software composed of artifacts written in multiple (programming) languages is pervasive in today's enterprise, desktop, and mobile applications. Since they form one system, artifacts from different languages refer...
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software product line (SPL) engineering provides a promising approach for developing variant-rich software systems. But, testing of every product variant in isolation to ensure its correctness is in general not feasib...
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Workflows exist in Wally different variants in order to adapt the behavior of systems to different circumstances and to arising user's needs. Variability modeling is a way of keeping track at the model level of th...
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ISBN:
(纸本)9783642280320
Workflows exist in Wally different variants in order to adapt the behavior of systems to different circumstances and to arising user's needs. Variability modeling is a way of keeping track at the model level of the currently supported and used workflow variants. Variability modeling approaches for workflows address two directions: structure-oriented approaches explicitly specify the workflow variants by means of linguistic constructs, while behavior-oriented approaches define the set of all valid compositions of workflow components by means of ontological annotations and temporal logic constraints. In this paper, we describe how both structure-oriented and behavior-oriented variability modeling can be captured in an eXtreme Model-Driven Design paradigm (XMDD). We illustrate this via a concrete case (a variant-rich bioinformatics workflow realized with the jABC platform for XMDD), and we compare the two approaches in order to identify their profiles and synergies.
In this paper we present our experiences from a decade of plug-in development in the jABC framework, that is characterized by rigorous application of simplicity principles in two dimensions. First, the scope of the pl...
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Program verification is the only way to be certain that a given piece of software is free of (certain types of) errors - - errors that could otherwise disrupt operations in the field. To date, formal verification has ...
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Testing software product lines by considering each product variant in isolation is impracticable due to the high number of potential product configurations. Therefore, applying SPL reuse principles also to test artifa...
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We present an active automata learning algorithm for Mealy state machines that directly constructs a state machine hypothesis according to observations, while other algorithms generate a state machine as output from i...
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ISBN:
(纸本)9783642347801
We present an active automata learning algorithm for Mealy state machines that directly constructs a state machine hypothesis according to observations, while other algorithms generate a state machine as output from information gathered in an observation table. Our DHC algorithm starts with a one-state hypothesis that it successively extends using a direct construction approach. This approach enables direct observation of the automata construction process: the learning algorithm continues to complete its hypothesis, providing intuition to a field of formal methods otherwise dominated by algorithms that largely operate on internal data structures without visible feedback. The DHC algorithm is competitive in cases where memory is the critical issue, e.g., in embedded networked systems. It is also well-suited as educational tool to teach the underlying well-established theoretical methods in a totally unbiased fashion, without cluttering the view onto the actual idea of the learning process with aspects only relevant to internal bookkeeping.
In this paper we address the major bottleneck of active automata learning, the typically huge number of required tests, by investigating the impact of using a distributed testing environment (a crowd of teachers) to e...
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ISBN:
(纸本)9783642347801
In this paper we address the major bottleneck of active automata learning, the typically huge number of required tests, by investigating the impact of using a distributed testing environment (a crowd of teachers) to execute test cases (membership queries) in parallel. This kind of parallelization of automata learning has the best potential when the time for test case execution is dominant, an assumption valid for most practical applications. Our investigation explicitly focuses on the impact of the structure of the system under learning (number of states, size of alphabet) and the degree of supported parallelism. It comprises three variants of active learning algorithms with different test case generation profiles. These differences can be observed directly at the level of the run-times, which all show a linear speedup for moderate degrees of parallelization, but with different saturation points beyond which further parallelization does not pay off.
A prominent learning algorithm is Angluin's L* algorithm, which allows to learn a minimal deterministic automaton using so-called membership and equivalence queries addressed to a teacher. In many applications, ho...
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We propose fLTL, an extension to linear-time temporal logic (LTL) that allows for expressing relative frequencies by a generalization of temporal operators. This facilitates the specification of requirements such as t...
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