Automating output size and reuse metrics in a repository-based computer-aided software engineering (CASE) environment

Abstract

AUTOMATING OUTPUT SIZE AND SOFTWARE REUSE METRICS IN A REPOSITORY-BASED COMPUTER AIDED SOFTWARE ENGINEERING (CASE) ENVIRONMENT ABSTRACTMeasurement of software development productivity is needed in order to control software costs, but it is discouragingly labor-intensive and expensive. Computer aided software engineering (CASE) technologies --especially repository-based, integrated CASE --have the potential to support the automation of this measurement. In this paper, we discuss the development of automated analyzers for function point and software reuse measurement for object-based CASE. Both analyzers take advantage of the existence of a representation of the application system that is stored within an object repository, and that contains the necessary information about the application system. We also discuss metrics for software reuse measurement, including reuse leverage, reuse value and reuse classifcation, that are motivated by managerial requirements and the efforts, within industry and the IEEE, to standardize measurement. The functionality and the analytical capabilities of state-of-the-art automated software metrics analyzers are illustrated in the context of an investment banking industry application, that is similar to systems deployed at the New York City-based investment bank where these tools were developed and tested.

On XML Based Automated Function Point Analysis: An Effective Method to Assess Developer Productivity

“…Some studies were focused on evolving the process of function point analysis [1], [6]- [16]while other studies focused on automation of all or some of the processes involved in FPA [5], [17]- [19]. The articles, which were attempting to extend and evolve FPA generally, structured their research to compare one or more aspects of the new process they were developing against the previously established best practices for performing FPA.…”

“…Unfortunately function point analysis also carries with it several distinct disadvantages: the requirement of certified function point specialists in order to achieve accurate, reliable counts; they are time-consuming and expensive; automation of function point analysis has been poorly studied and is, therefore, of unknown accuracy; and the process is unreliable for software that is smaller than 15 function points in size [4]. These drawbacks have led to slow adoption of function point analysis [5].…”

Estimating the Effort of Mobile Application Development

“…Its characteristics are: better defines the complexity adjustment factor and also adds to its count the percentage of reused code [20].…”

The Impact of Sentiment-driven Feedback on Knowledge Reuse in Online Communities

“…One of the settings in which knowledge reuse has been often derived from observable data is software development. Specifically, code reuse in software development, as the name implies, refers to employing previously written code (i.e., objects) as an alternative to writing new (possibly identical) code to perform the same or similar function (Banker, Kauffman, Wright, & Zweig, 1994). Code reuse has been previously measured in terms of the reuse leverage metric.…”

“…Code reuse has been previously measured in terms of the reuse leverage metric. Concretely, the reuse leverage in an application refers to the total number of objects used divided by the number of new objects built (Banker, Kauffman, & Zweig, 1992). For example, if a software application comprises 400 objects (i.e., used objects) of which 100 had to be programmed from scratch (i.e., new objects), the reuse leverage would be 4.0.…”