. To validate our technique we show evidence of applying it on the result sets of different analysis approaches. As a conclusion we propose that the Distribution Map technique should belong to any reverse engineering toolkit.
Resumo:
Successful software systems cope with complexity by organizing classes into packages. However, a particular organization may be neither straightforward nor obvious for a given developer. As a consequence, classes can be misplaced, leading to duplicated code and ripple effects with minor changes effecting multiple packages. We claim that contextual information is the key to rearchitecture a system. Exploiting contextual information, we propose a technique to detect misplaced classes by analyzing how client packages access the classes of a given provider package. We define locality as a measure of the degree to which classes reused by common clients appear in the same package. We then use locality to guide a simulated annealing algorithm to obtain optimal placements of classes in packages. The result is the identification of classes that are candidates for relocation. We apply the technique to three applications and validate the usefulness of our approach via developer interviews.
Resumo:
Much of the knowledge about software systems is implicit, and therefore difficult to recover by purely automated techniques. Architectural layers and the externally visible features of software systems are two examples of information that can be difficult to detect from source code alone, and that would benefit from additional human knowledge. Typical approaches to reasoning about data involve encoding an explicit meta-model and expressing analyses at that level. Due to its informal nature, however, human knowledge can be difficult to characterize up-front and integrate into such a meta-model. We propose a generic, annotation-based approach to capture such knowledge during the reverse engineering process. Annotation types can be iteratively defined, refined and transformed, without requiring a fixed meta-model to be defined in advance. We show how our approach supports reverse engineering by implementing it in a tool called Metanool and by applying it to (i) analyzing architectural layering, (ii) tracking reengineering tasks, (iii) detecting design flaws, and (iv) analyzing features.
Resumo:
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.
Resumo:
Enterprise Applications are complex software systems that manipulate much persistent data and interact with the user through a vast and complex user interface. In particular applications written for the Java 2 Platform, Enterprise Edition (J2EE) are composed using various technologies such as Enterprise Java Beans (EJB) or Java Server Pages (JSP) that in turn rely on languages other than Java, such as XML or SQL. In this heterogeneous context applying existing reverse engineering and quality assurance techniques developed for object-oriented systems is not enough. Because those techniques have been created to measure quality or provide information about one aspect of J2EE applications, they cannot properly measure the quality of the entire system. We intend to devise techniques and metrics to measure quality in J2EE applications considering all their aspects and to aid their evolution. Using software visualization we also intend to inspect to structure of J2EE applications and all other aspects that can be investigate through this technique. In order to do that we also need to create a unified meta-model including all elements composing a J2EE application.
Resumo:
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.
Resumo:
Navigating large software systems is difficult as the various artifacts are distributed in a huge space, while the relationships between different artifacts often remain hidden and obscure. As a consequence, developers using a modern interactive development environment (IDE) are forced to open views on numerous source artifacts to reveal these hidden relationships, leading to a crowded workspace with many opened windows or tabs. Developers often lose the overview in such a cluttered workspace as IDEs provide little support to get rid of unused windows. AutumnLeaves automatically selects windows unlikely for future use to be closed or grayed out while important ones are displayed more prominently. This reduces the number of windows opened at a time and adds structure to the developer's workspace. We validate AutumnLeaves with a benchmark evaluation using recorded navigation data of various developers to determine the prediction quality of the employed algorithms.
Resumo:
Moose is a powerful reverse engineering platform, but its facilities and means to analyze software are separated from the tools developers typically use to develop and maintain their software systems: development environments such as Eclipse, VisualWorks, or Squeak. In practice, this requires developers to work with two distinct environments, one to actually develop the software, and another one (e.g., Moose) to analyze it. We worked on several different techniques, using both dynamic and static analyzes to provide software analysis capabilities to developers directly in the IDE. The immediate availability of analysis tools in an IDE significantly increases the likelihood that developers integrate software analysis in their daily work, as we discovered by conducting user studies with developers. Finally, we identified several important aspect of integrating software analysis in IDEs that need to be addressed in the future to increase the adoption of these techniques by developers.
Resumo:
In addition to multi-national Grid infrastructures, several countries operate their own national Grid infrastructures to support science and industry within national borders. These infrastructures have the benefit of better satisfying the needs of local, regional and national user communities. Although Switzerland has strong research groups in several fields of distributed computing, only recently a national Grid effort was kick-started to integrate a truly heterogeneous set of resource providers, middleware pools, and users. In the following. article we discuss our efforts to start Grid activities at a national scale to combine several scientific communities and geographical domains. We make a strong case for the need of standards that have to be built on top of existing software systems in order to provide support for a heterogeneous Grid infrastruc
Resumo:
The debugger is an essential tool in any programming environment, as it helps developers understand the dynamic behaviour of software systems. However, traditional debuggers fail in answering domain-specific questions, as the semantics of what they show and do are fixed. In this paper we introduce our work towards a moldable debugger which, unlike traditional debuggers, both adapts itself and can be adapted to a particular debugging context. Thus, it allows developers to answer their questions by using concepts from their own application domains.
Resumo:
Highly available software systems occasionally need to be updated while avoiding downtime. Dynamic software updates reduce down-time, but still require the system to reach a quiescent state in which a global update can be performed. This can be difficult for multi-threaded systems. We present a novel approach to dynamic updates using first-class contexts, called Theseus. First-class contexts make global updates unnecessary: existing threads run to termination in an old context, while new threads start in a new, updated context; consistency between contexts is ensured with the help of bidirectional transformations. We show that for multi-threaded systems with coherent memory, first-class contexts offer a practical and flexible approach to dynamic updates, with acceptable overhead.
Resumo:
In order to analyze software systems, it is necessary to model them. Static software models are commonly imported by parsing source code and related data. Unfortunately, building custom parsers for most programming languages is a non-trivial endeavour. This poses a major bottleneck for analyzing software systems programmed in languages for which importers do not already exist. Luckily, initial software models do not require detailed parsers, so it is possible to start analysis with a coarse-grained importer, which is then gradually refined. In this paper we propose an approach to "agile modeling" that exploits island grammars to extract initial coarse-grained models, parser combinators to enable gradual refinement of model importers, and various heuristics to recognize language structure, keywords and other language artifacts.
Resumo:
Debuggers are crucial tools for developing object-oriented software systems as they give developers direct access to the running systems. Nevertheless, traditional debuggers rely on generic mechanisms to explore and exhibit the execution stack and system state, while developers reason about and formulate domain-specific questions using concepts and abstractions from their application domains. This creates an abstraction gap between the debugging needs and the debugging support leading to an inefficient and error-prone debugging effort. To reduce this gap, we propose a framework for developing domain-specific debuggers called the Moldable Debugger. The Moldable Debugger is adapted to a domain by creating and combining domain-specific debugging operations with domain-specific debugging views, and adapts itself to a domain by selecting, at run time, appropriate debugging operations and views. We motivate the need for domain-specific debugging, identify a set of key requirements and show how our approach improves debugging by adapting the debugger to several domains.
Resumo:
Software developers often ask questions about software systems and software ecosystems that entail exploration and navigation, such as who uses this component?, and where is this feature implemented?. Software visualisation can be a great aid to understanding and exploring the answers to such questions, but visualisations require expertise to implement effectively, and they do not always scale well to large systems. We propose to automatically generate software visualisations based on software models derived from open source software corpora and from an analysis of the properties of typical developers queries and commonly used visualisations. The key challenges we see are (1) understanding how to match queries to suitable visualisations, and (2) scaling visualisations effectively to very large software systems and corpora. In the paper we motivate the idea of automatic software visualisation, we enumerate the challenges and our proposals to address them, and we describe some very initial results in our attempts to develop scalable visualisations of open source software corpora.