Rüdiger Lincke

Quantitative Evaluation of Software Quality Metrics in Open-Source Projects

The validation of software quality metrics lacks statistical significance. One reason for this is that the data collection requires quite some effort. To help solve this problem, we develop tools for metrics analysis of a large number of software projects (146 projects with ca. 70.000 classes and interfaces and over 11 million lines of code). Moreover, validation of software quality metrics should focus on relevant metrics, i.e., correlated metrics need not to be validated independently. Based on our statistical basis, we identify correlation between several metrics from well-known object-oriented metrics suites. Besides, we present early results of typical metrics values and possible thresholds.

Online-configuration of software visualizations with Vizz3D

A software visualization is defined by an abstract software model, views on this model and a mapping between them. For creating new visualizations, we online-configure views and their mappings instead of hand-coding them. In this paper, we introduce an architecture allowing such an online configuration and, as a proof of concept, a framework implementing this architecture. In several examples, we demonstrate generality and flexibility of our approach.

A Metrics-Based Approach to Technical Documentation Quality

Technical documentation is now fully taking the step from stale printed booklets (or electronic versions of these) to interactive and online versions. This provides opportunities to reconsider how we define and assess the quality of technical documentation. This paper suggests an approach based on the Goal-Question-Metric paradigm: predefined quality goals are continuously assessed and visualized by the use of metrics. To test this approach, we perform two experiments. We adopt well known software analysis techniques, e.g., clone detection and test coverage analysis, and assess the quality of two real world documentations, that of a mobile phone and of (parts of) a warship. The experiments show that quality issues can be identified and that the approach is promising.

Software Quality Prediction Models Compared

Numerous empirical studies confirm that many software metrics aggregated in software quality prediction models are valid predictors for qualities of general interest like maintainability and correctness. Even these general quality models differ quite a bit, which raises the question: Do the differences matter? The goal of our study is to answer this question for a selection of quality models that have previously been published in empirical studies. We compare these quality models statistically by applying them to the same set of software systems, i.e., to altogether 328 versions of 11 open-source software systems. Finally, we draw conclusions from quality assessment using the different quality models, i.e., we calculate a quality trend and compare these conclusions statistically. We identify significant differences among the quality models. Hence, the selection of the quality model has influence on the quality assessment of software based on software metrics.

An Extensible Meta-Model for Program Analysis

Software maintenance tools for program analysis and refactoring rely on a metamodel capturing the relevant properties of programs. However, what is considered relevant may change when the tools are extended with new analyses, refactorings, and new programming languages. This paper proposes a language independent metamodel and an architecture to construct instances thereof, which is extensible for new analyses, refactorings, and new front-ends of programming languages. Due to the loose coupling between analysis, refactoring, and front-end components, new components can be added independently and reuse existing ones. Two maintenance tools implementing the metamodel and the architecture, VIZZANALYZER and X-DEVELOP, serve as proof of concept.

Information Quality Testing

When a new system, such as a knowledge management system or a content management system is put into production, both the software and hardware are systematically and thoroughly tested while the main purpose of the system — the information — often lacks systemic testing. In this paper we study how to extend testing approaches from software and hardware development to information engineering. We define an information quality testing procedure based on test cases, and provide tools to support testing as well as the analysis and visualization of data collected during the testing. Further, we present a feasibility study where we applied information quality testing to assess information in a documentation system. The results show promise and have been well received by the companies that participated in the feasibility study.

An Extensible Metamodel for Program Analysis (abstract only)

Software maintenance tools for program analysis and refactoring rely on a metamodel capturing the relevant properties of programs. However, what is considered relevant may change when the tools are extended with new analyses, refactorings, and new programming languages. This paper proposes a language independent metamodel and an architecture to construct instances thereof, which is extensible for new analyses, refactorings, and new front-ends of programming languages. Due to the loose coupling between analysis, refactoring, and front-end components, new components can be added independently and reuse existing ones. Two maintenance tools implementing the metamodel and the architecture, VlZZANALYZER and X-DEVELOP, serve as proof of concept.