Small Software Projects Research Articles

A structured methodology for software development effort prediction using the analytic hierarchy process

Predicting the effort needed for software development projects has frustrated many project managers. A primary reason is that most estimation measures fail to observe environmental characteristics that vary significantly depending on the organization involved in the software development. The objective of this article is to propose an improved method for software estimation using the analytic hierarchy process (AHP) to capture such environmental factors as well as technical aspects of software in the estimation process. Development efforts of a software project are factored into manageable components through a hierarchical structure. This methodology can provide a structured approach in which the organization's characteristics are integrated with the technical requirements of the software project. A small sample software project demonstrates the applicability of the AHP in software estimation.

A practical training in software engineering methodology

This paper reports the application of large-scale software engineering methodology to small software projects. These projects were part of the curriculum of the recently launched Motorola Entry Level Training Program For Software Engineers, for college graduates. The results indicated that large scale software engineering methodology can be applied successfully to small projects. In addition, our results support most of Barry Boehm's findings in a similar study. The "deadline effect," as observed by Boehm holds especially true in our software projects and can be used to help manage software development.Contrary to Boehm's results, however, we found that programming including debugging is the dominant activity in small software product development. Possible reasons are given to explain this difference.

Prototyping and small scale software projects

To reduce the development time of small scale interactive software systems for research and clinical use in cardiology at UAB a display-oriented language was developed. Experience with this system has been very successful in early stabilization of the specification of the user dialogue.

An Experiment in Small-Scale Application Software Engineering

This paper reports the results of an experiment in applying large-scale software engineering procedures to small software projects. Two USC student teams developed a small, interactive application software product to the same specification, one using Fortran and one using Pascal. Several hypotheses were tested, and extensive experimenal data collected. The major conclusions were as follows.

Some experience with automated aids to the design of large-scale reliable software

This paper summarizes some recent experience in analyzing and eliminating sources of error in the design phase of large software projects. It begins by pointing out some of the significant differences in software error incidence between large and small software projects. The most striking contrast, illustrated by project data, is the large preponderance of design errors over coding errors on large-scale projects, not only with respect to numbers of errors, but also with respect to the relative time and effort required to detect them and correct them. The paper next presents a taxonomy of software error causes, and some analyses of the design error data, performed to obtain a better understanding of the nature of large-scale software design errors and to evaluate alternative methods of preventing, detecting, and eliminating them. Based on this analysis of observational data, a hypothesis was derived regarding the potential cost-effectiveness of an automated aid to detecting inconsistencies between assertions about the nature of inputs and outputs of the various elements (functions, modules, data bases, data sources, etc.) of the software design. This hypothesis was tested by developing a prototype version of such an aid, the Design Assertion Consistency Checker (DACC), using TRW's Generalized Information Management (GIM) system, and using it on a large-scale software project with 186 elements and 967 assertions about their inputs and outputs. Of the 121,000 possible mismatches between input and output assertions, DACC found 818, at a cost in computer time of $30. Most of the mismatches resulted from shortfalls in the initial version of DACC or the initial data preparation, such as a lack of a synonym capability and a lack of a explicit statements about external inputs and outputs. However, a number of serious mismatches were exposed at a time when they were easy to correct, and a most useful work-list generated of items needing resolution before allowing the design effort to proceed to further detail. In general, the data confirmed the hypothesis about the general utility of a DACC capability for large software projects. However, a number of additional features should be considered to compensate for current deficiencies (in areas such as manuscript preparation) and to fully take advantage of having the software design in machine-readable form.

Some experience with automated aids to the design of large-scale reliable software

Summarizes some recent experience in analyzing and eliminating sources of error in the design phase of large software projects. It points out some of the significant differences in software error incidence between large and small software projects. A taxonomy of software error causes, and some analyses of the design error data performed to obtain a better understanding of the nature of large-scale software design errors and to evaluate alternative methods of preventing, detecting, and eliminating them are presented. Based on this analysis of observational data, a hypothesis was derived regarding the potential cost effectiveness of an automated aid to detecting inconsistencies between assertions about the nature of inputs and outputs of the various elements of the software design.