Agile practices adoption with Lean in growing entrepreneur companies

Abstract. There are three popular terms in the software development industry recently, they are Agile, Lean and Entrepreneurs. Agile is an approach in which requirements and solutions for the products evolve through short cycles. Entrepreneur can be defined as the process of designing, launching and running a new business based on potential opportunities and often is a small business. In recent years, entrepreneurs firms follow Lean concepts in Information Technology industry are trying to adopt Agile methodologies because they believe it helps them to avoid failures and grow faster. However, when growing they often face problems to maintain the agility which they have when they were smaller. The aim of this study is to find out approaches and lessons which can be used to adopt Agile practices in young expanding firms. In addition, those methods were compared to those from large-scale Agile frameworks to give conclusions on adoption approaches. Three interviews were conducted with the high-level managers of target case companies and two of them based in Oulu, Finland and one located in Hanoi, Vietnam. All of the companies which joined the research are working software development area but each of them has a different pathway and side services. They also share are similar numbers of employees above 9 and smaller than 30, which is the reason that they were chosen. Another reason for this selection is that all of them called themselves a Lean start-up or following core concepts of it. On another hand, large-scale Agile frameworks were introduced as an approach for big organizations to adopt Agile practices. In this research, lessons from those frameworks were proposed as suggestions and a new point of view for maintaining agility. The results of the research can be concluded that focusing on customer requirements, forming small Agile teams and giving more freedom to members are three practices that companies in the interview are using. Furthermore, from designed frameworks, it showed that having dynamic teams, enhancing the value of each iteration and improving the training process are ways to improve the adoption process in large firms

Electronic structure of Zr-Ni-Sn systems: role of clustering and nanostructures in Half-Heusler and Heusler limits

Half-Heusler and Heusler compounds have been of great interest for several decades for thermoelectric, magnetic, half-metallic and many other interesting properties. Among these systems, Zr-Ni-Sn compounds are interesting thermoelectrics which can go from semiconducting half-Heusler (HH) limit, ZrNiSn, to metallic Heusler (FH) limit, ZrNi$_2$Sn. Recently Makogo et al. [J. Am. Chem. Soc. 133, 18843 (2011)] found that dramatic improvement in the thermoelectric power factor of HH can be achieved by putting excess Ni into the system. This was attributed to an energy filtering mechanism due to the formation of FH nanostructures in the HH matrix. Using density functional theory we have investigated clustering and nanostructure formation in HH$_{1-x}$FH$_x$ systems near the HH and FH ends and found that excess Ni atoms in HH tend to stay close to each other and form nanoclusters of FH. On the other hand, there is competing interaction between Ni-vacancies in FH which prevent them from forming HH nano clusters. Effects of nano inclusions on the electronic structure at both HH and FH ends will be discussed.Comment: Published in J. Phys.: Condens. Matte

Health data in cloud environments

The process of provisioning healthcare involves massive healthcare data which exists in different forms on disparate data sources and in different formats. Consequently, health information systems encounter interoperability problems at many levels. Integrating these disparate systems requires the support at all levels of a very expensive infrastructures. Cloud computing dramatically reduces the expense and complexity of managing IT systems. Business customers do not need to invest in their own costly IT infrastructure, but can delegate and deploy their services effectively to Cloud vendors and service providers. It is inevitable that electronic health records (EHRs) and healthcare-related services will be deployed on cloud platforms to reduce the cost and complexity of handling and integrating medical records while improving efficiency and accuracy. The paper presents a review of EHR including definitions, EHR file formats, structures leading to the discussion of interoperability and security issues. The paper also presents challenges that have to be addressed for realizing Cloudbased healthcare systems: data protection and big health data management. Finally, the paper presents an active data model for housing and protecting EHRs in a Cloud environment

Exact one-loop results for li→ljγl_i \to l_j\gamma in 3-3-1 models

We investigate the decays $l_i\rightarrow l_j \gamma$, with $l_i=e,\mu,\tau$ in a general class of 3-3-1 models with heavy exotic leptons with arbitrary electric charges. We present full and exact analytical results keeping external lepton masses. As a by product, we perform numerical comparisons between exact results and approximate ones where the external lepton masses are neglected. As expected, we found that branching fractions can reach the current experimental limits if mixings and mass differences of the exotic leptons are large enough. We also found unexpectedly that, depending on the parameter values, there can be huge destructive interference between the gauge and Higgs contributions when the gauge bosons connecting the Standard Model leptons to the exotic leptons are light enough. This mechanism should be taken into account when using experimental constraints on the branching fractions to exclude the parameter space of the model.Comment: 27 pages, 5 figures, 4 tables; additional explanation on input parameters; matches journal versio

Adversarial Attacks on Code Models with Discriminative Graph Patterns

Pre-trained language models of code are now widely used in various software engineering tasks such as code generation, code completion, vulnerability detection, etc. This, in turn, poses security and reliability risks to these models. One of the important threats is \textit{adversarial attacks}, which can lead to erroneous predictions and largely affect model performance on downstream tasks. Current adversarial attacks on code models usually adopt fixed sets of program transformations, such as variable renaming and dead code insertion, leading to limited attack effectiveness. To address the aforementioned challenges, we propose a novel adversarial attack framework, GraphCodeAttack, to better evaluate the robustness of code models. Given a target code model, GraphCodeAttack automatically mines important code patterns, which can influence the model's decisions, to perturb the structure of input code to the model. To do so, GraphCodeAttack uses a set of input source codes to probe the model's outputs and identifies the \textit{discriminative} ASTs patterns that can influence the model decisions. GraphCodeAttack then selects appropriate AST patterns, concretizes the selected patterns as attacks, and inserts them as dead code into the model's input program. To effectively synthesize attacks from AST patterns, GraphCodeAttack uses a separate pre-trained code model to fill in the ASTs with concrete code snippets. We evaluate the robustness of two popular code models (e.g., CodeBERT and GraphCodeBERT) against our proposed approach on three tasks: Authorship Attribution, Vulnerability Prediction, and Clone Detection. The experimental results suggest that our proposed approach significantly outperforms state-of-the-art approaches in attacking code models such as CARROT and ALERT

Histolocalization and physico-chemical characterization of dihydrochalcones: Insight into the role of apple major flavonoids

Flavonoids, like other metabolites synthesized via the phenylpropanoid pathway, possess a wide range of biological activities including functions in plant development and its interaction with the environment. Dihydrochalcones (mainly phloridzin, sieboldin, trilobatin, phloretin) represent the major flavonoid subgroup in apple green tissues. Although this class of phenolic compounds is found in very large amounts in some tissues (≈200 mg/g of leaf DW), their physiological significance remains unclear. In the present study, we highlight their tissue-specific localization in young growing shoots suggesting a specific role in important physiological processes, most notably in response to biotic stress. Indeed, dihydrochalcones could constitute a basal defense, in particular phloretin which exhibits a strong broad-range bactericidal and fungicidal activity. Our results also indicate that sieboldin forms complexes with iron with strong affinity, reinforcing its antioxidant properties and conferring to this dihydrochalcone a potential for iron seclusion and/or storage. The importance of localization and biochemical properties of dihydrochalcones are discussed in view of the apple tree defense strategy against both biotic and abiotic stresses