Mature Software Research Articles

Agile Bureaucracy in the Digital Age

In providing public services, the bureaucracy faces challenges of disruption, rapid technological developments, and demands for fast, efficient, and flexible services while it struggles with procedural problems and hierarchy. After bureaucratic reform efforts in Indonesia have been conducted for many years, the apparatus readiness in the local government context to provide fast and responsive services in the digitalisation era and unpredictable situations like pandemics is unexamined. While researchers focus on the use of agile government concept in local government, the assessment of adaptive governance and its implications, and the use of information technology communication in the public sector, in this paper, the authors assess agile bureaucracy in service delivery through digital public services. The results show the software maturity in local bureaus, characterised by their ability to understand user needs for digitalised service and qualified infrastructure tools to support governance. However, agencies face the challenge of weak collaboration with minimal coordination among departments and weak responsibility and adaptability to hinder digital service delivery processes. This article highlights that in adopting the agile concept, bureaucracy requires technological support and the leaders' strong commitment. Moreover, the bureaucracy needs to build a broad and coordinated partnership ecosystem, and the main points are adapting quickly and responsively to problems.

Challenge for Chinese BIM Software Extension Comparison with International BIM Development

This study provides an in-depth analysis of the current status of the promotion and application of BIM software in China, highlighting its differences from the international market. Chinese BIM software shows advantages in data security, cost-effectiveness, user habit adaptability, and localization standards, but faces challenges in terms of technological maturity and ecosystem development. By employing bibliometric methods and utilizing literature resources from CNKI and the Web of Science, the study offers a comprehensive analysis of the market and policy environment and proposes targeted recommendations. The study indicates that Chinese BIM software has significant advantages in enhancing data security and cost-effectiveness but lacks technological maturity and requires improvements in ecosystem development. User habits are crucial for the promotion of BIM software, and the localization and adaptability of the software need further enhancement. To promote the widespread application of BIM in the architecture, engineering, and construction (AEC) industries, a robust market mechanism needs to be established. The government should strengthen policy support and improve regulatory frameworks; software developers should enhance product functionality and work closely with users; and application enterprises should actively provide feedback to promote software improvements. Moreover, the introduction of reasonable capital and the collaboration between educational institutions and enterprises to cultivate professional talent are critical for the promotion and application of BIM technology. The research emphasizes that forming a cross-departmental joint mechanism to promote a virtuous cycle in the AEC market is key to achieving the widespread application of BIM technology. These measures can provide strong market impetus for the development of BIM software, accelerate the maturity and ecosystem construction of Chinese BIM software, and ultimately realize the comprehensive upgrading of informatization and digitization in the construction industry.

LEONARDO

A new pre-exascale computer cluster has been designed to foster scientific progress and competitive innovation across European research systems, it is called LEONARDO. This paper describes thegeneral architecture of the system and focuses on the technologies adopted for its GPU-accelerated partition. High density processing elements, fast data movement capabilities and mature software stack collections allow the machine to run intensive workloads in a flexible and scalable way. Scientific applications from traditional High Performance Computing (HPC) as well as emerging Artificial Intelligence (AI) domains can benefit from this large apparatus in terms of time and energy to solution.

Process mining software engineering practices: A case study for deployment pipelines

Context:In mature software development organizations the ci/cd pipeline is the only route to deploy software into production. While the workflow of this process seems straightforward, the reality is different since exceptions and deviations are the norm in actual industry practice. In this context, Process Mining appears as a promising technique to uncover deviations and check compliance with standardized DevOps processes, and highlight bottlenecks and potential improvement areas. Objective:This paper presents a case study designed to assess the potential of using Process Mining techniques to provide visibility into the deployment pipeline. Method:This research uses raw event data extracted from the continuous practices toolchain, which is then used to compute a comprehensive set of DevOps-specific metrics, thus supporting objective monitoring of the quality and efficiency of the deployment workflow. The study focuses on different development units in the Engineering team, each working in a distinct business context but sharing standard practices. Results:We verified that even though there are standards for the deployment pipelines, each team’s workflow denotes local variations with unique points for improvement that are highly coupled to their business unit context. We observed that each team’s pipeline has different temporal profiles that reflect their context and work practices. Additionally, we identified a set of deployment pipeline metrics focusing on process compliance, efficiency, and deployment stability. Conclusion:The main contributions of this paper include (1) the description of an actual application of Process Mining to the deployment pipeline of a highly complex e-commerce platform, (2) how this approach provided an objective understanding of the efficiency and quality of the development workflow, (3) how this process-centric view, combined with domain-specific DevOps metrics, supports continuous practices, and (4) how Developers can analyse their workflows by applying Process Mining while using standard tools like GitLab and PM4Py.

Application Experiences on a GPU-Accelerated Arm-based HPC Testbed.

This paper assesses and reports the experience of ten teams working to port, validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC Developer Kit systems, each one equipped with a server-class Arm CPU from Ampere Computing and two data center GPUs from NVIDIA Corp. The systems are connected together using InfiniBand interconnect. The selected applications and mini-apps are written using several programming languages and use multiple accelerator-based programming models for GPUs such as CUDA, OpenACC, and OpenMP offloading. Working on application porting requires a robust and easy-to-access programming environment, including a variety of compilers and optimized scientific libraries. The goal of this work is to evaluate platform readiness and assess the effort required from developers to deploy well-established scientific workloads on current and future generation Arm-based GPU-accelerated HPC systems. The reported case studies demonstrate that the current level of maturity and diversity of software and tools is already adequate for large-scale production deployments.

Understanding Post-Stroke Movement by Means of Motion Capture and Musculoskeletal Modeling: A Scoping Review of Methods and Practices

Research of post-stroke locomotion via musculoskeletal (MSK) modeling has offered an unprecedented insight into pathological muscle function and its interplay with skeletal geometry and external stimuli. Advances in solving the dynamical system of post-stroke effort and the generic MSK models used have triggered noticeable improvements in simulating muscle activation dynamics of stroke populations. However, a review of these advancements to inform the scientific community has yet to be made.: PubMed and Scopus databases were used to perform a thorough literature search to identify relevant articles since 2010. Here, we review MSK methods and practices—developed in the last ten years—that have been utilized to explore post-stroke locomotion and examine how their outcomes can inform clinical practice.: Out of the 44 articles that were initially found, 19 were reviewed. The articles were categorized with respect to the type of assessment the MSK methods were used for.: This review notes the considerable competence of existing methods to address post-stroke motion deficits. However, the drawbacks in the implementation of such methods by non-experts due to the high skill demand and the lack of mature software technology for further dissemination of practices and outcomes remain non-trivial.

Research on airworthiness certification of airborne software in civil aircraft compliance verification test

During the development of civil aircraft, in order to verify the compliance of airborne systems with airworthiness regulations, airborne software is used in airworthiness compliance verification tests. It is usually unrealistic for airborne software to complete all certification activities and get approval from authority before the start of compliance verification test, which causes airborne software with intermediate state cannot be directly used in compliance verification test. If the compliance verification test is carried out after the completion of all certification activities of airborne software, the project progress of the whole civil aircraft will be greatly delayed. Based on the actual characteristics of Chinese civil aircraft development project, the requirements of compliance verification test for airborne software are researched from the perspective of software review. Considering the results and confidence of software review, the requirements and criteria of airborne software maturity assessment are formulated, which accelerates the progress of compliance verification test while meeting the requirements of airworthiness regulations and promotes the certification process of civil aircraft project.

Area and shape distortions in open-source discrete global grid systems

ABSTRACT A Discrete Global Grid System (DGGS) is a type of spatial reference system that tessellates the globe into many individual, evenly spaced, and well-aligned cells to encode location and, thus, can serve as a basis for data cube construction. This facilitates integration and aggregation of multi-resolution data from various sources to rapidly calculate spatial statistics. We calculated normalized area and compactness for cell geometries from 5 open-source DGGS implementations - Uber H3, Google S2, RiskAware OpenEAGGR, rHEALPix by Landcare Research New Zealand, and DGGRID by Southern Oregon University - to evaluate their suitability for a global-level statistical data cube. We conclude that the rHEALPix and OpenEAGGR and DGGRID ISEA-based DGGS definitions are most suitable for global statistics because they have the strongest guarantee of equal area preservation - where each cell covers almost exactly the same area on the globe. Uber H3 has the smallest shape distortions, but Uber H3 and Google S2 have the largest variations in cell area. However, they provide more mature software library functionalities. DGGRID provides excellent functionality to construct grids with desired geometric properties but as the only implementation does not provide functions for traversal and navigation within a grid after its construction.

Applied open-source Discrete Global Grid Systems

Abstract. Discrete Global Grid Systems (DGGS) are spatial reference systems that use a hierarchical tessellation of cells to partition and address the globe and provide alternative spatial data format and indexing methods as compared to traditional vector and raster spatial data. In order to effectively use DGGS, functional software needs to be available and data needs to be indexed into a DGGS. We compare the software APIs of the 5 main open-source DGGS implementations – Uber H3, Google S2, rHEALPix by Landcare Research New Zealand, RiskAware OpenEAGGR, and DGGRID by Southern Oregon University – and present exemplary workflows for converting spatial and vector and raster datasets into DGGS-indexed format. We summarize, that Uber H3 and Google S2 provide more mature software library functionalities and DGGRID provides excellent functionality to construct grids with desired geometric properties and to load point data but does not provide functions for traversal and navigation within a grid after its construction.

A Novel Method for Software Reliability Assessment via Neuro-Fuzzy System

Nowadays, the utilization of software engineering in various areas of technology is remarkably increased. As a matter of fact, it is used in many critical applications such as eye surgery, autopilot systems of airplanes, centralized traffic control (CTC), and so on. Therefore, the reliability of software is very important, and it plays an essential role in the lifetime of the software. Software reliability is one of the main characteristics of software quality. Moreover, the rapid assessment of the reliability of the application is essential during the software life cycle. In this paper, Iuse the neuro-fuzzy methods to assess the software's reliability in order to cope with uncertainties in measuring the actual parameters of the software. By designing neuro-fuzzy inference systems and applying four parameters of the ISO/IEC 9126quality model(i.e., the maturity of software, fault-tolerant, recoverability, and reliability compliance) and finding the parameters of a fuzzy system by exploiting approximation techniques from neural networks, Ipresent an integrated assessment model for evaluation of software reliability. The case study used in this paper to evaluate the proposed method is the software income tax calculator. By applying the input parameters, Iobserve that the software reliability is 0.65. software reliability in our proposed method is more exact than software reliability in the fuzzy multi-criteria and fuzzy method because The weights of the input parameters have been set by experts and software developers, and simulations are carried out using MATLAB tool (ANFIS). Simulations confirm that the proposed method provides acceptable results.

Factors impacting BIM application in prefabricated buildings in China with DEMATEL-ISM

PurposeSome papers have investigated the complex factors impacting building information modeling (BIM) application in prefabricated buildings (PBs), but few paid attention to their interaction relationships. Ignoring the fact that different factors are not isolated may lead to some key factors being overlooked without appropriate improvement strategies being proposed. This paper aims to analyze those factors and their inter-relationships, with the view to identify the critical factors and their interaction relationships so as to derive constructive strategies that would effectively facilitate BIM adoption in Chinese prefabrication.Design/methodology/approachFirst, factors influencing BIM application in prefabrication are extracted and collated by literature review, expert interview and analysis of PBs characteristics. Thereafter, an evaluation laboratory (decision-making trial and evaluation laboratory) and interpretive structural modeling are used to explore the relationships and hierarchy among the factors. Based on the degree of cause and centrality, critical factors are extracted and the interaction relationship are investigated.FindingsThe results show that BIM policies and standards for PBs are the main causal factors. The maturity of BIM software and BIM data interface for PBs, willingness to share data, the strategic goals of the enterprise, BIM law and BIM input and benefit are the main transitional factors while BIM staff and workflow, enterprise attitude, distribution of BIM liability and cooperation of participants are the main direct factors.Originality/valueBased on the above findings, corresponding improvement strategies are proposed so as to promote BIM application in prefabrication and the rapid development of China’s PBs efficiently.

Optimization of network sensor node location based on edge coverage control

The increasing maturity of wireless communication technology and computer software has dramatically reduced the cost of embedded devices with functions such as sensing targets, processing data, and communications and expanded the application scenarios and scale, which has promoted the rapid development of WSN. Moreover, the acquisition of location information of unknown nodes is one of the critical issues that can be studied in wireless sensor networks. Therefore, aiming to solve large-ranging errors caused by uncertain factors in the ranging stage, this paper proposes a sensor network positioning method based on edge coverage control. It can dynamically correct model parameters to improve the performance of the DV-Hop method, integrate RSSI technology and error correction into the corresponding stage of DV-Hop, and make full use of the advantages of RSSI technology in short-distance applications. With the help of the known location information in WSN, the ranging error is reduced while avoiding information redundancy. The performance of DV-Hop can be improved to finally solve the positioning problem when the node deployment is relatively sparse. Simulation verification data show that the improved method can effectively reduce the distance estimation error in the same situation and achieve higher positioning accuracy.

Research on Artificial Intelligence Interaction in Computer-Aided Arts and Crafts

Background. With the continuous maturity of computer software and hardware technology, the theory and method of computer-aided art design have developed rapidly. Objective. Applying artificial intelligence theory to computer-aided process art design is one of the newly developed research hotspots, and it is also the development trend of industrial design modernization. Methods. On the one hand, it can transplant the research results in the field of artificial intelligence into computer-aided art design, and on the other hand, it expands the application field of artificial intelligence, so that the two can be perfectly combined to promote common development. Results. With the development of artificial intelligence technology, computer art has gradually become a very active field, and a large number of computer art works are available every year. Conclusions. This paper briefly describes the basic concepts of computer-aided art design and artificial intelligence and discusses the application of artificial intelligence in computer-aided art design.

MeTeaM—A method for characterizing mature software metrics teams

Background:Metrics teams play an increasingly important role in handling data and information in modern software development organizations; they manage their companies’ measurement programs, collect and process data, and develop and distribute information products. Metrics teams can comprise several roles, and their set-up can differ between companies, as can the metrics maturity of host organizations. These differences impact the effectiveness and quality of a team’s measurement program. Objective:Our objective was to design and evaluate a model to describe the characteristics of a mature metrics team, which efficiently designs, develops, maintains, and evolves its organization’s measurement program. Method:We conducted an action research study on four metrics teams of four distinct companies. We designed and evaluated a domain-specific model for assessing the maturity of metrics teams – MeTeaM – and also assessed the four metrics teams per se. Results:Our results were two-fold: the creation of the metrics team maturity model MeTeaM and a template to assess metrics teams. Our evaluation showed that the model captures the characteristics of successful metrics teams and quantifies the maturity status of both the metrics teams and their host organizations. Conclusions:More mature metrics teams score higher in the MeTeaM model than less mature teams. The assessment provides less mature metrics teams with valuable insights on what factors to improve. Such insights can be shared with and acted upon successfully with their organizations.

An ontological analysis of software system anomalies and their associated risks

Software systems have an increasing value in our lives, as our society relies on them for the numerous services they provide. However, as our need for larger and more complex software systems grows, the risks involved in their operation also grows, with possible consequences in terms of significant material and social losses. The rational management of software defects and possible failures is a fundamental requirement for a mature software industry. Standards, professional guides and capability models directly emphasize how important it is for an organization to know and to have a well-established history of failures, errors and defects as they occur in software activities. The problem is that each of these reference models employs its own vocabulary to deal with these phenomena, which can lead to a deficiency in the understanding of these notions by software engineers, causing potential interoperability problems between supporting tools, and, consequently, a poorer adoption of these standards and tools in practice. In this paper, we address this problem of the lack of a consensual conceptualization in this area by proposing two reference conceptual models: an Ontology of Software Defects, Errors and Failures (OSDEF), which takes into account an ecosystem of software artifacts, and a Reference Ontology of Software Systems (ROSS), which characterizes software systems and related artifacts at different levels of abstraction. Moreover, we use OSDEF and ROSS to perform an ontological analysis of the impact of defects, errors and failures of software systems from a risk analysis perspective. To do that, we employee an existing core ontology, namely, the Common Ontology of Value and Risk (COVR). The ontologies presented here are grounded on the Unified Foundational Ontology (UFO) and based on well-known and widely-accepted standards, professional and scientific guides and capability models. We demonstrate how this approach can suitably promote conceptual clarification and terminological harmonization in this area.

Assessment Strategies to Evaluate Building Information Modeling Capabilities of Organizations

With the advances in technology, Building Information Modeling (BIM) has been implemented in construction projects to minimize its complexity by increasing project efficiency and effectiveness. While BIM has been widely implemented, construction projects are still unsuccessful due to inappropriate BIM capabilities among organizations that are involved in the project. Therefore, this study aims to determine the strategies for assessing an organization’s BIM capabilities. The data collected through individual interviews with fifteen of BIM managers are analyzed using thematic analysis in order to achieve that objective. The findings suggest that the five parameters for evaluating an organization’s BIM capabilities are: documentation process, project track record, staff competencies, availability of BIM experts, and software maturity. This study contributes by providing a set of strategies for measuring an organization’s BIM capabilities in the construction industry. The lesson of this study would help researchers and industry practitioners prevent construction project failure from assessing project team members’ BIM capabilities before starting a project.

Named Data Networking for Content Delivery Network Workflows.

In this work we investigate Named Data Networking's (NDN's) architectural properties and features, such as content caching and intelligent packet forwarding, in the context of Content Delivery Network (CDN) workflows. More specifically, we evaluate NDN's properties for PoP (Point of Presence) to PoP and PoP to device connectivity. We use the Apache Traffic Server (ATS) platform to create a CDN-like caching hierarchy in order to compare NDN with HTTP-based content delivery. Overall, our work demonstrates that several properties inherent to NDN can benefit content providers and users alike through in-network caching of content, fast retransmission, and stateful hop-by-hop packet forwarding. Our experimental results demonstrate that HTTP delivers content faster under stable conditions due to a mature software stack. However, NDN performs better in the presence of packet loss, even for a loss rate as low as 0.1%, due to packet-level caching in the network and fast retransmissions from close upstreams. We further show that the Time To First Byte (TTFB) in NDN is consistently lower than HTTP (~ 100ms in HTTP vs. ~ 50ms in NDN), a vital requirement for CDNs. Unlike HTTP, NDN also supports transparent failover to another upstream when a failure occurs in the network. Finally, we present implementation-agnostic (implementation choices can be Software Defined Networking, Information Centric Networking, or something else) network properties that can benefit CDN workflows.

Robust Automated Photometry Pipeline for Blurred Images

The primary task of the 1.26 m telescope jointly operated by the National Astronomical Observatory and Guangzhou University is photometric observations of the g, r, and i bands. A data processing pipeline system was set up with mature software packages, such as IRAF, SExtractor, and SCAMP, to process approximately 5 GB of observational data automatically every day. However, the success ratio was significantly reduced when processing blurred images owing to telescope tracking error; this, in turn, significantly constrained the output of the telescope. We propose a robust automated photometric pipeline (RAPP) software that can correctly process blurred images. Two key techniques are presented in detail: blurred star enhancement and robust image matching. A series of tests proved that RAPP not only achieves a photometric success ratio and precision comparable to those of IRAF but also significantly reduces the data processing load and improves the efficiency.

The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment

BackgroundDigital health is a dynamic field that has been generating a large number of tools; many of these tools do not have the level of maturity required to function in a sustainable model. It is in this context that the concept of global goods maturity is gaining importance. Digital Square developed a global good maturity model (GGMM) for digital health tools, which engages the digital health community to identify areas of investment for global goods. The Surveillance Outbreak Response Management and Analysis System (SORMAS) is an open-source mobile and web application software that we developed to enable health workers to notify health departments about new cases of epidemic-prone diseases, detect outbreaks, and simultaneously manage outbreak response.ObjectiveThe objective of this study was to evaluate the maturity of SORMAS using Digital Square’s GGMM and to describe the applicability of the GGMM on the use case of SORMAS and identify opportunities for system improvements.MethodsWe evaluated SORMAS using the GGMM version 1.0 indicators to measure its development. SORMAS was scored based on all the GGMM indicator scores. We described how we used the GGMM to guide the development of SORMAS during the study period. GGMM contains 15 subindicators grouped into the following core indicators: (1) global utility, (2) community support, and (3) software maturity.ResultsThe assessment of SORMAS through the GGMM from November 2017 to October 2019 resulted in full completion of all subscores (10/30, (33%) in 2017; 21/30, (70%) in 2018; and 30/30, (100%) in 2019). SORMAS reached the full score of the GGMM for digital health software tools by accomplishing all 10 points for each of the 3 indicators on global utility, community support, and software maturity.ConclusionsTo our knowledge, SORMAS is the first electronic health tool for disease surveillance, and also the first outbreak response management tool, that has achieved a 100% score. Although some conceptual changes would allow for further improvements to the system, the GGMM already has a robust supportive effect on developing software toward global goods maturity.

Combinational metamorphic testing in integer vulnerabilities detection

Integer vulnerability is a common and hidden problem of software security. Even mature software written by experienced programmers cannot avoid integer vulnerability. Therefore, it is very important for testers to detect the bugs. However, testing the bugs will face the test oracle problem. As far as we know, the metamorphic testing can effectively alleviate the test oracle problem. In this paper, a method of combinational metamorphic relations (CMR) is proposed, which solves the test oracle problem and is more effective than metamorphic relation for Integer vulnerability detection. A case study results shows that the combinational metamorphic relations are more effective in bugs-detection than the single metamorphic relations.