A data-driven game theoretic strategy for developers in software crowdsourcing: a case study

Crowdsourcing has the advantages of being cost-effective and saving time, which is a typical embodiment of collective wisdom and community workers’ collaborative development. However, this development paradigm of software crowdsourcing has not been used widely. A very important reason is that requesters have limited knowledge about crowd workers’ professional skills and qualities. Another reason is that the crowd workers in the competition cannot get the appropriate reward, which affects their motivation. To solve this problem, this paper proposes a method of maximizing reward based on the crowdsourcing ability of workers, they can choose tasks according to their own abilities to obtain appropriate bonuses. Our method includes two steps: Firstly, it puts forward a method to evaluate the crowd workers’ ability, then it analyzes the intensity of competition for tasks at Topcoder.com—an open community crowdsourcing platform—on the basis of the workers’ crowdsourcing ability; secondly, it follows dynamic programming ideas and builds game models under complete information in different cases, offering a strategy of reward maximization for workers by solving a mixed-strategy Nash equilibrium. This paper employs crowdsourcing data from Topcoder.com to carry out experiments. The experimental results show that the distribution of workers’ crowdsourcing ability is uneven, and to some extent it can show the activity degree of crowdsourcing tasks. Meanwhile, according to the strategy of reward maximization, a crowd worker can get the theoretically maximum reward

Data distribution and exploitation in a global microservice artefact observatory

​© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Cloud computing and specifically the microservice architecture pattern is becoming an increasingly prominent paradigm in computer science. Many modern cloud applications are composed of a variety of different microservices, each potentially built in different languages, using different technologies and a different software artefact structure. What is needed is the capability to monitor this rapidly expanding field and leverage the data to enable further research and development of microservice architectures. Drawing inspiration from the global observatories used in geoscience and astronomy, the aim of this research initiative is the establishment of a global observatory for microservice artefacts, allowing the aggregation of data from different hubs and the execution of dynamic analysis on them

Model-based integration testing technique using formal finite state behavioral models for component-based software

Many issues and challenges could be identified when considering integration testing of Component-Based Software Systems (CBSS). Consequently, several research have appeared in the literature, aimed at facilitating the integration testing of CBSS. Unfortunately, they suffer from a number of drawbacks and limitations such as difficulty of understanding and describing the behavior of integrated components, lack of effective formalism for test information, difficulty of analyzing and validating the integrated components, and exposing the components implementation by providing semi-formal models. Hence, these problems have made it in effective to test today’s modern complex CBSS. To address these problems, a model-based approach such as Model-Based Testing (MBT) tends to be a suitable mechanism and could be a potential solution to be applied in the context of integration testing of CBSS. Accordingly, this thesis presents a model-based integration testing technique for CBSS. Firstly, a method to extract the formal finite state behavioral models of integrated software components using Mealy machine models was developed. The extracted formal models were used to detect faulty interactions (integration bugs) or compositional problems between integrated components in the system. Based on the experimental results, the proposed method had significant impact in reducing the number of output queries required to extract the formal models of integrated software components and its performance was 50% better compared to the existing methods. Secondly, based on the extracted formal models, an effective model-based integration testing technique (MITT) for CBSS was developed. Finally, the effectiveness of the MITT was demonstrated by employing it in the air gourmet and elevator case studies, using three evaluation parameters. The experimental results showed that the MITT was effective and outperformed Shahbaz technique on the air gourmet and elevator case studies. In terms of learned components for air gourmet and elevator case studies respectively, the MITT results were better by 98.14% and 100%, output queries based on performance were 42.13% and 25.01%, and error detection capabilities were 70.62% and 75% for each of the case study

A verified and optimized Stream X-Machine testing method, with application to cloud service certification

The Stream X-Machine (SXM) testing method provides strong and repeatable guarantees of functional correctness, up to a specification. These qualities make the method attractive for software certification, especially in the domain of brokered cloud services, where arbitrage seeks to substitute functionally equivalent services from alternative providers. However, practical obstacles include: the difficulty in providing a correct specification, the translation of abstract paths into feasible concrete tests, and the large size of generated test suites. We describe a novel SXM verification and testing method, which automatically checks specifications for completeness and determinism, prior to generating complete test suites with full grounding information. Three optimisation steps achieve up to a ten-fold reduction in the size of the test suite, removing infeasible and redundant tests. The method is backed by a set of tools to validate and verify the SXM spec-ification, generate technology-agnostic test suites and ground these in SOAP, REST or rich-client service implementations. The method was initially validated using seven specifications, three cloud platforms and five grounding strategies

Integrating mobile and cloud resources management using the cloud personal assistant

The mobile cloud computing model promises to address the resource limitations of mobile devices, but effectively implementing this model is difficult. Previous work on mobile cloud computing has required the user to have a continuous, high-quality connection to the cloud infrastructure. This is undesirable and possibly infeasible, as the energy required on the mobile device to maintain a connection, and transfer sizeable amounts of data is large; the bandwidth tends to be quite variable, and low on cellular networks. The cloud deployment itself needs to efficiently allocate scalable resources to the user as well. In this paper, we formulate the best practices for efficiently managing the resources required for the mobile cloud model, namely energy, bandwidth and cloud computing resources. These practices can be realised with our mobile cloud middleware project, featuring the Cloud Personal Assistant (CPA). We compare this with the other approaches in the area, to highlight the importance of minimising the usage of these resources, and therefore ensure successful adoption of the model by end users. Based on results from experiments performed with mobile devices, we develop a no-overhead decision model for task and data offloading to the CPA of a user, which provides efficient management of mobile cloud resources

Portability of Process-Aware and Service-Oriented Software: Evidence and Metrics

Modern software systems are becoming increasingly integrated and are required to operate over organizational boundaries through networks. The development of such distributed software systems has been shaped by the orthogonal trends of service-orientation and process-awareness. These trends put an emphasis on technological neutrality, loose coupling, independence from the execution platform, and location transparency. Execution platforms supporting these trends provide context and cross-cutting functionality to applications and are referred to as engines. Applications and engines interface via language standards. The engine implements a standard. If an application is implemented in conformance to this standard, it can be executed on the engine. A primary motivation for the usage of standards is the portability of applications. Portability, the ability to move software among different execution platforms without the necessity for full or partial reengineering, protects from vendor lock-in and enables application migration to newer engines. The arrival of cloud computing has made it easy to provision new and scalable execution platforms. To enable easy platform changes, existing international standards for implementing service-oriented and process-aware software name the portability of standardized artifacts as an important goal. Moreover, they provide platform-independent serialization formats that enable the portable implementation of applications. Nevertheless, practice shows that service-oriented and process-aware applications today are limited with respect to their portability. The reason for this is that engines rarely implement a complete standard, but leave out parts or differ in the interpretation of the standard. As a consequence, even applications that claim to be portable by conforming to a standard might not be so. This thesis contributes to the development of portable service-oriented and process-aware software in two ways: Firstly, it provides evidence for the existence of portability issues and the insufficiency of standards for guaranteeing software portability. Secondly, it derives and validates a novel measurement framework for quantifying portability. We present a methodology for benchmarking the conformance of engines to a language standard and implement it in a fully automated benchmarking tool. Several test suites of conformance tests for two different languages, the Web Services Business Process Execution Language 2.0 and the Business Process Model and Notation 2.0, allow to uncover a variety of standard conformance issues in existing engines. This provides evidence that the standard-based portability of applications is a real issue. Based on these results, this thesis derives a measurement framework for portability. The framework is aligned to the ISO/IEC Systems and software Quality Requirements and Evaluation method, the recent revision of the renowned ISO/IEC software quality model and measurement methodology. This quality model separates the software quality characteristic of portability into the subcharacteristics of installability, adaptability, and replaceability. Each of these characteristics forms one part of the measurement framework. This thesis targets each characteristic with a separate analysis, metrics derivation, evaluation, and validation. We discuss existing metrics from the body of literature and derive new extensions speciffically tailored to the evaluation of service-oriented and process-aware software. Proposed metrics are defined formally and validated theoretically using an informal and a formal validation framework. Furthermore, the computation of the metrics has been prototypically implemented. This implementation is used to evaluate metrics performance in experiments based on large scale software libraries obtained from public open source software repositories. In summary, this thesis provides evidence that contemporary standards and their implementations are not sufficient for enabling the portability of process-aware and service-oriented applications. Furthermore, it proposes, validates, and practically evaluates a framework for measuring portability

Coastal cities at risk in the Philippines (CCARPH) : investing in climate and disaster resilience project : technical report for years 1-3

The project worked to increase capacity of coastal cities and vulnerable communities in the Philippines to adapt to climate and disaster risks, and move towards resilience in the context of rapid urbanization and economic expansion. Advocating for science-based decision-making, and operating through public-private transdisciplinary collaboration, coastal cities at risk in the Philippines (CCARPH) along with the National Resilience Council (NRC) helped integrate private sector roles in understanding, mitigating, and preventing risks associated with climate change. The report covers project activities, strategic partnerships, outputs and outcomes, with embedded links to websites, publications, policy briefs and innovative approaches