Object-Oriented Software Metrics.

This paper presents some initial results from a twelve-month empirical research study of model driven engineering (MDE). Using largely qualitative questionnaire and interview methods we investigate and document a range of technical, organizational and social factors that apparently influence organizational responses to MDE: specifically, its perception as a successful or unsuccessful organizational intervention. We then outline a range of lessons learned. Whilst, as with all qualitative research, these lessons should be interpreted with care, they should also be seen as providing a greater understanding of MDE practice in industry, as well as shedding light on the varied, and occasionally surprising, social, technical and organizational factors that affect success and failure. We conclude by suggesting how the next phase of the research will attempt to investigate some of these issues from a different angle and in greater depth.

Empirical assessment of MDE in industry

Metrics and Models in Software Quality Engineering

Despite that formal and informal quality aspects are of significantimportance to business process modeling, there is only little empiricalwork reported on process model quality and its impact factors. Inthis paper we investigate understandability as a proxy for quality of processmodels and focus on its relations with personal and model characteristics.We used a questionnaire in classes at three European universitiesand generated several novel hypotheses from an exploratory data analysis.Furthermore, we interviewed practitioners to validate our findings.The results reveal that participants tend to exaggerate the differences inmodel understandability, that self-assessment of modeling competenceappears to be invalid, and that the number of arcs in models has animportant influence on understandability.

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What makes process models understandable

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

The Unified Modeling Language has attracted many organizations and practitioners. UML is now the de facto modeling language for software development. Several features account for its popularity: it's a standardized notation, rich in expressivity; UML 2.0 provides 13 diagram types that enable modeling several different views and abstraction levels. Furthermore, UML supports domain-specific extensions using stereotypes and tagged values. Finally, several case tools integrate UML modeling with other tasks such as generating code and reverse-engineering models from code. Our study focused on UML use and model quality in actual projects rather than on its adequacy as a notation or language.

In practice: UML software architecture and design description

The Unified Modeling Language (UML) is the de facto standard for designing and architecting software systems. UML offers a large number of diagram types that can be used with varying degree of rigour. As a result UML models may contain consistency defects. Previous research has shown that industrial UML models that are used as basis for implementation and maintenance contain large numbers of defects. This study investigates to what extent implementers detect defects and to what extent defects cause different interpretations by different readers. We performed two controlled experiments with a large group of students (111) and a group of industrial practitioners (48). The experiment's results show that defects often remain undetected and cause misinterpretations. We present a classification of defect types based on a ranking of detection rate and risk for misinterpretation. Additionally we observed effects of using domain knowledge to compensate defects. The results are generalizable to industrial UML users and can be used for improving quality assurance techniques for UML-based development.

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Effects of defects in UML models: an experimental investigation

With the advent of UML and MDA, models play an increasingly important role in software development. Hence, the management of the quality of models is of key importance for completing projects succesfully. However, existing approaches towards software quality focus on the implementation and execution of systems. These existing quality models cannot be straightforwardly mapped to the domain of UML models as source code and models differ in several essential ways (level of abstraction, precision, completeness and consistency). In this paper we present a quality model for managing UML-based software development. This model enables identifying the need for actions for quality improvement already in early stages of the life-cycle. Early actions for quality improvement are less resource intensive and, hence, less cost intensive than later actions. We discuss our experiences in applying the quality model to several industrial case studies. Finally we present a tool that visualizes our quality model. This tool helps in relating management level quality data to detailed data about specific quality subcharacteristics

Managing Model Quality in UML-Based Software Development

We present MetricView, a software visualization and exploration tool that combines traditional UML diagram visualization with metric visualization in an effective way. MetricView is very easy and natural to use for software architects and developers yet offers a powerful set of mechanisms that allow fine customization of the visualizations for getting specific insights. We discuss several visual and architectural design choices which turned out to be important in the construction of MetricView, and illustrate our approach with several results using real-life datasets

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Visual Exploration of Combined Architectural and Metric Information

Delivering high quality software in an economic way requires advanced control over the software development process and the product in all stages of its life-cycle. The use of metrics as means of control and improvement plays an important role in software engineering. Interviews with industrial software engineers identified incompleteness of UML designs as a potential problem for subsequent stages of development. In this paper we propose a definition of completeness of a UML model and present a set of rules to assess model completeness. We report results from industrial case studies to assess the level of completeness in practice. The amount of completeness and consistency rule violations was very high. Different case studies showed large variations in conformance to and violations of rules.

Christian F. J. Lange

Papers

In practice: UML software architecture and design description

Effects of defects in UML models: an experimental investigation

Managing Model Quality in UML-Based Software Development

Visual Exploration of Combined Architectural and Metric Information

An empirical assessment of completeness in UML designs