From the Publisher:
Well-suited for both the student and the working professional,Software Engineering A Practitioner's Approach recognizes the dramatic growth in the field of software engineering and emphasizes new and important methods and tools used in the industry.

Software Engineering: A Practitioner's Approach

This paper summarizes the current state of the art and recent trends in software engineering economics. It provides an overview of economic analysis techniques and their applicability to software engineering and management. It surveys the field of software cost estimation, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.

Software engineering economics

Given the central role that software development plays in the delivery and application of information technology, managers are increasingly focusing on process improvement in the software development area. This demand has spurred the provision of a number of new and/or improved approaches to software development, with perhaps the most prominent being object-orientation (OO). In addition, the focus on process improvement has increased the demand for software measures, or metrics with which to manage the process. The need for such metrics is particularly acute when an organization is adopting a new technology for which established practices have yet to be developed. This research addresses these needs through the development and implementation of a new suite of metrics for OO design. Metrics developed in previous research, while contributing to the field's understanding of software development processes, have generally been subject to serious criticisms, including the lack of a theoretical base. Following Wand and Weber (1989), the theoretical base chosen for the metrics was the ontology of Bunge (1977). Six design metrics are developed, and then analytically evaluated against Weyuker's (1988) proposed set of measurement principles. An automated data collection tool was then developed and implemented to collect an empirical sample of these metrics at two field sites in order to demonstrate their feasibility and suggest ways in which managers may use these metrics for process improvement. >

/pdf/a-metrics-suite-for-object-oriented-design-539bycjzzb.pdf

A metrics suite for object oriented design

https://csse.usc.edu/TECHRPTS/1984/usccse84-500/usccse84-500.pdf

Software Engineering Economics

One of the most important problems faced by software developers and users is the prediction of the size of a programming system and its development effort. As an alternative to "size," one might deal with a measure of the "function" that the software is to perform. Albrecht [1] has developed a methodology to estimate the amount of the "function" the software is to perform, in terms of the data it is to use (absorb) and to generate (produce). The "function" is quantified as "function points," essentially, a weighted sum of the numbers of "inputs," "outputs,"master files," and "inquiries" provided to, or generated by, the software. This paper demonstrates the equivalence between Albrecht's external input/output data flow representative of a program (the "function points" metric) and Halstead's [2] "software science" or "software linguistics" model of a program as well as the "soft content" variation of Halstead's model suggested by Gaffney [7].

Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation

Elements of software science

In this preliminary report, a hypothesis is developed to the effect that algorithms, considered as distrillations of thought, may possess a general structure which obeys physical laws. Testing the hypothesis against measurements of published algorithms does not disprove it.

Natural laws controlling algorithm structure

/pdf/a-software-physics-analysis-of-akiyama-s-debugging-data-1b5crkcodg.pdf

A Software Physics Analysis of Akiyama's Debugging Data

Publisher Summary The chapter presents the overview of the present status of software science. Software science is an intellectually exciting discipline currently undergoing rapid development. Software science can be treated as a proper basis or foundation for the field of software engineering, but not as synonymous with it. This is not unlike other branches, in that the engineering usually preceded and indeed stimulated the development of the underlying science. It is interesting to note, however, that it is only after the development of thermodynamics for power engineering, electrodynamics for electrical engineering, or statics, dynamics, and strength-of-materials for mechanical engineering that those branches could be considered quasi complete, highly competent, and dependable engineering disciplines. Such a goal for software engineering clearly motivates much of the work in software science. Despite the fact that there are no theorems, and perhaps never can be any, in the field of software science, one basic attribute shared by the equations in this field has become quite noticeable. This is the total and complete lack of arbitrary constants or unknown coefficients among the basic equations. It cannot yet be predicted what impact this discipline may be expected to have on the field of software engineering, or of computer programming in general in the future, but perhaps its greatest impact may result from one conclusion that seems inescapable. This conclusion is that natural laws govern language and the mental activity of using it far more strictly than previously recognized.

Maurice H. Halstead

Papers

Elements of software science

Natural laws controlling algorithm structure

A Software Physics Analysis of Akiyama's Debugging Data

Advances in Software Science

Invariant properties of algorithms