The decision of using existing software components versus building from scratch custom software is one of the most complex and important choices of the entire development/integration process. However, the reuse of software components raises a spectrum of issues, from requirements negotiation to product selection and integration. The correct tradeoff is reached after having analyzed advantages and issues correlated to the reuse. Despite the reuse failures in real cases, many efforts have been made to make this idea successful.
In this context of software reuse in open source projects, we address the problem of reusing annotated components proposing a rigorous approach to assure the quality of the application under construction. We introduce the concept of caller-based slicing as a way of certifying that the integration of a component annotated with a contract into a system will preserve the correct behavior of the former, avoiding malfunctioning after integration.
To complement the efforts done and the benefits of slicing techniques, there is also a need to find an efficient way to visualize the main program with the annotated components and the slices. To take full profit of visualization, it is crucial to combine the visualization of the control/data flow with the textual representation of source code. To attain this objective, we extend the notions of System Dependence Graph and Slicing Criterion to cope with annotations.

In this paper, we present a systematic way of deriving (1) languages of (generalized) regular expressions, and (2) sound and complete axiomatizations thereof, for a wide variety of systems. This generalizes both the results of Kleene (on regular languages and deterministic finite automata) and Milner (on regular behaviours and finite labelled transition systems), and includes many other systems such as Mealy and Moore machines.

(Semi-)automated diagnosis of software faults can drastically increase debugging efficiency, improving reliability and time-to-market. Current automatic diagnosis techniques are predominantly of a statistical nature and, despite typical defect densities, do not explicitly consider multiple faults, as also demonstrated by the popularity of the single-fault benchmark set of programs. We present a reasoning approach, called Zoltar-M(ultiple fault), that yields multiple-fault diagnoses, ranked in order of their probability. Although application of Zoltar-M to programs with many faults requires heuristics (trading-off completeness) to reduce the inherent computational complexity, theory as well as experiments on synthetic program models and multiple-fault program versions available from the software infrastructure repository (SIR) show that for multiple-fault programs this approach can outperform statistical techniques, notably spectrum-based fault localization (SFL). As a side-effect of this research, we present a new SFL variant, called Zoltar-S(ingle fault), that is optimal for single-fault programs, outperforming all other variants known to date.

In fault diagnosis intermittent failure models are an important tool to adequately deal with realistic failure behavior. Current model-based diagnosis approaches account for the fact that a component c"j may fail intermittently by introducing a parameter g"j that expresses the probability the component exhibits correct behavior. This component parameter g"j, in conjunction with a priori fault probability, is used in a Bayesian framework to compute the posterior fault candidate probabilities. Usually, information on g"j is not known a priori. While proper estimation of g"j can be critical to diagnostic accuracy, at present, only approximations have been proposed. We present a novel framework, coined Barinel, that computes estimations of the g"j as integral part of the posterior candidate probability computation using a maximum likelihood estimation approach. Barinel's diagnostic performance is evaluated for both synthetic systems, the Siemens software diagnosis benchmark, as well as for real-world programs. Our results show that our approach is superior to reasoning approaches based on classical persistent failure models, as well as previously proposed intermittent failure models.

Refinement by interpretation replaces signature morphisms by logic interpretations as a means to translate specifications and witness refinements. The approach was recently introduced by the authors [13] in the context of equational specifications, in order to capture a number of relevant transformations in software design, reuse and adaptation. This paper goes a step forward and discusses the generalization of this idea to deductive systems of arbitrary dimension. This makes possible, for example, to refine sentential into equational specifications and the latter into modal ones. Moreover, the restriction to logics with finitary consequence relations is dropped which results in increased flexibility along the software development process.

Even though concurrent programming has been a hot topic of discussion in Computer Science for the past 30 years, the community has yet to settle on a, or a few standard approaches to implement concurrent programs. But as more and more cores inhabit our CPUs and more and more services are made available on the web the problem of coordinating different tasks becomes increasingly relevant.
The present paper addresses this problem with an implementation of the orchestration language Orc as a domain specific language in Haskell. Orc was, therefore, realized as a combinator library using the lightweight threads and the communication and synchronization primitives of the Concurrent Haskell library. With this implementation it becomes possible to create orchestrations that re-use existing Haskell code and, conversely, re-use orchestrations inside other Haskell programs.
The complexity inherent to distributed computation, entails the need for the classification of efficient, re-usable, concurrent programming patterns. The paper discusses how the calculus of recursive schemes used in the derivation of functional programs, scales up to a distributed setting. It is shown, in particular, how to parallelize the entire class of binary tree hylomorphisms.

Spectrum-based fault localization (SFL) shortens the test-diagnose-repair cycle by reducing the debugging effort. As a light-weight automated diagnosis technique it can easily be integrated with existing testing schemes. Since SFL is based on discovering statistical coincidences between system failures and the activity of the different parts of a system, its diagnostic accuracy is inherently limited. Using a common benchmark consisting of the Siemens set and the space program, we investigate this diagnostic accuracy as a function of several parameters (such as quality and quantity of the program spectra collected during the execution of the system), some of which directly relate to test design. Our results indicate that the superior performance of a particular similarity coefficient, used to analyze the program spectra, is largely independent of test design. Furthermore, near-optimal diagnostic accuracy (exonerating over 80% of the blocks of code on average) is already obtained for low-quality error observations and limited numbers of test cases. In addition to establishing these results in the controlled environment of our benchmark set, we show that SFL can effectively be applied in the context of embedded software development in an industrial environment.

Coordination in Reo emerges from the composition of the behavioural constraints of the primitives, such as channels, in a component connector. Understanding and implementing Reo, however, has been challenging due to interaction of the channel metaphor, which is an inherently local notion, and the non-local nature of constraint propagation imposed by composition. In this paper, the channel metaphor takes a back seat, and we focus on the behavioural constraints imposed by the composition of primitives, and phrase the semantics of Reo as a constraint satisfaction problem. Not only does this provide a clear intensional description of the behaviour of Reo connectors in terms of synchronisation and data flow constraints, it also paves the way for new implementation techniques based on constraint propagation and satisfaction. In fact, decomposing Reo into constraints provides a new computational model for connectors, which we extend to model interaction with an unknown external world beyond what is currently possible in Reo.

Analytic usability analysis methods have been proposed as an alternative to user testing in early phases of development due to the cost of the latter approach. By working with models of the systems, analytic models are not capable of identifying implementation related problems that might have an impact on usability. Model-based testing enables the testing of an implemented software artefact against a model of what it should be (the oracle). In the case of model-based user interface testing, the models should be expressed at an adequate level of abstraction, adequately modelling the interaction process. This paper describes an effort to develop tool support enabling the use of task models as oracles for model-based testing of user interfaces.