In order to increase our ability to use measurement to support software development practise we need to do more analysis of code. However, empirical studies of code are expensive and their results are difficult to compare. We describe the Qualitas Corpus, a large curated collection of open source Java systems. The corpus reduces the cost of performing large empirical studies of code and supports comparison of measurements of the same artifacts. We discuss its design, organisation, and issues associated with its development.

Formal methods offer an effective means to assert the correctness of software systems through mathematical reasoning. However, the need to formulate system properties in a purely mathematical fashion can create pragmatic barriers to the application of these techniques. For this reason, Dwyer et al. invented property specification patterns which is a system of recurring solutions to deal with the temporal intricacies that would make the construction of reactive systems very hard otherwise. Today, property specification patterns provide general rules that help practitioners to qualify order and occurrence, to quantify time bounds, and to express probabilities of events. Nevertheless, a comprehensive framework combining qualitative, real-time, and probabilistic property specification patterns has remained elusive. The benefits of such a framework are twofold. First, it would remove the distinction between qualitative and quantitative aspects of events; and second, it would provide a structure to systematically discover new property specification patterns. In this paper, we report on such a framework and present a unified catalogue that combines all known plus 40 newly identified or extended patterns. We also offer a natural language front-end to map patterns to a temporal logic of choice. To demonstrate the virtue of this new framework, we applied it to a variety of industrial requirements, and use PSPWizard, a tool specifically developed to work with our unified pattern catalogue, to automatically render concrete instances of property specification patterns to formulae of an underlying temporal logic of choice.

Software metrics offer us the promise of distilling useful information from vast amounts of software in order to track development progress, to gain insights into the nature of the software, and to identify potential problems. Unfortunately, however, many software metrics exhibit highly skewed, nonGaussian distributions. As a consequence, usual ways of interpreting these metrics -for example, in terms of "average" values -can be highly misleading. Many metrics, it turns out, are distributed like wealth -with high concentrations of values in selected locations. We propose to analyze software metrics using the Gini coefficient, a higherorder statistic widely used in economics to study the distribution of wealth. Our approach allows us not only to observe changes in software systems efficiently, but also to assess project risks and monitor the development process itself. We apply the Gini coefficient to numerous metrics over a range of software projects, and we show that many metrics not only display remarkably high Gini values, but that these values are remarkably consistent as a project evolves over time.

Detecting inconsistencies is a critical part of Requirements Engineering (RE) and has been a topic of interest for several decades. Domain knowledge and semantics of requirements not only play important roles in elaborating requirements but are also a crucial way to detect conflicts among them. In this paper we present a novel knowledge-based RE framework (KBRE) in which domain knowledge and semantics of requirements are central to elaboration, structuring, and management of captured requirements. Moreover, we also show how they facilitate the identification of requirements inconsistencies and other related problems. In our KBRE model, Description Logic (DL) is used as the fundamental logical system for requirements analysis and reasoning. In addition, the application of DL in the form of Manchester OWL Syntax brings simplicity to the formalization of requirements while preserving sufficient expressive power. A tool has been developed and applied to an industrial use case to validate our approach.

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When building software systems, developers have to weigh the benefits of using one specific solution approach against the risks and costs of using another one. This process is not random. Certain preferences, architectural styles, and solution domain pressures create systematic biases that we can measure in order to assess their impact on the system being built and the underlying development process itself. In this paper we explore, whether the getter and setter methods in Java give rise to a bias also. Getter and setter methods, called "properties", are perceived commonplace and considered by some as a threat to data encapsulation. However, little empirical evidence exists that can reliably inform us about the real impact of the use of properties in Java. For this reason, we examined 102 open-source Java systems and discovered that properties are employed much more carefully than one might expect. Contrary to some folklore, developers use properties not just to gain access to an object's private state, but in a systematic and responsible manner and, in general, consistent with the domain requirements of the developed software system.

Contemporary software systems are composed of many components, which, in general, undergo phased and incremental development. In order to facilitate the corresponding construction process, it is important that the development team in charge has a good understanding of how individual software components typically evolve. Furthermore, software engineers need to be able to recognize abnormal patterns of growth with respect to size, structure, and complexity of the components and the resulting composite. Only if a development team understands the processes that underpin the evolution of software systems, will they be able to make better development choices. In this paper, we analyze recurring structural and evolutionary patterns that we have observed in public-domain software systems built using object-oriented programming languages. Based on our analysis, we discuss common growth patterns found in present-day component-based software systems and illustrate simple means to aid developers in achieving a better understanding of those patterns. As a consequence, we hope to raise the awareness level in the community on how component-based software systems tend to naturally evolve.

Abstract. Automata-based interface and protocol specifications provide an elegant framework to capture and automatically verify the interactive behavior of component-based software systems. Unfortunately, the underlying formalisms suffer from combinatorial state explosion when constructing new specifications for composite components or systems and may therefore render the application of these techniques impractical for real-world applications. In this paper, we explore the bisimulation technique as a means for a mechanical state space reduction of component-based systems. In particular, we apply both strong and weak bisimulation to Component Interaction Automata in order to obtain a minimal automata that can serve as a behavioral equivalent abstraction for a given component specification and illustrate that the proposed approach can significantly reduce the complexity of an interface specification after composition.