Software metric

Abstract: Coupling of a subsystem characterizes its interdependence with other subsystems. A subsystem's cohesion, on the other hand, characterizes its internal interdependencies. When used in conjunction with other attributes, measurements of a subsystem's coupling and cohesion can contribute to software quality models. An abstraction of a software system can be represented by a graph, and a module (subsystem) by a subgraph. Software design graphs depict components and their relationships. E.B. Allen and T.M. Khoshgoftaar (1999) proposed information theory-based measures of coupling and cohesion of a modular system. This paper proposes related information theory-based measures of coupling and cohesion of a module. These measures have the properties of module-level coupling and cohesion defined by Briand, Morasca and Basili (1997, 1999) . We define cohesion of a module in terms of intra-module coupling, normalized to between zero and one. We illustrate the measures with example graphs and an empirical analysis of the call graph of a moderate-sized C program, the Nethack computer game. Preliminary analysis showed that the information-theory approach has finer discrimination than counting.

Abstract: Generally believed to be a problem belonging to the compiler and architecture communities, performance optimization has rarely gained attention in mainstream software engineering research. However, due to the proliferation of large-scale object-oriented software designed to solve increasingly complex problems, performance issues stand out, preventing applications from meeting their performance requirements. Many such issues result from design principles adopted widely in the software research community, such as the idea of software reuse and design patterns. We argue that, in the modern era when Moore's dividend becomes less obvious, performance optimization is more of a software engineering problem than ever and should receive much more attention in the future. We explain why this is the case, review what has been achieved in software bloat analysis, present challenges, and provide a road map for future work.

Abstract: This paper presents an empirical study that evaluates software-quality models over several releases, to address the question, "How long will a model yield useful predictions?" The classification and regression trees (CART) algorithm is introduced, CART can achieve a preferred balance between the two types of misclassification rates. This is desirable because misclassification of fault-prone modules often has much more severe consequences than misclassification of those that are not fault-prone. The case-study developed 2 classification-tree models based on 4 consecutive releases of a very large legacy telecommunication system. Forty-two software product, process and execution metrics were candidate predictors. Model 1 used measurements of the first release as the training data set; this model had 11 important predictors. Model 2 used measurements of the second release as the training data set; this model had 15 important predictors. Measurements of subsequent releases were evaluation data sets. Analysis of the models' predictors yielded insights into various software development practices. Both models had accuracy that would be useful to developers. One might suppose that software-quality models lose their value very quickly over successive releases due to evolution of the product and the underlying development processes. The authors found the models remained useful over all the releases studied.

Abstract: Software maintenance can be successfully accomplished if the computing arrangements of the people doing the maintenance are compatible with their established patterns of work in the setting. To foster and achieve such compatibility requires an understanding of the reasons and the circumstances in which participants carry out maintenance activities. In particular, it requires an understanding of how software users and maintainers act toward the changing circumstances and unexpected events in their work situation that give rise to software system alterations. To contribute to such an understanding, we describe a comparative analysis of the work involved in maintaining and evolving text-processing systems in two academic computer science organizations. This analysis shows that how and why software systems are maintained depends on occupational and workplace contingencies, and vice versa.