Christian F. J. Lange

Managing Model Quality in UML-Based Software Development

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

Effects of defects in UML models: an experimental investigation

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 experiments 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.

Improving the quality of UML models in practice

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.

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

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%.

Model size matters

Size is an important attribute of software artefacts; for most artefact types exists a body of measurement knowledge. As software engineering is becoming more and more model-centric, it is surprising that there exists only little work on model size metrics (MoSMe). In this position paper we identify the goals justifying the need for MoSMe, such as prediction, description and progress measurement. Additionally, we identify challenges that make it difficult to measure the size of UML models and that MoSMe have to deal with. Finally, we propose a classification of MoSMe and concrete examples of metrics for the size of UML models.

A Visualization Framework for Task-Oriented Modeling Using UML

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

MetricViewEvolution: UML-based Views for Monitoring Model Evolution and Quality

As the role of models during software development and maintenance is becoming more and more important, techniques are needed to control a models quality during evolution. We present our tool MetricViewEvolution as a step towards managing model quality during development and evolution. Six views are implemented in MetricViewEvolution that aid the user in tasks such as model understanding, identification of quality problems and evolution trends. The views combine structural model information with metrics data from inside the model and external sources. MetricViewEvolution has been applied successfully in industrial case studies

Investigations in applying metrics to multi-view architecture models

The goal of our research is to develop industry-proof software architecture and design metrics. We identify a number of problems that arise in computing software architecture and design metrics in industrial settings that were not encountered in computing source-code metrics. These problems include the absence of a single, unifying representation for architectures and they arise from the fact that architecture diagrams are used in an informal manner. We describe our approach towards defining metrics for architectures and designs which are represented in the 4+1 views paradigm using UML. We report our experiences with architectural metrics in industrial settings.

Supporting task-oriented modeling using interactive UML views

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 fulfill these tasks. We propose views to visualize the information to support fulfilling the tasks. This paper reports on a large-scale controlled experiment to validate the usefulness of the proposed views that are implemented in our MetricView Evolution tool. The results of the experiment with 100 participants are statistically significant and show that the correctness of comprehension is improved by 4.5% and that the time needed is reduced by 20%.

Combining metrics data and the structure of UML models using GIS visualization approaches

UML models describe the structure and behavior of existing or future software systems. In addition to the UML model, developers consult metrics and other attribute data for evaluation and analysis purposes. In hitherto techniques, attribute data and structural data in the diagrams of the UML model is split in different representations. For the process of evaluation of a system the attribute data must be combined with the structural data. Geographical information systems (GIS) deploy visualization techniques to combine these different types of data. We propose a set of visualization techniques adopted from GIS to enrich UML models with attribute data. Advantages and examples of the visualizations are discussed, as well as limitations to the applicability. Especially the technique where colors represent attribute values of elements seems promising.