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Blockchain technology offers a sizable promise to rethink the way interorganizational business processes are managed because of its potential to realize execution without a central party serving as a single point of trust (and failure). To stimulate research on this promise and the limits thereof, in this article, we outline the challenges and opportunities of blockchain for business process management (BPM). We first reflect how blockchains could be used in the context of the established BPM lifecycle and second how they might become relevant beyond. We conclude our discourse with a summary of seven research directions for investigating the application of blockchain technology in the context of BPM.

Graph deep learning models, such as graph convolutional networks (GCN) achieve remarkable performance for tasks on graph data. Similar to other types of deep models, graph deep learning models often suffer from adversarial attacks. However, compared with non-graph data, the discrete features, graph connections and different definitions of imperceptible perturbations bring unique challenges and opportunities for the adversarial attacks and defenses for graph data. In this paper, we propose both attack and defense techniques. For attack, we show that the discreteness problem could easily be resolved by introducing integrated gradients which could accurately reflect the effect of perturbing certain features or edges while still benefiting from the parallel computations. For defense, we observe that the adversarially manipulated graph for the targeted attack differs from normal graphs statistically. Based on this observation, we propose a defense approach which inspects the graph and recovers the potential adversarial perturbation. Our experiments on a number of datasets show the effectiveness of the proposed methods.

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Context: Continuous practices, i.e., continuous integration, delivery, and deployment, are the software development industry practices that enable organizations to frequently and reliably release new features and products. With the increasing interest in and literature on continuous practices, it is important to systematically review and synthesize the approaches, tools, challenges, and practices reported for adopting and implementing continuous practices.Objective: This research aimed at systematically reviewing the state of the art of continuous practices to classify approaches and tools, identify challenges and practices in this regard, and identify the gaps for future research. Method:We used systematic literature review (SLR) method for reviewing the peer-reviewed papers on continuous practices published between 2004 and 1st June 2016. We applied thematic analysis method for analysing the data extracted from reviewing 69 papers selected using predefined criteria. Results:We have identified thirty approaches and associated tools, which facilitate the implementation of continuous practices in the following ways: (1) -reducing build and test time in continuous integration (CI)‖; (2) -increasing visibility and awareness on build and test results in CI‖; (3) -supporting (semi-) automated continuous testing‖; (4) -detecting violations, flaws and faults in CI‖; (5) -addressing security and scalability issues in deployment pipeline‖, and (6) -improving dependability and reliability of deployment process‖. We have also determined a list of critical factors such as -testing (effort and time)‖, -team awareness and transparency‖, -good design principles‖, -customer‖, -highly skilled and motivated team‖, -application domain‖, and -appropriate infrastructure‖ that should be carefully considered when introducing continuous practices in a given organization. The majority of the reviewed papers were validation (34.7%) and evaluation (36.2%) research types. This review also reveals that continuous practices have been successfully applied to both greenfield and maintenance projects. Conclusion:Continuous practices have become an important area of software engineering research and practice. Whilst the reported approaches, tools, and practices are addressing a wide range of challenges, there are several challenges and gaps which require future research work for: improving the capturing and reporting of contextual information in the studies reporting different aspects of continuous practices; gaining a deep understanding of how software-intensive systems should be (re-) architected to support continuous practices; addressing the lack of knowledge and tools for engineering processes of designing and running secure deployment pipelines.

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Software architecture evaluation has been proposed as a means to achieve quality attributes such as maintainability and reliability in a system. The objective of the evaluation is to assess whether or not the architecture will lead to the desired quality attributes. Recently, there have been a number of evaluation methods proposed. There is, however, little consensus on the technical and non-technical issues that a method should comprehensively address and which of the existing methods is most suitable for a particular issue. This paper presents a set of commonly known but informally described features of an evaluation method and organizes them within a framework that should offer guidance on the choice of the most appropriate method for an evaluation exercise. In this paper, we use this framework to characterise eight SA evaluation methods.