Showing papers on "Enterprise software published in 2018"

Coordination Challenges in Large-Scale Software Development: A Case Study of Planning Misalignment in Hybrid Settings

Abstract: Achieving effective inter-team coordination is one of the most pressing challenges in large-scale software development. Hybrid approaches of traditional and agile development promise combining the overview and predictability of long-term planning on an inter-team level with the flexibility and adaptability of agile development on a team level. It is currently unclear, however, why such hybrids often fail. Our case study within a large software development unit of 13 teams at a global enterprise software company explores how and why a combination of traditional planning on an inter-team level and agile development on a team level can result in ineffective coordination. Based on a variety of data, including interviews with scrum masters, product owners, architects and senior management, and using Grounded Theory data analysis procedures, we identify a lack of dependency awareness across development teams as a key explanation of ineffective coordination. Our findings show how a lack of dependency awareness emerges from misaligned planning activities of specification, prioritization, estimation and allocation between agile team and traditional inter-team levels and ultimately prevents effective coordination. Knowing about these issues, large-scale hybrid projects in similar contexts can try to better align their planning activities across levels to improve dependency awareness and in turn achieve more effective coordination.

Platform Sponsor Investments and User Contributions in Knowledge Communities:: The Role of Knowledge Seeding

Abstract: How should digital platforms engage with and invest in their online communities to shape innovation and knowledge contributions from members in their platform ecosystems? This is an important question because user contributions are important drivers of technological progress and business value. We examine the effect of platform sponsors’ investments in online communities on user knowledge contributions, using fine-grained longitudinal data from a leading enterprise software vendor’s community network. We focus on the sponsor practice of knowledge seeding, in which its employees provide free technical support by answering questions posted in discussion forums. We define user knowledge contribution as peer-evaluated, quality-weighted solutions that community members provide to help resolve the questions their peers raise. We show that the platform sponsor’s investments in knowledge seeding have a positive, significant association with user knowledge contribution. We also find temporal and geographical variations in returns on the sponsor’s knowledge investments. Specifically, returns (i.e., amount of user contribution that is stimulated) decrease with the age of the community, consistent with the observation that the most active contributors are lead users who tend to join the community early. In addition, returns vary across different countries, such that greater returns are realized when the investment is made in countries with higher levels of information technology (IT) infrastructure, partly because country-level IT infrastructure may be associated with greater absorptive capacity of these countries. We discuss the implications for research and practice.

A methodology to create a sensing, smart and sustainable manufacturing enterprise

Abstract: Next-generation manufacturing enterprises need to be sensing, smart and sustainable to be competitive: ‘sensing’ refers to context awareness at internal and external levels; ‘smart’ refers to knowledge-based organisations that adapt to changes and ‘sustainable’ refers to the ability to operate without damaging the environment, community or economy. Although technologies do exist to support the development of such enterprises, there is a need for methodologies that help in the entire enterprise engineering problem. This paper proposes a methodology, based on the principles of enterprise architecture, to design a sensing, smart and sustainable manufacturing enterprise. The methodology aims at adopting the best practices used in enterprise engineering while dealing with the relevant gaps. An analysis of the characteristics of the ‘Sensing, Smart and Sustainable Manufacturing Enterprise’ (S3-ME) is presented to understand the advantages of using the proposed methodology. The methodology comprises the instanti...

Optimal Distribution Strategy for Enterprise Software: Retail, SaaS, or Dual Channel?

Abstract: While the optimal distribution channel strategy of physical goods has been extensively studied, there is a lack of research for that of enterprise software as a digital good. This research analyzes the optimal distribution strategy of enterprise software by taking into account the distinct features of enterprise software for both the short‐run problem, in which the software quality is fixed, and the long‐run problem, in which the software quality becomes part of the strategic decisions. Our results indicate that in the presence of high unfit cost relative to the customization cost, the dual channel strategy exists and generates the highest profit for the firm and the highest social welfare. When the unfit cost is low relative to the customization cost, the SaaS channel strategy becomes the best strategy for both the firm in terms of profitability and society in terms of social welfare. This key finding is robust in that it holds for both the short‐run problem and the long‐run problem.

Architectural Coordination of Enterprise Transformation

Abstract: Architectural coordination of enterprise transformation (ACET) integrates and aggregates local information and provides different viewpoints, such as financial, structural, or skill perspectives to the respective stakeholder groups, with the aim of creating a consensus and shared understanding of an enterprise transformation among the stakeholders. Its core purpose is to inform decision-makers with both local and enterprise-wide concerns so that the overall transformation goals can be successfully pursued, i.e. reducing inconsistencies and including local decisions in the overarching goals. This book consists of three major parts, framed by an introduction and a summary. To enable readers to gain a better understanding of the issues involved in real-world enterprise transformations as well as the possible role of architectural coordination and the associated challenges, Part I provides an analysis of status quo of corporate ACET practice. Part II then continues with an exploration of the challenges facing ACET from a theoretical perspective. Based on these challenges, Part III then presents a collection of components for a possible design theory for ACET. Instead of an integrated method, this collection of components constitutes method fragments that can be arranged in different ways depending on the perspective taken, the actual enterprise architecture management approach, the enterprise transformation type and the transformation’s context.

Intelligent collaborative system and service in value network for enterprise computing

Abstract: Recently, competitive environment for enterprise computing is being mixed with increased uncertainty of supply and demand, globalised markets, shortening of product’s life cycle, rapid change of pr...

Trustworthiness in Enterprise Crowdsourcing: a Taxonomy & evidence from data

Abstract: In this paper we study the trustworthiness of the crowd for crowdsourced software development. Through the study of literature from various domains, we present the risks that impact the trustworthiness in an enterprise context. We survey known techniques to mitigate these risks. We also analyze key metrics from multiple years of empirical data of actual crowdsourced software development tasks from two leading vendors. We present the metrics around untrustworthy behavior and the performance of certain mitigation techniques. Our study and results can serve as guidelines for crowdsourced enterprise software development.

Evaluating cloud database migration options using workload models

Abstract: A key challenge in porting enterprise software systems to the cloud is the migration of their database. Choosing a cloud provider and service option (e.g., a database-as-a-service or a manually configured set of virtual machines) typically requires the estimation of the cost and migration duration for each considered option. Many organisations also require this information for budgeting and planning purposes. Existing cloud migration research focuses on the software components, and therefore does not address this need. We introduce a two-stage approach which accurately estimates the migration cost, migration duration and cloud running costs of relational databases. The first stage of our approach obtains workload and structure models of the database to be migrated from database logs and the database schema. The second stage performs a discrete-event simulation using these models to obtain the cost and duration estimates. We implemented software tools that automate both stages of our approach. An extensive evaluation compares the estimates from our approach against results from real-world cloud database migrations.

Beyond ERP systems: an outline of self-referential enterprise systems

Abstract: While it is widely agreed that current enterprise resource planning (ERP) systems cannot evolve much further, it is the question how future enterprise systems will look like. To approach an answer to this question, this report provides at first an analysis of essential high level requirements and their implications. Against this background, a conception of future enterprise systems referred to as self‐referential enterprise systems (SRES) is presented. It is characterized by an elaborate conceptual foundation, which is based on multi‐perspective enterprise models. These models enable enterprise software to not only refer to their conceptual foundation, but also to the concepts that characterize the context they are embedded in. In order to promote cross‐organizational integration and high‐level reuse, it is suggested to develop reference models, which provide design blueprints for an entire range of organizations. While the development of reference models and the realization of corresponding SRES is a very attractive research vision, it overextends the resources of single research institutions by far. It also requires involving prospective users. To cope with these challenges, the paper suggests a conception of collaborative development of open reference models. It concludes with the description of the recently launched “Open Model” initiative that is aimed at promoting the joint development of large conceptual models which could serve as a foundation of future SRES.

Machine learning-based run-time anomaly detection in software systems: An industrial evaluation

Abstract: Anomalies are an inevitable occurrence while operating enterprise software systems. Traditionally, anomalies are detected by threshold-based alarms for critical metrics, or health probing requests. However, fully automated detection in complex systems is challenging, since it is very difficult to distinguish truly anomalous behavior from normal operation. To this end, the traditional approaches may not be sufficient. Thus, we propose machine learning classifiers to predict the system's health status. We evaluated our approach in an industrial case study, on a large, real-world dataset of 7.5 • 106 data points for 231 features. Our results show that recurrent neural networks with long short-term memory (LSTM) are more effective in detecting anomalies and health issues, as compared to other classifiers. We achieved an area under precision-recall curve of 0.44. At the default threshold, we can automatically detect 70% of the anomalies. Despite the low precision of 31 %, the rate in which false positives occur is only 4 %.

Deep customization of multi-tenant SaaS using intrusive microservices

Abstract: Enterprise software needs to be customizable, and the customization needs from a customer are often beyond what the software vendor can predict in advance. In the on-premises era, customers do deep customizations beyond vendor's prediction by directly modifying the vendor's source code and then build and operate it on their own premises. When enterprise software is moving to cloud-based multi-tenant SaaS (Software as a Service), it is no longer possible for customers to directly modify the vendor's source code, because the same instance of code is shared by multiple customers at runtime. Therefore, the question is whether it is still possible to do deep customization on multi-tenant SaaS. In this paper, we give an answer to this question with a novel architecture style to realize deep customization of SaaS using intrusive microservices. We evaluate the approach on an open source online commercial system, and discuss the further research questions to make deep customization applicable in practice.

A Catalogue of Architectural Decisions for Designing IIoT Systems

Abstract: Designing Industrial IoT (IIoT) systems enforces new sets of architectural decisions on software/system architects Although a rich set of materials for architecting enterprise software systems exist, there is a lack of reference documents on architectural decisions and alternatives that architects face to design IIoT systems Based on our experience in designing IIoT systems in various domains such as process automation, discrete manufacturing and building automation, we provide a catalogue of architectural decisions, their impacts on the quality attributes of systems, and technology options to realize each design alternative

The App Store Model for Enterprise Application Software

Abstract: App stores in the consumer software market are omnipresent and have significantly changed the way how software is being produced, marketed, and consumed. Enterprise software customers also demand higher flexibility in buying and adopting standardized enterprise application software - and new technologies such as cloud computing and highly efficient development platforms provide new options for software vendors and the entire software value chain. This application-oriented work researches the challenge of establishing the app store model for enterprise application software as a technology-driven business model in a two-sided platform ecosystem. The author analyzes the topic comprehensively from the software buyer’s, the software provider’s and the platform provider’s perspective and uncovers detailed insights on barriers, drivers, and constraints. Moreover he proposes solutions on the level business processes and detailed requirements. His research is highly interdisciplinary and utilizes both empirical qualitative and design-oriented methods.

State of the practice in service identification for SOA migration in industry

Abstract: The migration of legacy software systems to Service Oriented Architectures (SOA) has become a mainstream trend for modernizing enterprise software systems. A key step in SOA migration is the identification of services in the target application, but it is a challenging one to the extent that the potential services (1) embody reusable functionalities, (2) can be developed in a cost-effective manner, and (3) should be easy to maintain. In this paper, we report on state of the practice of SOA migration in industry. We surveyed 45 practitioners of legacy-to-SOA migration to understand how migration, in general, and service identification (SI), in particular are done. Key findings include: (1) reducing maintenance costs is a key driver in SOA migration, (2) domain knowledge and source code of legacy applications are most often used respectively in a hybrid top-down and bottom-up approach for SI, (3) industrial SI methods focus on domain services–as opposed to technical services, (4) there is very little automation of SI in industry, and (5) RESTful services and microservices are the most frequent target architectures. We conclude with a set of recommendations and best practices.

Using multi-attribute decision-making approaches in the selection of a hospital management system.

Abstract: The most appropriate organizational software is always a real challenge for managers, especially, the IT directors. The illustration of the term "enterprise software selection", is to purchase, create, or order a software that; first, is best adapted to require of the organization; and second, has suitable price and technical support. Specifying selection criteria and ranking them, is the primary prerequisite for this action. This article provides a method to evaluate, rank, and compare the available enterprise software for choosing the apt one. The prior mentioned method is constituted of three-stage processes. First, the method identifies the organizational requires and assesses them. Second, it selects the best method throughout three possibilities; indoor-production, buying software, and ordering special software for the native use. Third, the method evaluates, compares and ranks the alternative software. The third process uses different methods of multi attribute decision making (MADM), and compares the consequent results. Based on different characteristics of the problem; several methods had been tested, namely, Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Elimination and Choice Expressing Reality (ELECTURE), and easy weight method. After all, we propose the most practical method for same problems.

Testing Service Oriented Architectures Using Stateful Service Virtualization via Machine Learning

Abstract: Today's enterprise software systems are much complicated than the past. Increasing number of dependent applications, heterogeneous technologies and wide usage of Service Oriented Architectures (SOA), where numerous services communicate with each other, makes testing of such systems challenging. For testing these software systems, the concept of service virtualization is gaining popularity. Service virtualization is an automated technique to mimic the behavior of a given real service. Services can be classified as stateless or stateful services. Many services are stateful in nature. Although there are works in the literature for virtualization of state-less services, no such solution exists for stateful services. To the best of our knowledge, this is the first work for stateful service virtualization. We employ classification based and sequence-to-sequence based machine learning algorithms in developing our solutions. We demonstrate the validity of our approach on two data sets collected from real life services and obtain promising results.

A constraint-logic object-oriented language

Abstract: Object-oriented (OO) programming languages prevail in the development of enterprise software, but they do not particularly support the implementation of software which includes solving complicated search problems with dynamically appearing constraints, e. g. as found in logistics. Such problems could be tackled by implementing the main business logic in e. g. Java and the search in a constraint-logic language. However, integrating both aspects is clumsy. Thus, we propose the constraint-logic OO language Muli. It facilitates an integrated implementation of applications that use both aspects. Muli extends Java by logic variables and encapsulated search. Its implementation is based on a symbolic Java virtual machine and constraint solvers. Outside of search regions, Muli behaves just like Java. We motivate the benefits of integrating object-oriented programming and constraint-logic programming and introduce concepts that are required to achieve a seamless integration. We also describe our implementation of these concepts and discuss our approach.

Multihoming within Platform Ecosystems: The Strategic Role of Human Capital

Abstract: Platform ecosystems characterized by a few platform owners and numerous other complementor firms that partner with them have become quite common across industries. Even though there has been considerable research on platform ecosystems, attention has mostly been on the platform owners and their strategies. In this paper, we focus on the complementor firms and try to understand the phenomenon of multihoming, a strategy in which a complementor firm chooses to join multiple platforms rather than one. We build a micro-foundational capability framework based on human capital and test it on a novel dataset from the ERP platform ecosystem. The study has implications for our understanding of platform growth and innovation and contributes toward the literature on platform ecosystems as well as strategic human capital.

Algebra for Enterprise Ontology: towards analysis and synthesis of enterprise models

Abstract: ABSTRACT Enterprise modeling methodologies have made enterprises more likely to be the object of systems engineering rather than craftsmanship. However, the current state of research in enterprise modeling methodologies lacks investigations of the mathematical background embedded in these methodologies. Abstract algebra, a broad subfield of mathematics, and the study of algebraic structures may provide interesting implications in both theory and practice. Therefore, this research gives an empirical challenge to establish an algebraic structure for one aspect model proposed in Design & Engineering Methodology for Organizations (DEMO), which is a major enterprise modeling methodology in the spotlight as a modeling principle to capture the skeleton of enterprises for developing enterprise information systems. The results show that the aspect model behaves well in the sense of algebraic operations and indeed constructs a Boolean algebra. This article also discusses comparisons with other modeling languages and suggests future work.

Using Intrusive Microservices to Enable Deep Customization of Multi-tenant SaaS

Abstract: Enterprise software applications need to be customized in order to meet special requirements from customers. When the customization requirements are beyond the prediction of vendors, deep customization is needed, and traditionally customers do deep customizations by directly modifying the application source code. When the applications are moving from on-premises to multi-tenant Software as a Service, directly changing code is not feasible because many customers are sharing one instance of the application code. In this paper, we present a new approach to enable deep customization on multi-tenant SaaS, using intrusive microservices. The custom code is implemented as an isolated and self-contained microservice running beside the main service, and it uses callback code to intrusively execute queries or commands inside the main service. We present the key techniques behind intrusive microservices and illustrate how turned an open source online shopping application into a deeply customizable multi-tenant service.

Identifying Needs for a Holistic Modelling Approach to Privacy Aspects in Enterprise Software Systems

Abstract: Modelling is a common method for both Business Architecture Management and for Software Architecture Management. In general, there is a gap in the model continuity between business models and software models. Especially when modelling compliance driven requirements like privacy traceability is important for compliance checks and helps to build the models in an efficient way. In this paper, approaches for modelling privacy from business and software engineering perspective are examined. A key finding is that there is currently no comprehensive modelling approach covering the needed aspects and perspectives.

An Approach for Guiding Developers to Performance and Scalability Solutions

Abstract: The quality of enterprise software applications plays a crucial role for the satisfaction of the users and the economic success of the enterprises. Software applications with unsatisfying performance and scalability are perceived by its users as low in quality, as less interesting and less attractive, and cause frustration when preventing the users from attaining their goals. This book proposes an approach for a recommendation system that enables developers who are novices in software perform Umfang: XV, 359 S. Preis: €47.00 | £43.00 | $83.00

An Analytical Study of Methodologies and Tools for Enterprise Information Security Risk Management

Abstract: An enterprise is characterized by its business processes and supporting ICT infrastructure. Securing these entities is of utmost importance for the survival of an enterprise and continuity of its business operations. In order to secure them, it is important to first detect the risks that can be realized to cause harm to those entities. Over the years, several kinds of security risk analysis methodologies have been proposed. They cater to different categories of enterprise entities and consider varying levels of detail during risk analysis. An enterprise often finds it difficult to select a particular method that will best suit its purpose. This paper attempts to address this problem by presenting a detailed study of existing risk analysis methodologies. The study classifies them into specific categories and performs comparative analyses considering different parameters addressed by the methodologies, including asset type, vulnerabilities, threats, and security controls. An Analytical Study of Methodologies and Tools for Enterprise Information Security Risk Management

Methods and Systems for providing a platform for Code-Free Blockchain Application and Smart Contract Development

Abstract: The enterprise software market is massive, with a forecasted $200 bln to be spent on application integrations by 2019. On average, enterprises deal with dozens, if not hundreds of disparate and isolated custom applications and software service providers to satisfy their needs. Blockchains bear hope for a more interoperable future, with ecosystems founded on open source protocols that allow companies to quickly engage in financial applications, supply chain management and other core services without fracturing business processes across a multitude of applications and software providers. Embodiments of the present invention address these and/or other needs by providing an innovative platform that allows enterprises to develop and deploy Blockchain Applications and Smart Contract visually without code. Embodiments of the present invention will enable enterprises to execute their business processes and extract value from the collective utility of fully interoperable public and private Blockchains and/or will be able to build everything from smart contracts to UI to integration visually without code.

Enterprise Requirements Management Knowledge Towards Digital Transformation

Abstract: As the enterprise services are rapidly digitized by digital transformation, the need to integrated knowledge management of IT requirements and business requirements is increased.

A process for distributed software evolution: a proprietary software case study

Abstract: Proprietary enterprise software is commonly embedded in multinational organizations and therefore has multiple sources of global or local demand. This type of software is subject to constant evolutions motivated by improvements in the features or by changes in the legal and economic context of its environment. Problems arising from the demand for requirements are associated with the suitability of a particular local requirement to its global context, for example: tax rules are characteristic of a specific country while a business rule can achieve every global structure. In addition, software customization can be implemented by the software producer, external partners, programmers allocated within the customer company, and so on. The coordination of this scenario is considered critical for the productive sector company that uses proprietary enterprise software. If the software does not evolve, the company processes can be temporarily compromised, and the software becomes obsolete. We report a case study of a large proprietary ERP system in a multinational company located in Brazil that is among the three largest exporters in its market segment. As a contribution, we present the current structure of the distributed evolution process of the software in question and how the stakeholder coordination of this scenario occurs.

Mining the Ground Truth of Enterprise Toolchains

Abstract: Data on organizations’ use of agile and DevOps tools provides the ground truth of enterprise software delivery.

Single stage prediction with embedded topic modeling of online reviews for mobile app management

Abstract: Mobile apps are one of the building blocks of the mobile digital economy. A differentiating feature of mobile apps to traditional enterprise software is online reviews, which are available on app marketplaces and represent a valuable source of consumer feedback on the app. We create a supervised topic modeling approach for app developers to use mobile reviews as useful sources of quality and customer feedback, thereby complementing traditional software testing. The approach is based on a constrained matrix factorization that leverages the relationship between term frequency and a given response variable in addition to co-occurrences between terms to recover topics that are both predictive of consumer sentiment and useful for understanding the underlying textual themes. The factorization is combined with ordinal regression to provide guidance from online reviews on a single app’s performance as well as systematically compare different apps over time for benchmarking of features and consumer sentiment. We apply our approach using a dataset of over 100,000 mobile reviews over several years for three of the most popular online travel agent apps from the iTunes and Google Play marketplaces.

The Case for Microservices

Abstract: Enterprise software architecture always evolves with new architectural styles. These are paradigm shifts in the technology, coupled with the desire to find better ways to build software application in a fast but reliable way.