Multiobjective optimisation and decision making for vessel routing - a prototype and case study

Application Programming Interfaces (APIs) are everyday tools for every software professional. When creating an API, a designer typically abstracts the tasks the API intends to perform. The API user, on the other hand, should use the API to perform specific-propose tasks. During the development of an API, the designer needs to write dialogues with which the user will interact with the API, performing a conversation between them. In this way, an API capable of offering effective dialogues to its users is called a conversational API. A conversational API is the one that is capable of communicating to its users its form of use and its internal logic of operation, making it clear the design decisions when abstracting concepts and tasks. In this paper, we present Colloquy, an evidence-based method to support the design of conversational APIs. Colloquy was conceived based on the lessons learned from an action research we conducted to identify effective strategies for designing conversational APIs. For six months, we followed the redesign of an existing API developed at an R&D laboratory of a large IT company. In this paper, we also present the first empirical evaluation of Colloquy. We conducted a case study in which the method was employed to design an API for refactoring source code in the Java programming language. Among other benefits, we found that Colloquy was effective in developing empathy with users and modeling conversations with them. Besides, Colloquy contributed to identifying new requirements and created models as API documentation.

APIs (application programming interfaces) play a key role in software development. Virtually, all programmers are potential users of third-party APIs. From the perspective of the theory of Semiotic Engineering, we may characterize an API as an artifact mediating the communication between two types of developers: the API designers and its users. During the construction of an API, the designers should establish proper dialogues with the users. These dialogues will enable the conversation of these actors at the interaction time. In this way, we define a conversational API as an API capable of offering effective dialogues to its users. In this paper, we introduce Colloquy, a method for supporting the design of conversational APIs. Colloquy results from the lessons learnt during an action research conducted for redesigning a real and complex API. The set of Colloquy resources allow API designers to go beyond conventional concerns with usability. We also report in this paper a case study in which Colloquy was used for redesigning a refactoring API. The study findings indicate the method helped the designer creating empathy with the API users, as well as better reflecting and depicting the requirements and the conversations that the API should attend to the different user profiles.

Code examples are important resources for expressing correct application programming interface (API) usages. However, many framework and library APIs fail in offering sufficient code examples in corresponding API documentations. This is because constructing proper code examples for documentation purpose takes significant developers' efforts. To reduce such effort, this work proposes a methodology, PropER-Doc, that recommends proper code examples for documentation purpose. PropER-Doc accepts queries from API developers and utilizes code search engines (CSEs) to collect corresponding code example candidates. The structural and conceptual links between API elements are captured from the API implementation and available API documents to guide candidate recommendation. During recommendation, PropER-Doc groups collected candidates based on involved API types for distinguishing different API usages. To assist API developers in selecting proper candidates, a diagrammatic presentation and three code example appropriateness metrics are also developed in {PropER-Doc}. Two case studies on Eclipse JDT framework are conducted to confirm the effectiveness of PropER-Doc.

External service integration and adherence to industry standards has become ever more important for collections data management platforms. External APIs (Application Programming Interfaces), allow for the development of bi-directional data flows critical to service integration. In contrast to service-oriented backend APIs, public APIs must have continually up-to-date, comprehensive documentation that covers common use cases, on-the-fly request validation, and meaningful error messages. OpenAPI (OpenAPI Initiative 2021), a machine-readable API documentation specification can help significantly with testing and maintenance, and libraries can be used to automate common maintenance tasks. Specify 7 is a biological collections data management platform developed by the Specify Collections Consortium (Specify Software Consortium 2021). This presentation summarizes the challenges and lessons learned with publishing the existing backend Specify 7 API to a public-facing external API. Each Specify 7 API is composed of 200 resources. A standard set of CRUD (Create, Read, Update, Delete) operations is provided for each resource for client interaction with a group of service-based endpoints for bulk operations such as file uploads, file-based data imports, and attachment manipulation. To support the migration, we developed a custom library to enhance request validation. Parameter validation is extended through a real-time comparison against the existing schema and data. The library is available to the community under a MIT license on GitHub (https://github.com/specify/open_api_tools/). In this presentation, we will close with an overview of the next steps for the Specify 7 public API. These include: An update to the latest OpenAPI specification, version 3.1. The latest version aims to increase compatibility with the Javascript Object Notation (JSON) Schema specification, and thus would allow us to use JSON Schema (IETF Trust 2021) validation frameworks. An in-depth evaluation of GraphQL for its ability to force all endpoints to be strongly typed and automatic validation of request parameters and response objects. An update to the latest OpenAPI specification, version 3.1. The latest version aims to increase compatibility with the Javascript Object Notation (JSON) Schema specification, and thus would allow us to use JSON Schema (IETF Trust 2021) validation frameworks. An in-depth evaluation of GraphQL for its ability to force all endpoints to be strongly typed and automatic validation of request parameters and response objects.

CORDITE: The Curated CORona Drug InTERactions Database for SARS-CoV-2

Increased pace of Application Programming interfaces (APIs) and third party data feeds have altered the game of cyber threat intelligence, by facilitating automated data exchange and situational awareness. Nevertheless, such external data sources have new vulnerabilities because of the inconsistent quality, unchecked authenticity, and different levels of trustworthiness. Conventional one-dimensional risk appraisals are not usually effective in capturing interchangeable character of threat posed by current data being consumed, leading to incomplete or obsolete security knowledge bases. This paper suggests a risk scoring system that is dynamical to determine the security and reliability of third-party data feeds and APIs in a threat intelligence system. The framework constantly changes risk scores by combining machine learning classifiers, feature detection based on API request metadata, and variable weighting of key risk factors to adapt to changing risk conditions. The validation of the methodology occurs in simulated enterprise settings whereby numerous API feeds are consumed, evaluated and compared with the benchmark of fixed mode models. The findings reveal that dynamic risk scoring methodology enhances much higher predictive accuracy, responsiveness, and operational relevance of cyber threat intelligence dashboards. The study is significant to cybersecurity practice because it provides a model that organizations can use to determine which sources of threat data to prioritize, reduce exposure and increase resilience, which is scalable and adjustable.

The last two decades brought an explosion of computational tools and processes in many scientific domains (e.g., life-, social- and geo-science). Scientific workflows, i.e., computational pipelines, accompanied by workflow management systems, were soon adopted as a de-facto standard among non-computer scientists for orchestrating such computational processes. The goal of this dissertation is to provide a framework that would automate the orchestration of such computational pipelines in practice. We refer to such problems as scientific workflow synthesis problems. This dissertation introduces the temporal logic SLTLx, and presents a novel SLTLx-based synthesis approach that overcomes limitations in handling data object dependencies present in existing synthesis approaches. The new approach uses transducers and temporal goals, which keep track of the data objects in the synthesised workflow. The proposed SLTLx-based synthesis includes a bounded and a dynamic variant, which are shown in Chapter 3 to be NP-complete and PSPACE-complete, respectively. Chapter 4 introduces a transformation algorithm that translates the bounded SLTLx-based synthesis problem into propositional logic. The transformation is implemented as part of the APE (Automated Pipeline Explorer) framework, presented in Chapter 5. It relies on highly efficient SAT solving techniques, using an off-the-shelf SAT solver to synthesise a solution for the given propositional encoding. The framework provides an API (application programming interface), a CLI (command line interface), and a web-based GUI (graphical user interface). The development of APE was accompanied by four concrete application scenarios as case studies for automated workflow composition. The studies were conducted in collaboration with domain experts and presented in Chapter 6. Each of the case studies is used to assess and illustrate specific features of the SLTLx-based synthesis approach. (1) A case study on cartographic map generation demonstrates the ability to distinguish data objects as a key feature of the framework. It illustrates the process of annotating a new domain, and presents the iterative workflow synthesis approach, where the user tries to narrow down the desired specification of the problem in a few intuitive steps. (2) A case study on geo-analytical question answering as part of the QuAnGIS project shows the benefits of using data flow dependencies to describe a synthesis problem. (3) A proteomics case study demonstrates the usability of APE as an “off-the-shelf” synthesiser, providing direct integration with existing semantic domain annotations. In addition, a manual evaluation of the synthesised results shows promising results even on large real-life domains, such as the EDAM ontology and the complete bio.tools registry. (4) A geo-event question-answering study demonstrates the usability of APE within a larger question-answering system. This dissertation answers the goals it sets to solve. It provides a formal framework, accompanied by a lightweight library, which can solve real-life scientific workflow synthesis problems. Finally, the development of the library motivated an upcoming collaborative project in the life sciences domain. The aim of the project is to develop a platform which would automatically compose (using APE) and benchmark workflows in computational proteomics.

Multimedia mapping provides a unique approach to integrating geospatial information in digital map format and multimedia information (e.g., text, photographs, sound, and video). Multimedia mapping on the Internet is the direct result of advancement of Web mapping techniques, Internet technology, and Web standards (e.g., HTML, XML, Ajax). However, like traditional Internet GIS applications, multimedia mapping on the Internet is suffered from slow response time, limitation of data sizes, and the slow client/server communications. In addition, the development of multimedia mapping on the Internet requires a huge investment of computer hardware and software, and a steep learning curve for the application developer to become knowledgeable about all of the components involved. It is imperative that a better solution is needed to implement multimedia mapping projects on the Internet. This chapter discusses a new approach of multimedia mapping that utilizes commercial Application Programming Interface (APIs) such as Google Maps API, Yahoo! Flickr API, and YouTube API that can provide faster response time, greater user interaction, as well as higher quality multimedia presentation. A case study of an online visitor guide for the campus of Southern Illinois University Edwardsville is demonstrated.

In multi-core processor architecture, all the cores run instructions on different cores at the same time. As a result, overall speed for programs that support multithreading is increased. A CPU in multithreaded environment is capable to handle multiple threads concurrently. The threads share the resources among different cores. Optimal thread allocation to cores with proper load balancing is very challenging. This paper presents a way to allocate threads to multiple cores that minimize thread switching overhead. As a result, overall work load is balanced. For parallel computation, OpenMP (Open Multi-Processing)- an Application Programming Interface (API) is used here in this paper, to supports multi-platform shared-memory for allocating threads in multiple cores with proper load balancing.

When the Application Programming Interface (API) of a framework or library changes, its clients must be adapted. This change propagation---known as a ripple effect---is a problem that has garnered interest: several approaches have been proposed in the literature to react to these changes.Although studies of ripple effects exist at the single system level, no study has been performed on the actual extent and impact of these API changes in practice, on an entire software ecosystem associated with a community of developers. This paper reports on an empirical study of API deprecations that led to ripple effects across an entire ecosystem. Our case study subject is the development community gravitating around the Squeak and Pharo software ecosystems: seven years of evolution, more than 3,000 contributors, and more than 2,600 distinct systems. We analyzed 577 methods and 186 classes that were deprecated, and answer research questions regarding the frequency, magnitude, duration, adaptation, and consistency of the ripple effects triggered by API changes.

The XSEDE User Portal (XUP) [1] is a web interface providing a set of user specific XSEDE services and documentation to a diverse audience. The XUP architecture started out depending on monolithic services provided by large Java libraries, but continues to evolve to use an application programming interface (API) [2] powered by a set of microservices [3]. The goal is to have the XUP API provide development and deployment environments that are agile, sustainable, and capable of handling feature changes. In making this transition, we have developed guidelines for API services that balance complexity and reuse needs with flexibility requirements. In doing so, we have also created our own set of best practices on how to convert to using microservices. In this paper we will use the XSEDE User Portal API development as a case study to explain our rationale, approach, and experiences in working with microservices in a real production environment to provide better and more reliable science services for end users.

The enhancing Paleontological and Neontological Data Discovery API (ePANDDA) project (NSF ICER 1821039) has developed an application programming interface (API) to integrate online paleontological and neontological databases, including the Paleobiology Database, iDigBio, and iDigPaleo. This connectivity provides a synthetic resource of information on all aspects of specimens, taxa, and localities. Here we present a case study that demonstrates how the ePANDDA API is being utilized to aid the digitization and dissemination of natural history collections, connect relevant disassociated data, and create added value to each of those resources. The Invertebrate Paleontology Collection at the Natural History Museum of Los Angeles County (NHMLA) is presently contributing data to the NSF-funded Fossil Insect Collaborative TCN (http://fossilinsects.colorado.edu). A cornerstone of the “Fossil Insects of L.A.” contribution (NSF DBI 1702342) is the historic Georg Statz Collection of fossil insects from the Rott Formation (Oligocene) of Germany. This collection of spectacularly preserved compression fossils was extensively described between the 1920s and 1940s, creating a comprehensive published record, which has been entered into the Paleobiology Database. Several thousand specimens of Statz’ collection, including over 900 type specimens, left Europe in the 1950s to be permanently reposited at the NHMLA. While important to their long-term conservation, this move has hampered collection access by the research community. The ePANDDA project will be able to link specimen record data hosted in iDigBio with bibliographic and taxonomic data reposited in the Paleobiology Database. In addition, programmatic development of the Paleobiology Database now allows for the tracking of fossil occurrences at the resolution of individual specimen records, and better documents the institutions with which those specimens are reposited. Therefore, images of NHMLA specimens, together with historic photographs, drawings, and annotations, will be discoverable through the Paleobiology Database and associated with the bibliographic records within which they were originally described or listed. Seamless search and discovery among these online resources enriches the potential of the historic Statz collection and augments its value for both research and education. We anticipate greater visibility of this and other NHMLA collections as a result of creating such linkages.

As application ecosystems evolve toward microservices, serverless architectures, and cloud-native models, Application Programming Interfaces (APIs) have become essential conduits for data and functionality exchange. However, their ubiquity and accessibility also make them prime targets for cyberattacks. This paper explores the evolving threat landscape for APIs, outlines the security challenges associated with API-first development, and recommends best practices for securing APIs across their lifecycle. It also includes a case study on high-profile API breaches from 2021–2022 and offers practical implementation strategies aligned with NIST and OWASP frameworks.

API integration and organisational agility outcomes in digital music platforms: A qualitative case study

Earth observation (EO) data play a crucial role in monitoring ecosystems and environmental processes. Time series of satellite data are essential for long-term studies in this context. Working with large volumes of satellite data, however, can still be a challenge, as the computational environment with respect to storage, processing and data handling can be demanding, which sometimes can be perceived as a barrier when using EO data for scientific purposes. In particular, open-source developments which comprise all components of EO data handling and analysis are still scarce. To overcome this difficulty, we present Tools for Analyzing Time Series of Satellite Imagery (TATSSI), an open-source platform written in Python that provides routines for downloading, generating, gap-filling, smoothing, analyzing and exporting EO time series. Since TATSSI integrates quality assessment and quality control flags when generating time series, data quality analysis is the backbone of any analysis made with the platform. We discuss TATSSI’s 3-layered architecture (data handling, engine and three application programming interfaces (API)); by allowing three APIs (a native graphical user interface, some Jupyter Notebooks and the Python command line) this development is exceptionally user-friendly. Furthermore, to demonstrate the application potential of TATSSI, we evaluated MODIS time series data for three case studies (irrigation area changes, evaluation of moisture dynamics in a wetland ecosystem and vegetation monitoring in a burned area) in different geographical regions of Mexico. Our analyses were based on methods such as the spatio-temporal distribution of maxima over time, statistical trend analysis and change-point decomposition, all of which were implemented in TATSSI. Our results are consistent with other scientific studies and results in these areas and with related in-situ data.