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

Software development is becoming more and more model-centric. As a result models are used for a large variety of purposes, such as quality analysis, understanding, and maintenance. We argue that the UML and related existing tooling does not offer sufficient support to the developer to understand the models and evaluate their quality. We have proposed and implemented a collection of views to increase model understanding: MetaView, ContextView, MetricView, and UML-City-View. The purpose of this experiment is to validate whether there is a difference between the proposed views and the existing views with respect to comprehension correctness and comprehension effort. The comprehension task performed by the subjects was to answer a questionnaire about a model. 100 MSc students with relevant background knowledge have participated in the experiment. The results are statistically significant and show that the correctness is improved by 4.5% and that the time needed is reduced by 20%.

Interactive Views to Improve the Comprehension of UML Models - An Experimental Validation

Modelers tend to exploit the various degrees of freedom provided by the UML. The lack of uniformity and the large amount of defects contained in UML models result in miscommunication between different readers. To prevent these problems we propose modeling conventions, analogue to coding conventions for programming. This work reports on a controlled experiment to explore the effect of modeling conventions on defect density and modeling effort. 106 masters' students participated over a six-weeks period. Our results indicate that decreased defect density is attainable at the cost of increased effort when using modeling conventions, and moreover, that this trade-off is increased if tool-support is provided. Additionally we report observations on the subjects' adherence to and attitude towards modeling conventions. Our observations indicate that efficient integration of convention support in the modeling process, e.g. through training and seamless tool integration, forms a promising direction towards preventing defects.

An experimental investigation of UML modeling conventions

The importance of UML models in software engineering is increasing. Inherent to the UML is its lack of a formal semantics, its risk for inconsistency and completeness defects and the absence of modeling norms. These properties are sources for poor model quality and defects. To find out to which extent defects occur and what types of defects occur in practice we empirically investigate the state-of-the-practice of quality in UML models using a practitioners survey and a series of industrial case studies. Additionally we analyze the effects of defects in UML models experimentally. Based on this experiment we present an objective classification of UML defects which allows for prioritizing defects and thus allocate resources for defect removal. We aim at building a rule-set, metrics and visualization techniques to improve the quality of UML models during development. We propose a quality model that is specific for UML models. Finally, we propose modeling conventions, similar to coding conventions, to prevent for defects and to assure uniformity of modeling within an organization. We aim at empirically validating our techniques to provide pragmatic technology that can be transferred to industrial practice.

Improving the quality of UML models in practice

The UML is a collection of 13 diagram notations to describe different views of a software system. The existing diagram types display model elements and their relations. Software engineering is becoming more and more model-centric, such that software engineers start using UML models for more tasks than just describing the system. Tasks such as analysis or prediction of system properties require additional information such as metrics of the UML model or from external sources, e.g. a version control system. In this paper we identify tasks of model-centric software engineering and information that is required to fulfil these tasks. We propose views to visualize the information to support fulfilling the tasks. This paper reports on industrial case studies and a light-weight user experiment to validate the usefulness of the proposed views that are implemented in our MetricView evolution tool

Christian F. J. Lange

Papers

Interactive Views to Improve the Comprehension of UML Models - An Experimental Validation

An experimental investigation of UML modeling conventions

An experimental investigation of UML modeling conventions

Improving the quality of UML models in practice

A Visualization Framework for Task-Oriented Modeling Using UML