Rachel Harrison

An evaluation of the MOOD set of object-oriented software metrics

This paper describes the results of an investigation into a set of metrics for object-oriented design, called the MOOD metrics. The merits of each of the six MOOD metrics is discussed from a measurement theory viewpoint, taking into account the recognized object-oriented features which they were intended to measure: encapsulation, inheritance, coupling, and polymorphism. Empirical data, collected from three different application domains, is then analyzed using the MOOD metrics, to support this theoretical validation. Results show that (with appropriate changes to remove existing problematic discontinuities) the metrics could be used to provide an overall assessment of a software system, which may be helpful to managers of software development projects. However, further empirical studies are needed before these results can be generalized.

Experimental assessment of the effect of inheritance on the maintainability of object-oriented systems

In this paper, we describe an empirical investigation into the modifiability and understandability of object-oriented (OO) software. A controlled experiment was conducted to establish the effects of varying levels of inheritance on understandability and modifiability. The software used in this experiment consisted of a C++ system without any inheritance and a corresponding version containing three levels of inheritance, as well as a second larger C++ system without inheritance and a corresponding version with five levels of inheritance. For both of the systems, the application modelled a database for a University personnel system. A number of statistical hypotheses were tested. Results indicated that the systems without inheritance were easier to modify than the corresponding systems containing three or five levels of inheritance. Also, it was easier to understand the system without inheritance than a corresponding version containing three levels of inheritance. Results also indicated that larger systems are equally difficult to understand whether or not they contain inheritance. The results contained in this paper highlight the need for further empirical investigations in this area, particularly into the benefits of using inheritance.

Coupling metrics for object-oriented design

We describe and evaluate some recently innovated coupling metrics for object-oriented (OO) design. The Coupling Between Objects (CBO) metric of Chidamber and Kemerer (1991) is evaluated empirically using five OO systems, and compared with an alternative OO design metric called SAS, which measures the number of associations between a class and its peers. The NAS metric is directly collectible from design documents such as the Object Model of OMT. Results from all systems studied indicate a strong relationship between CBO and NAS, suggesting that they are not orthogonal. We hypothesised that coupling would be related to understandability, the number of errors and error density. So relationships were found for any of the systems between class understandability and coupling. Only limited evidence was found to support our hypothesis linking increased coupling to increased error density. The work described in this paper is part of the Metrics for OO Programming Systems (MOOPS) project, which aims to evaluate existing OO metrics, and to innovate and evaluate new OO analysis and design metrics, aimed specifically at the early stages of development.

An Investigation into the Applicability and Validity ofObject-Oriented Design Metrics

In this paper we consider empirical evidence in support of a set of object-oriented software metrics. In particular, we look at the object oriented design metrics of Chidamber and Kemerer, and their applicability in different application domains.We briefly describe the metrics, and present our empirical findings, arising from our analysis of systems taken from a number of different application domains. Our investigations have led us to conclude that a subset of the metrics can be of great value to software developers, maintainers and project managers.

An overview of object-oriented design metrics

In this paper, we examine the current state in the field of object-oriented design metrices. We describe three sets of currently available metrics suites, namely, those of Chidamber and Kemerer (1993), Lorenze and Kidd (1994) and Abreu (1995). We consider the important features of each set, and assess the appropriateness and usefulness of each in evaluating the design of object-oriented systems. As a result, we identify problems common to all three sets of metrices, allowing us to suggest possible improvements in this area.

Comparing Programming Paradigms: an Evaluation of Functional and Object-Oriented Programs

A quantitative evaluation of the functional and object-oriented paradigms is presented. The aim of this project is to investigate whether the quality of code produced using a functional language is significantly different from that produced using an object-oriented language. 12 sets of algorithms are developed, together with a number of utility functions, in both Standard ML (SML) and C++. Strict constraints are imposed during the development cycle to improve the reliability of the results. The statistical tests do not reveal any significant differences for direct measures of the development metrics used which are associated with quality, such as the number of known errors, the number of modification requests, a subjective complexity assessment, etc. However, significant differences are found for an indirect measure, the number of known errors per thousand non-comment source lines, and for various code metrics, including the number of distinct functions called, the number of distinct library functions called, and the ratio of these, which is a measure of code reuse. A difference is also found for the time taken to test the programs, due to different compilation techniques and a difference in the number of test cases executed.

An evaluation of code metrics for object-oriented programs

Abstract This paper reports on the preliminary results of an investigation into the quality of programs written using different programming paradigms. In particular, the project aims to provide a quantitative analysis of the object-oriented and functional paradigms. Here, we report on the first stage of the project, the evaluation of a number of suggested indicators to determine whether or not they are correlated with the quality of object-oriented programs. Quality is assumed to be measured by the number of known errors encountered and the number of modification requests made during development, testing and maintenance, the times taken to attend to these and a subjective assessment of program complexity. We found that two of the suggested code metrics (the number of non-comment source lines and the number of function declarations) were strongly correlated with these measures of quality.

Estimating the quality of functional programs: an empirical investigation

Abstract This paper describes an investigation into estimating the quality of functional programs. The work reported here is part of a larger, ongoing study into a quantitative analysis of the effect of utilizing different programming paradigms on code quality. Before undertaking such a comparative analysis it was necessary to establish a baseline of quality indicators which could then be used as metrics for the remainder of the project. Thus the aim of the research presented here was to evaluate a set of suggested indicators corresponding to internal attributes by investigating the correlation between the suggested indicators and the desired external quality-type attributes of the code. A method for the evaluation of the suggested metrics is discussed and the results of performing such an evaluation for functional programs are presented.

Process modelling and empirical studies of software evolution (workshop)

INTRODUCTION Much progress is being made in both the areas of process modelling and software metrics. However, neither of these concepts is complete without the other: processes cannot be improved if no assessment of quality is available, and metrics are useless if they cannot be applied in order to assess the evolution of systems. Bringing together researchers and practitioners from both of these fields should stimulate some very interesting interactions.

Quantifying internal attributes of functional programs

Abstract There has been considerable interest in the use of metrics to quantify various quality attributes of software systems 1–4 . However, much of the reported research has been concerned with systems which are implemented in imperative and (to a lesser extent) object-oriented languages. The aim of the research reported here was to determine a suite of metrics which could be used to assess the quality attributes of code written in functional languages. This is a necessary preliminary step to assessing programs written in functional languages in a quantitative manner. In this paper we identify a set of appropriate measures and suggest additional measures to cope with the more novel aspects of functional languages. Experiments to determine whether or not these suggested measures do have any correlation with quality attributes have been performed with imperative languages 5 . Similar experiments with functional languages will also need to be performed.