Open source communities typically use a software repository to archive various software projects with their source code, mailing list discussions, documentation, bug reports, and so forth. For example, SourceForge currently hosts over seventy thousand open source software systems. Because of the size of the rich information content, such repositories offer numerous opportunities for sharing information among projects. For example, one would like to know a set of projects that are related or similar to each other, so that the project groups can collaborate and share their work. With thousands of projects in typical repositories, however, manually locating related projects can be difficult. Hence, we propose MUDABlue, a tool that automatically categorizes software systems. MUDABlue has three major aspects: 1) it relies on no other information than the source code, 2) it determines category sets automatically, and 3) it allows a software system to be a member of multiple categories. MUDABlue has a Web interface to visualize determined categories, which eases browsing a software repository. We show the effectiveness of MUDABlue's categorization capability by comparing its generated categories with that of some other existing research tools.

The success of several Open Source™ software systems, e.g., Apache, Bind, Emacs, and Linux, has recently sparked interest in studying and emulating the software engineering principles underlying this innovative development and use model. Certain aspects of the Open Source development method, e.g., community building, open discussions for requirements and features, and evolvable and modular designs are having fundamental and far reaching consequences on general software engineering practices.To leverage such Open Source methods and tools, we have defined an innovative software engineering paradigm for large corporations: Progressive Open Source (POS). POS leverages the power of Open Source methods and tools for large corporations in a progressive manner: starting from completely within the corporation, to include partner businesses, and eventually complete Open Source. In this paper we present the design goals and principles for POS. We illustrate POS with two programs in HP: Corporate Source and the Collaborative Development Program (CDP). We present early results from both these programs suggesting the power and necessity of POS for all modern large corporations.

The increasing complexity of enterprise applications, the expanding number of networked machines, and the rapid deployment of Internet-based business applications (E-commerce), emphasize the importance and value of application management. One of the main problems in current application management products is the amount of time and effort needed to install and customize them. Application auto-discovery is a key technology for solving this problem. In this paper, we present a generic approach to application auto-discovery along with some examples. Our approach is to create a model-based discovery engine that is driven by an application template model. While the application template model captures the variation from one application to another, the auto-discovery engine uses sophisticated mechanisms such as scoping to execute an invariant auto-discovery process.

The downstream activities of large scale software systems life-cycle require team effort of several people over extended time periods. Current computing environments, exemplified by Unix, provide limited support for such team activities. Matisse is a knowledge-based team programming environment that addresses this issue. Matisse models source code, associated documents, people, and tasks as objects in an information system. Relationships between these objects provide associative information retrieval and navigational support; rules defined on object attributes facilitate team coordination and configuration management. We describe the design, implementation, and experimental use of Matisse. Matisse represents a novel information management architecture for team programming: It uses database technology for team information management and expert system technology for individual information management; some experimental data on accesses from the individual to the team information space is presented. Three hard scenarios: semiautomatic design history maintenance, dynamic object composition, and adaptive use of existing software, illustrate the power of Matisse, with respect to team programming, over traditional programming environments.

Article Process programming by hindsight Share on Authors: Pankaj K. Garg View Profile , Sanjay Bhansali View Profile Authors Info & Claims ICSE '92: Proceedings of the 14th international conference on Software engineeringJune 1992 Pages 280–293https://doi.org/10.1145/143062.143128Online:01 June 1992Publication History 6citation263DownloadsMetricsTotal Citations6Total Downloads263Last 12 Months2Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access