A Design Tool Used to Quantitatively Evaluate Student Projects

In the last decade, the field of Computer Science has undergone a revolution. It has started the move from a mysterious art form to a detailed science. The vehicle for this progress has been the rising popularity of the field of Software Engineering. This innovative area of computer science has brought about a number of changes in the way we think of, and work with, the development of software. Due to this renovation, a field that started with little or no design techniques and unstructured, unreliable software has progressed to a point where a plethora of techniques exist to improve the quality of a program design as well as that of the resultant software. The popularity of structured design and coding techniques prove that there is widespread belief that the overall product produced using these ideas is somehow better, and statistics seem to indicate that this belief is true. Until recently, however, there existed no technique for quantitatively showing one program better than its functional equivalent. In the past few years, the use of software quality metrics seems to indicate that such a comparison is not only possible, but is also valid. The advent of Software Engineering has demanded that most universities offer a Software Engineering course which entails a "Real-World" group project. Students participating in the class design a system using a program design language (PDL). Other students then write code from the design and finally the design team integrates the modules into a working system. For a complete description of the class see [HENS83] and [TOMJ87]

A Metric Tool for Predicting Source Code Quality from a PDL Design

The software crisis has increased the demand for automated tools to assist software developers in the production of quality software. Quality metrics have given software developers a tool to measure software quality. These measurements, however, are available only after the software has been produced. Due to high cost, software managers are reluctant, to redesign and reimplement low quality software. Ideally, a life cycle which allows early measurement of software quality is a necessary ingredient to solving the software crisis. This paper describes an automated tool for predicting software quality at design time

Design Metrics Which Predict Source Code Quality

Since the inception of software engineering, the major goal has been to control the development and maintenance of reliable software. To this end, many different design methodologies have been presented as a means to improve software quality through semantic clarity and syntactic accuracy during the specification and design phases of the software life cycle. On the other end of the life cycle, software quality metrics have been proposed to supply quantitative measures of the resultant software. This study is an attempt to unify the concepts of design methodologies and software quantity metrics by providing a means to determine the quality of a design before its implementation. By knowing (quantitatively) the quality of the design, a considerable amount of time and money can be saved by realizing design problems and being able to correct these problems at design time. All of this can be accomplished before any effort has been expended on the implementation of the software. This paper provides a means of allowing a software designer to predict the quality of the source code at design time. Actual equations for predicting source code quality from design metric values are given