This paper makes the business case for automating the collection ofsoftware metrics for gauging development performance in integratedcomputer aided software engineering (CASE) environments that arecharacterized by an object-oriented development methodology and acentralized repository. The automation of function point analysisis discussed in the context of such an integrated CASE environment(ICE). We also discuss new metrics that describe three differentdimensions of code reuse -- leverage, value and classification --and examine the p,ossibility of utilizing objects as means toestimate software development labor and measure productivity. Weargue that the automated collection of these software metrics opensup new avenues for refining the management of software developmentprojects and controlling stra-egic costs.

Measurement of software development productivity is needed in order to controlsoftware costs, but it is discouragingly labor-intensive and expensive. Computer aidedsoftware engineering (CASE) technologies -- especially object-oriented, integrated CASE-- have the potential to support the automation of this measurement. In this paper, wediscuss the conceptual development of automated analyzers for function point andsoftware reusability measurement for object-based CASE. Both analyzers take advantageof the existence of a representation of the application system that is stored within anobject repository, and that contains the necessary information about the applicationsystem. We also propose new metrics for software reusability measurement, includingreuse leverage, reuse value and reuse classification. The functionality and analyticcapabilities of state-of-the-art automated software metrics analyzers are illustrated in thecontext of an investment banking industry application.

Measurement of software development productivity is needed in order to control software costs, but it isdiscouragingly labor-intensive and expensive. Computer aided software engineering (CASE) technologies --especially repository-based, integrated CASE -- have the potential to support the automation of thismeasurement. In this paper, we discuss the development of automated analyzers for function point andsoftware reuse measurement for object-based CASE. Both analyzers take advantage of the existence of arepresentation of the application system that is stored within an object repository, and that contains thenecessary information about the application system. We also discuss metrics for software reusemeasurement, including reuse leverage, reuse value and reuse classification, that are motivated by managerialrequirements and the efforts, within industry and the IEEE, to standardize measurement. The functionalityand the analytical capabilities of state-of-the-art automated software metrics analyzers are illustrated in thecontext of an investment banking industry application, that is similar to systems deployed at the New YorkCity-based investment bank where these tools were developed and tested.

Output measurement metrics for the softwaredevelopment process need to be re-examined todetermine their performance in the new, radicallychanged CASE development environment. This papercritiques and empirically evaluates several approachesto the measurement of outputs from the CASE process.The primary metric evaluated is the function pointsmethod developed by Albrecht. A second metrictested is a short-form variation of function points thatis easier and quicker to calculate. We also propose anew output metric called object points and a relatedshort-form, which are specialized for outputmeasurement in object-oriented CASE environmentsthat include a central object repository. These metricsare proposed as more intuitive and lower costapproaches to measuring the CASE outputs. Ourpreliminary results show that these metrics have thepotential to yield as accurate, if not better, estimatesthan function points-based measures.

Software Engineering: Architecture-driven Software Development is the first comprehensive guide to the underlying skills embodied in the IEEE's Software Engineering Body of Knowledge (SWEBOK) standard. Standards expert Richard Schmidt explains the traditional software engineering practices recognized for developing projects for government or corporate systems. Software engineering education often lacks standardization, with many institutions focusing on implementation rather than design as it impacts product architecture. Many graduates join the workforce with incomplete skills, leading to software projects that either fail outright or run woefully over budget and behind schedule. Additionally, software engineers need to understand system engineering and architecture—the hardware and peripherals their programs will run on. This issue will only grow in importance as more programs leverage parallel computing, requiring an understanding of the parallel capabilities of processors and hardware. This book gives both software developers and system engineers key insights into how their skillsets support and complement each other. With a focus on these key knowledge areas, Software Engineering offers a set of best practices that can be applied to any industry or domain involved in developing software products. - A thorough, integrated compilation on the engineering of software products, addressing the majority of the standard knowledge areas and topics - Offers best practices focused on those key skills common to many industries and domains that develop software - Learn how software engineering relates to systems engineering for better communication with other engineering professionals within a project environment

Existing output measurement metrics for cost estimation and development productivityneed to be re-examined to determine their performance in computer aided softwareengineering (CASE) development environments. This paper critiques and empiricallyevaluates four approaches to the measurement of outputs. Two of the metrics, rawfunction counts and function points, are based on the function point analysis methodologypioneered by Albrecht and Gaffney at IBM (ALBR83). The second two, object countsand object points, are based on a new approach -- object points analysis -- that isintroduced here for the first time. The latter metrics are specialized for outputmeasurement in object-based CASE environments that include a centralized objectrepository. Estimation results for nineteen large-scale CASE projects show that the newmetrics have the potential to yield as accurate, yet easier to obtain estimates thanfunction points-based measures.