On translating UML models into graph transformation systems

The main idea of graph grammars and graph transformation is the rule-based graph rewriting, where the application of every rule graph rule leads to a graph transformation step. Graph grammars can be used to generate graph languages which is similar to Chomsky grammars in formal language theory. Moreover, graphs can be used to model the states of all kinds of systems, which allows one to use graph transformation to model state changes in these systems. A rule-based transformation system may show two kinds of nondeterminism: (1) for each rule can exist several matches, and (2) several rules can be applicable. This paper concentrates on the second non-determinism, studying a method to detect the rules which are not applicable in graph transformation systems, proposing a backward graph transformation conflict detecting algorithm. At first the computation of conflict and dependency of two rules is available by use of AGG . Secondly the set of dependencies has to be tested by Warshall algorithm and the set of conflicts has to be computed by backward algorithm. At last, the termination of graph transformation systems and validity of rules can be detected as well.

In this work we show that the reachability problem for graph transformation systems is in the complexity class XP when parameterized with respect to the depth of derivations and the cutwidth of the source graph. More precisely, we show that for any set \(\mathcal {R}\) of graph transformation rules, one can determine in time \(f(c,d)\cdot |G|\cdot |H|^{g(c,d)}\) whether a graph G of cutwidth c can be transformed into a graph H in depth at most d by the application of graph transformation rules from \(\mathcal {R}\). In particular, our algorithm runs in polynomial time when c and d are constants. On the other hand, we show that the problem becomes NP-hard if we allow \(c=O(|G|)\) and \(d=5\). In the case in which all transformation rules are monotone we get an algorithm running in time \(f(c,d)\cdot |G|^{O(c)}\cdot |H|\). To prove our main theorems we will establish an interesting connection between graph transformation systems and regular slice languages. More precisely, we show that if \(\mathcal {A}\) is a slice automaton representing a set \({\mathcal {L}}_{{\mathcal {G}}}(\mathcal {A})\) of graphs, then one can construct in time linear in \(|\mathcal {A}|\) a slice automaton \(\mathcal {N}(\mathcal {A})\) representing the set of all graphs that can be obtained from graphs in \({\mathcal {L}}_{{\mathcal {G}}}(\mathcal {A})\) by the application of one layer of transformation rules in \(\mathcal {R}\).

UML state machines are quite popular and useful to specify dynamic components of software systems. They have a formal static semantics but their execution semantics is described only informally. Graph transformation, on the other hand, constitutes a well-studied area with many theoretical results and practical application domains. In this paper, an operational semantics for a subset of UML state machines is proposed which is based on graph transformation. In more detail, a UML state machine is described as a structured graph transformation system in such a way that the wellformedness rules of UML state machines are satisfied and the firing of a (maximum) set of enabled non-conflicting transitions corresponds to the application of a graph transformation rule. The presented approach uses the concept of transformation units, a recently developed modularization concept for graph transformation systems.

Graph Transformation Systems (GTSs) provide visual and explicit semantics for dynamically evolving multi-process systems such as network programs and communication protocols. Existing symmetry reduction techniques that generate a reduced, bisimilar model for alleviating state explosion in model checking are not applicable to dynamic models such as those given by GTSs. We develop symmetry reduction techniques applicable to evolving GTS models and the programs that generate them. We also provide an on-the-fly algorithm for generating a symmetry-reduced quotient model directly from a set of graph transformation rules. The generated quotient model is GTS-bisimilar to the model under verification and may be exponentially smaller than that model. Thus, analysis of the system model can be performed by checking the smaller GTS-bisimilar model.

Applying an attributed graph transformation rule to a given object graph always implies some kind of constraint solving. In many cases, the given constraints are almost trivial to solve. For instance, this is the case when a rule describes a transformation G ⇒ H, where the attributes of H are obtained by some simple computation from the attributes of G. However there are many other cases where the constraints to solve may be not so trivial and, moreover, may have several answers. This is the case, for instance, when the transformation process includes some kind of searching. In the current approaches to attributed graph transformation these constraints must be completely solved when defining the matching of the given transformation rule. This kind of early binding is well-known from other areas of Computer Science to be inadequate. For instance, the solution chosen for the constraints associated to a given transformation step may be not fully adequate, meaning that later, in the search for a better solution, we may need to backtrack this transformation step. In this paper, based on our previous work on the use of symbolic graphs to deal with different aspects related with attributed graphs, including attributed graph transformation, we present a new approach that, based on the new notion of narrowing graph transformation rule, allows us to delay constraint solving when doing attributed graph transformation, in a way that resembles lazy computation. For this reason, we have called lazy this new kind of transformation. Moreover, we show that the approach is sound and complete with respect to standard attributed graph transformation. A running example, where a graph transformation system describes some basic operations of a travel agency, shows the practical interest of the approach.

Model checking is one of the successful techniques in automated verification of software and hardware systems. However, employing this technique for verification of properties such as the safety and liveness requires that all possible states of a system are generated and then the given property is checked. In large and complex systems, generating all states causes the state space explosion problem. Hence, it is possible to refute such properties by searching the state space to find a state in which the given property is violated. Of course, it is possible that detecting such states in complex systems leads to the exhaustive exploration of the state space. Recent researches confirm that using meta-heuristic and evolutionary approaches to intelligently explore a portion of the state space can be a promising idea. Hence, in this paper, we propose an approach based on ant colony optimization algorithm for refuting the safety and liveness properties and also analyzing reachability ones in systems specified formally through graph transformation system. Refutation of liveness and analyzing reachability properties in systems modeled by graph transformations are the prominent advantages of this approach in comparison with the previous approaches. The proposed approach is implemented in GROOVE which is an open source toolset for designing and model checking graph transformation systems. Experimental results show that our proposed approach is faster and it generates shorter counterexamples in comparison with others.

The design of business or production systems frequently necessitates to simultaneously fulfill several logical and numerical constraints as requirements in order to deliver a functionally correct and optimal system. Such a problem can be typically formulated as a combined optimization and reachability analysis. In the current paper, we show how this problem can be formalized when the evolution of the system is captured by graph transformation systems (GTS) with a cost parameter attached to each graph transformation rule denoting the cost of firing the rule. Furthermore, we discuss how to solve such problems by combining guided state space exploration with algebraic techniques of Petri nets.

Multivariate conditional regression using a Bayesian estimation approach for the development of a surrogate dissolution model as part of a comprehensive Process Analytical Technology (PAT) release strategy is the subject of this chapter. An appropriate experimental design provides the basis for constructing a process model in the first step, relating dissolution variables as the response to the critical process parameters (CPPs). Dissolution variables are either: Case 1: in vitro release measurements at one or several specific dissolution time points, or Case 2: the three parameters of the Weibull function describing the full profile at the tablet or batch or run average level. The dissolution variables are augmented with the measured API Content-by-NIR of the tablet to form the multivariate response vector in the process model. Then a conditional regression of the dissolution variables given API Content-by-NIR content and process parameters settings in the second step yields a predictive surrogate model of the dissolution variables. In the first case, the surrogate model directly yields predictions of the in vitro release measurement at the specific time point(s). In the second case, Weibull parameters are predicted, yielding a mean dissolution prediction at any time point on the dissolution profile. The Bayesian estimation approach to the conditional regression model permits simulations that can characterize the analytical performance of the surrogate model with respect to accuracy and precision for model qualification purposes. Two examples are given which show the statistical modeling details of both cases.

In this paper a graph transformation system with the parallel derivation is used to model the process of distribution and adaptation for computer aided design. It is based on earlier research in formal language theory, especially graph grammars, and distributed models. The motivation for the ideas presented here is given and possible ways of application are described. A connection to the multi-agent model is also presented.

A rich concurrent semantics has been developed along the years for graph transformation systems, often generalizing in non-trivial ways concepts and results fist introduced for Petri nets. Besides the theoretical elegance, the concurrent semantic has potential applications in verification, e.g. in partial order reduction or in the use of finite prefixes of the unfolding for model checking. In practice (graph) transformation systems are often equipped with Negative Application Conditions, that describe forbidden contexts for the application of a rule. The talk will summarize some recent results showing that if the NACs are sufficiently simple (“incremental”) the concurrent semantics lifts smoothly to systems with NACs, but the general case requires original definitions and intuitions. Joint work with Reiko Heckel, Frank Hermann, Susann Gottmann and Nico Nachtigall

In the framework of graph transformation systems with Negative Application Conditions (NACs) the classical notion of switch equivalence of derivations is extended to permutation equivalence, because there are intuitively equivalent derivations which are not switch-equivalent if NACs are considered. By definition, two derivations are permutation-equivalent, if they respect the NACs and disregarding the NACs they are switch equivalent. A direct analysis of permutation equivalence is very complex in general, thus we propose a much more efficient analysis technique. For this purpose, we construct a Place/Transition Petri net, called dependency net, which encodes the dependencies among rule applications of the derivation, including the inhibiting effects of the NACs. The analysis of permutation equivalence is important for analysing simulation runs within development environments for systems modelled by graph transformation. The application of the technique is demonstrated by a graph transformation system within the context of workflow modelling. We show the effectiveness of the approach by comparing the minimal costs of a direct analysis with the costs of the efficient analysis applied to a derivation of our example system.

Graph states are key resources for measurement-based quantum computing, which is particularly promising for photonic systems. Fusions are probabilistic Bell state measurements, measuring pairs of parity operators of two qubits. Fusions can be used to connect/entangle different graph states, making them a powerful resource for measurement-based and related fusion-based quantum computing. There are several different graph structures and types of Bell state measurements, yet the associated graph transformations have only been analyzed for specific cases. Here, we provide a full set of graph transformation rules and give an intuitive visualization based on Venn diagrams of local neighborhoods of graph nodes. We derive these graph transformations for all types of rotated type-II fusion, showing that there are five different fusion success cases. Finally, we give application examples of the derived graph transformation rules and show that they can be used to construct graph codes or simulate fusion networks.

Background: Talazoparib (TALA; 1 mg/d) was well tolerated and exhibited promising antitumor activity in ABRAZO, a 2-cohort, 2-stage, open-label phase 2 study (NCT02034916) in patients (pts) with locally advanced or metastatic breast cancer and gBRCA1/2 mutations following platinum-based therapy (cohort 1 [C1]) or ≥3 platinum-free cytotoxic-based regimens (cohort 2 [C2]). This analysis evaluates health-related quality of life (QoL) for both cohorts. Methods: QoL was assessed on day 1 (baseline) and every 6 weeks for the initial 24 weeks and every 12 weeks thereafter, or sooner if progression was clinically suspected, using the EORTC QLQ-C30 and its breast cancer module, QLQ-BR23. For all scales, results were summarized using descriptive statistics for each cohort and at each time point, based on Characters (max 3400 including title, body and table [including spaces]): 3363 No abbreviations in title; title sentence case; define acronyms; no figures Category: Psychosocial, QOL, and Educational Aspects – Other 2 observed values and changes from baseline (clinically meaningful defined as ≥10-point change from baseline). Time to deterioration (TTD; defined as ≥10-point decrease in global health status [GHS]/functional scales or increase in symptom scales) analyses using survival analysis methods were carried out on the GHS/functional scales of QLQ-C30 and symptom scales of QLQ-BR23. Results:GHS was maintained from baseline across all time points for both C1 and C2 except at week 24 in C2, when a statistically significant but not clinically meaningful improvement in GHS was observed. In C1, statistically significant and clinically meaningful improvement was observed at specific time points in 4 functional scales (body image, week 6; sexual functioning, week 24; sexual enjoyment, week 36; and future perspective, weeks 6, 18, and 24) and in 3 symptom scales (dyspnea, week 24; insomnia, week 24; and breast symptoms, weeks 6 and 36). Statistically significant and clinically meaningful deterioration in C1 was observed in 2 functional scales (emotional functioning, week 12 and end of treatment, and role functioning, end of treatment) and in 1 symptom scale (fatigue, week 6). In C2, statistically significant and clinically meaningful improvement was observed at specific time points in 4 functional scales (role functioning, week 24; social functioning, week 24; sexual enjoyment, week 18; and future perspective, weeks 6, 12, and 18) and in 5 symptom scales (nausea/vomiting, week 18; pain, weeks 12, 18, and 24; insomnia, week 24; breast symptoms, weeks 12 and 18; and arm symptoms, week 48). For C2, no statistically significant and clinically meaningful deterioration was observed for any functional or symptoms scales across all time points, except in the dyspnea symptom scale at week 18. For C1 and C2, the median (95% confidence interval) TTD of GHS was 2.8 (2.1-3.0) and 5.5 (4.2-5.7) months, respectively. The median TTD for all QLQ-C30 functional scales for C1 and C2 ranged 2.1-3.1 and 4.2-5.6 months, respectively; the median TTD for all QLQ-BR23 symptoms scales ranged 2.6-4.0 and 4.2-5.6 months, respectively. Conclusions: The QoL of TALA-treated patients during ABRAZO was maintained. QoL is being evaluated among atients with germline BRCA1/2 mutated advanced BC treated with TALA vs physician's choice chemotherapy in the phase 3 EMBRACA trial (NCT01945775). Citation Format: Hurvitz SA, Turner NC, Telli ML, Rugo HS, Mailliez A, Ettl J, Grischke E-M, Mina LA, Balmaña J, Fasching PA, Tudor C, Quek RGW, Hannah AL, Robson ME, Wardley AM. Health-related quality of life during a phase 2 study of talazoparib in patients with advanced breast cancer and germline BRCA1/2 mutations (ABRAZO) [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-19-05.

Scenario-driven analysis of systems specified through graph transformations

Purpose: The aim of the study was to establish the moderating effect of project environment on the relationship between constrained programming and project outcomes in United Nations Agencies in Kenya.Methodology: A cross sectional survey is a method that involves the analysis of data collected from a population, or a representative subset, at one specific point in time (Orodho, 2011). This design is used to gather data on more than one case at a single point in time in order to collect a body of quantitative data in connection to the variables. The study picked data for projects and sought to investigate the concept trends and status of project outcomes at a particular period (2014-2018).Results: The results indicated that the geographical environment affect project outcomes (4.565); Social Cultural environment inhibit project outcomes (3.875); Beliefs and traditions affect project outcomes (4.670); Political instability hinders success of project outcomes (3.734) and technological changes affect project outcomes (3.713). The findings revealed the moderating effect of project environment on the relationship between constrained programming and project outcomes in UN agencies in Kenya.Contribution to policy, practice and theory: Humanitarian projects should realize that in the present project environment, constrained programming forms an important element of intangible assets of the UN agencies. These should be reconfigured to ensure that the projects seize opportunities, are proactive in the market place, make new product and process innovations.