Next generation software environments : principles, problems, and research directions

The past decade has seen a burgeoning of research and development in software environments. Conferences have been devoted to the topic of practical environments, journal papers produced, and commercial systems sold. Given all the activity, one might expect a great deal of consensus on issues, approaches, and techniques. This is not the case, however. Indeed, the term "environment" is still used in a variety of conflicting ways. Nevertheless substantial progress has been made and we are at least nearing consensus on many critical issues.The purpose of this paper is to characterize environments, describe several important principles that have emerged in the last decade or so, note current open problems, and describe some approaches to these problems, with particular emphasis on the activities of one large-scale research program, the Arcadia project. Consideration is also given to two related topics: empirical evaluation and technology transition. That is, how can environments and their constituents be evaluated, and how can new developments be moved effectively into the production sector

Data collection procedures for the Software Engineering Laboratory (SEL) database

This document is a guidebook to collecting software engineering data on software development and maintenance efforts, as practiced in the Software Engineering Laboratory (SEL). It supersedes the document entitled Data Collection Procedures for the Rehosted SEL Database, number SEL-87-008 in the SEL series, which was published in October 1987. It presents procedures to be followed on software development and maintenance projects in the Flight Dynamics Division (FDD) of Goddard Space Flight Center (GSFC) for collecting data in support of SEL software engineering research activities. These procedures include detailed instructions for the completion and submission of SEL data collection forms

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Enterprise Architecture Specification Case Study

A graduate course in enterprise architecture had a team project component in which a real-world business case, provided by an industry sponsor, formed the basis of the project charter and the architecture statement of work. The paper aims to share the team project experience on developing the architecture specifications based on the business case of an accountable health care organization. Students collaborated as a team in various roles to develop the architecture specifications for a new business initiative of the sponsoring organization, XYZ ACO. The teaching case describes the case study approach and the architecture approach adopted for the architecture process, and is accompanied by Teaching Case Notes which provide a selection of the models developed by members of the project team towards the architecture specifications. The course started with coverage of enterprise architecture theory, best practices and standards, and the team project gave students the opportunity to apply their theoretical knowledge and “learn by doing”. Students were challenged to interpret the business case, the project charter and project requirements, and each team member was allocated an architecture viewpoint and a role to play. The Teaching Case presents a summary of the team project and the lessons learned in performing the project

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

An Agent-Based System with Personalization and Intelligent Assistance Services for Facilitating Knowledge Sharing

The scenario of distributed knowledge in organization, lack of understanding of knowledge sharing benefits and technology inadequacies are the main barriers to knowledge sharing facilitation. A more user-centered application through personalization and intelligent assistance technique are identified as the evolution in knowledge sharing facilitation research. As response to these challenges, this study is dedicated to approach knowledge sharing facilitation with an agent-based system. Agent technology is a promising solution to knowledge sharing facilitation. Agent technology could provide personalization and intelligent assistance to give a more human-centered approach towards users in knowledge sharing participation. This thesis focuses on automatic interest identification and knowledge member recommendation in order to reduce user’s tasks and ease them to participate in knowledge sharing. The proposed agent based system is called KSFaci (Knowledge Sharing Facilitator). KSFaci provides personalization and intelligent assistance to users by offering knowledge member recommendation according to their interest preferences. This timely action gives users resources to find help and they can interact with each other to share or exchange knowledge. The first agent, Profiler is able to monitor user navigational behavior and build user profile on behalf of the user. The Recommender agent then determines the user’s most preferred interest and matches them against other users sharing similar interest. The main algorithms used are profile determination and user similarity. The recommendation services provided reduce users burden from manual browsing and searching for knowledge reference resources. KSFaci is embedded in web environment and is implemented using Java Servlet and runs under Apache server. The performance of KSFaci is evaluated using a four-factor evaluation metrics covering the user profile preciseness, recommendation service, staff directory and document repository. Several techniques have been used including weighted respond analysis, two-point scale, Likert-scale survey analysis and overlap analysis. User satisfaction result indicate that the agent-based approach used; by identifying user’s interests and establishing knowledge network based on interests of its users is capable in facilitating knowledge sharing. In conclusion, the recommended knowledge network created based on the automatic interest identification has now become medium for users to refer for knowledge sources and later perform knowledge sharing tasks