Ariadne: An Eclipse-based system for tracking originality of source code

My research explores the adoption of InnerSource, a practice that integrates open source methodologies within organizations to foster collaboration and overcome the traditional silo mentality. InnerSource and Agile implementations share many values such as transparency, employee empowerment, and a flexible response to change. InnerSource adoption can come before, after, or in parallel with Agile transformations. Despite the increasing recognition of InnerSource as a pivotal driver for developer productivity and its growing presence in industry discussions, academic research on the subject remains in its infancy. Leveraging my involvement with the InnerSource Commons community and drawing from Activity Theory, my research aims to fill critical gaps in our understanding of InnerSource adoption. Specifically, it investigates the activities organizations engage in to enable InnerSource, identifies blockers hindering its implementation, and proposes effective strategies to counteract these challenges. At the XP 2024 PhD Symposium, I intend to share some preliminary findings of my research, derived from a Systematic Literature Review and a pilot study with an InnerSource practitioner working group. My research not only seeks to advance theoretical knowledge in the field but also offers practical insights for organizations striving to change software development practices, contributing to a more collaborative and efficient software development environment.

To ensure integrity, trust, immutability and authenticity of software and information (cyber data, user data and attack event data) in a collaborative environment, research is needed for cross-domain data communication, global software collaboration, sharing, access auditing and accountability. Blockchain technology can significantly automate the software export auditing and tracking processes. It allows to track and control what data or software components are shared between entities across multiple security domains. Our blockchain-based solution relies on role-based and attribute-based access control and prevents unauthorized data accesses. It guarantees integrity of provenance data on who updated what software module and when. Furthermore, our solution detects data leakages, made behind the scene by authorized blockchain network participants, to unauthorized entities. Our approach is used for data forensics/provenance, when the identity of those entities who have accessed/ updated/ transferred the sensitive cyber data or sensitive software is determined. All the transactions in the global collaborative software development environment are recorded in the blockchain public ledger and can be verified any time in the future. Transactions can not be repudiated by invokers. We also propose modified transaction validation procedure to improve performance and to protect permissioned IBM Hyperledger-based blockchains from DoS attacks, caused by bursts of invalid transactions.

This paper presents a collaborative software development platform allowing traditional and virtual universities actors who are geographically distant to work on a software development project using common (usual) programming languages. In the context of the virtual universities operating in the field of STEM (Science, Technology, Engineering and Mathematics), pratical classes are needed to acquire and to enhance the necessary skills particularly in software engineering. To the various actors of these digital and traditional universities making some e-learning, this paper supplies a preconfigured collaborative software development environment including synchronization of files belonging to a given project, instant messaging, audio and video. Our platform has an administration interface allowing the management of permissions and preconfigured virtual machines allocation to the various actors. To reach our goals, we used the XMPP protocol for instant messaging and file synchronization. Then, we used WebRTC for audio and video between actors. Finally, we used the RDP protocol to allow the access to the virtual machines. In this work, we show how our platform was used by the Virtual University of the Senegal (UVS) teachers and students in the field of Applied Mathematics and Computer Science for some pratical classes about C/C++, Java, Python and PHP programming languages.

In collaborative software developments, many change processes implementing change requests are executed concurrently by different workers. The fact that the workers do not have sufficient information about the others' work and complicated dependencies among artifacts can lead to unexpected inconsistencies among the artifacts impacted by the changes. Most previous studies concentrated only on concurrent changes and considered them separately. However, even when the changes are not concurrent, inconsistencies may still happen if a worker does not recognize the impact of the changes made by other workers on his changes or the impact of his changes on other workers' changes. In addition, the changes in a change process are related to each other through their common target of realizing the change request and the dependencies among the changed artifacts. Therefore, to handle inconsistencies more effectively, we concentrate on both concurrent and non-concurrent changes, and the context of a change, i.e. the change process containing the change, rather than the ongoing changes only. In this paper, we present an inconsistency awareness mechanism and a Change Support Workflow Management System (CSWMS) that realizes this mechanism. By monitoring the progress of the change processes and the ongoing changes in the client workspaces, CSWMS can notify the workers of a (potential) inconsistency in advance along with the context of the inconsistency, that is, the changes causing the inconsistency and the change processes containing these changes. Based on the information provided by CSWMS, the workers can detect and resolve inconsistencies more easily and quickly. Therefore, our research can contribute to building a safer and more efficient collaborative software development environment.

Distributed software development is becoming a common practice among developers. Factors such as the development environments improvement, their extensibility, and the emergence of social networking software are leading factors. They lead the development process (both co-located and geographically distributed) to a practice that: 1) improves the team’s productivity, and 2) encourages and supports the social interaction among the teams’ members. The above factors along with the distributed development emergence, Integrated Development Environments (IDEs) evolution, and the social media advances got the attention of the software development teams, and made them consider how to better assist the social nature of software developers, and the social aspects of software development, including activity awareness of team members’ progress, their presence, collaboration, communication, and coordination around shared artifacts. IDEs are the most commonly used tools by developers and programmers. Integrating the most needed development tools inside the IDE, makes it a Collaborative Development Environment (CDE), and embedding a variety of social software features within a CDE helps support distributed development teams. It also creates a new genera of tools called Social Development Environments or “SDEs” as it is commonly called. This article discusses the origins and development of “SDEs”. It reflects and presents the research into development environments, explaining their role in supporting the communication and coordination needs of development teams. Also, it presents the effect of embedding social network features in such environments. It presents some emerging SDEs and future work. Finally, it concludes by introducing a new model named 5-star that classifies, and helps to evaluate and compare the collaborative tools. 5-star presents a new way to compare and evaluate the SDE systems based on their supported features. It bases the comparison on five major categories including: Communication, Coordination, Collaboration, Awareness & Presence, and Social networking (SN) tools.

This paper provides a way to overcome the limitations of general collaborative software development tools that completely restrict co-ownership of resources among individuals in a team oriented developmental environment. It also provides a solution for users to co-own resources and at the same time manage version control and solve collision problems that may occur due to the co-ownership of resources. The collaborative software development tool presented in this paper is made up of the classical client/server structure with the P2P (peer to peer) method which supports information exchange among individuals. This tool is developed based on open source software CVS (Concurrent Version System). Functional efficiency was confirmed by comparing it to the utility of prior existing collaborative software development tools.

Aiming at the problems of high product development cost and long development cycle caused by poor application of DC (Design Component) in a collaborative development environment, this paper proposes a reuse method of DC. Firstly, we analyze the application characteristics of 5 types of DC and build 5 different types of model libraries in the PDM system. Secondly, based on the informatization conditions of the enterprise, we analyze the functions and integration interfaces between the various systems in the collaborative development environment and clarify the data transfer relationship between each library between the PDM system, SBRMS, and CAD tools. Thirdly, combining the existing DC management requirements, we propose 5 application processes and clarify the task division of business roles in each business process, which can open the data integration link between each library and the systems. Through practical application, the design efficiency of special vehicles is improved, the design cycle is shortened, and the cost is reduced.

This paper describes the development of a compute-mediated collaborative product development environment (COMCOPE) within the context of the construction industry, a collaborative project between Anglia Polytechnic University, the University of Strathclyde, and some industrial partners. The most prominent feature about COMCOPE lies in the particular emphasis on supporting human-human interaction across time and space through computer mediation within a distributed and networked environment. Based on a review of related research areas, traditional computer integrated construction concepts have been extended within the framework of computer supported cooperative work, which results in the COMCOPE conceptual architecture. As the core of COMCOPE architecture an interaction model has been developed to help articulate collaborative activities. Implementation issues have been addressed, and a prototype system, based on an augmented client-server model, has been outlined.

There are various ideas in everyone's mind. But to convert the ideas into reality, requires initiative and action. Petroleum industry has been using different techniques, science and algorithms over the years to tackle the challenges in order to achieve a business objective. This paper shares the implemented approach to support business challenges by developing a Research and development environment to support the business community. The idea was to find out current business user challenges and support their requirements. IBTIKAR (innovation) lab is the result of this idea which is created to provide required In-House infrastructure (Hardware and Software) support within UAE National Oil Company premises. Research and development are integral part of any company/industry for tackling challenges. Accessing various data types and implementing the concept of Big data has been of a great value. Collaboration between business users, Information technology and Data Management is required to have concrete foundation and to prepare roadmap for the future. The application portfolio in an Oil and Gas upstream varies a lot and now a days, almost all the applications /tool come with a programming interface for integrating Open-Source algorithms. It makes it easier to directly connect the open-source tools to existing applications. The type of data types in upstream varies a lot and since these applications are already developed over the years to handle different kind of data, which further makes data analysis tasks achievable in timely manner. The available algorithms in existing tools and those accessed visa Open-source tools are further used for prediction and classification problems. With the advances in the learning algorithms, the modelling has become easier, and it requires very less coding. The challenges are more towards infrastructure support, as the data types and data size has gradually increased. Machine learning and Deep learning requires High end infrastructure to perform the data science using more CPU's, High End GPU's. In order to adapt to the advancing science and technologies, it makes everyone responsible to learn and implement the data science and Artificial intelligence (AI) concepts in daily tasks and projects to support organization strategy and objectives. In order to get the business community ready for AI, availability of Data science tools and infrastructure is required. This will support and allow the business users of any kind of data to try and test various data types using AI and data science. Following approach was taken from the idea initiation to the execution phase: Discussion with Business users to find out current business challenges and impediments in overcoming those challengesDocument project scopes for the discussed business challenges.Discussion with the respective Infrastructure support team to provide the Hardware and software support along with the required data storage space.Secure budget for developing IBTIKAR labDevelop environment for the research and development of various data science projectsIntegration of Open Source and Free software/s with the existing tools and applicationsAgree and support of the respective roles and responsibilitiesAgree of establishing a collaborative environment between business users, Information technology and data management engineers.To have tools covering the life cycle of the machine learning model (from creation to deployment to monitoring) The business users involved throughout the upstream activities, want to use available open-source algorithms and run various Proof of concepts. In order to get value out of data and to extract insight, it is must that business users are empowered with the required infrastructure, trainings, data science tools and Artificial intelligent algorithms in a collaborative Research and development environment. Configuration and implementation of the IBTIKAR environment has aided the business user community in conducting various Proof of concepts and execute process to handle various business objectives and extract value. IBTIKAR environment has delivered value to the business community by providing required High-end resources, a programming environment, available open-source algorithms and it has improved the level of efficiency, collaboration and people engagement.

IBM's Jazz initiative offers a state-of-the-art collaborative development environment (CDE) facilitating developer interactions around interdependent units of work. In this paper, we analyze development data across two versions of a major IBM product developed on the Jazz platform, covering in total 19 months of development activity, including 17,000+ work items and 61,000+ comments made by more than 190 developers in 35 locations. By examining the relation between developer talk and work, we find evidence that developers maintain a reasonably high level of connectivity with peer developers with whom they share work dependencies, but the span of a developer's communication goes much beyond the known dependencies of his/her work items. Using multiple linear regression models, we find that the number of defects owned by a developer is impacted by the number of other developers (s)he is connected through talk, his/her interpersonal influence in the network of work dependencies, the number of work items (s)he comments on, and the number work items (s)he owns. These effects are maintained even after controlling for workload, role, work dependency, and connection related factors. We discuss the implications of our results for collaborative software development and project governance.

IBM's Jazz initiative offers a state-of-the-art collaborative development environment (CDE) facilitating developer interactions around interdependent units of work. In this paper, we analyze development data across two versions of a major IBM product developed on the Jazz platform, covering in total 19 months of development activity, including 17,000+ work items and 61,000+ comments made by more than 190 developers in 35 locations. By examining the relation between developer talk and work, we find evidence that developers maintain a reasonably high level of connectivity with peer developers with whom they share work dependencies, but the span of a developer's communication goes much beyond the known dependencies of his/her work items. Using multiple linear regression models, we find that the number of defects owned by a developer is impacted by the number of other developers (s)he is connected through talk, his/her interpersonal influence in the network of work dependencies, the number of work items (s)he comments on, and the number work items (s)he owns. These effects are maintained even after controlling for workload, role, work dependency, and connection related factors. We discuss the implications of our results for collaborative software development and project governance.

Software development is rarely an individual effort and generally involves teams of developers collaborating to generate good reliable code. Among the software code there exist technical dependencies that arise from software components using services from other components. The different ways of assigning the design, development, and testing of these software modules to people can cause various coordination problems among them. We claim that the collaboration of the developers, designers and testers must be related to and governed by the technical task structure. These collaboration practices are handled in what we call Socio-Technical Patterns. The TESNA project (Technical Social Network Analysis) we report on in this paper addresses this issue. We propose a method and a tool that a project manager can use in order to detect the socio-technical coordination problems. We test the method and tool in a case study of a small and innovative software product company.

Manufacturing companies today instead of selling classical products turn more to offer Product Service Systems (PSS). The development of PSS in manufacturing industry requires intensive collaboration among various actors across the value chain. Innovative collaborative ICT environment including sets of advanced tools allowing for effective PSS development are needed. Enormous amount of knowledge to be gathered and shared under dynamically changing conditions, and diffused to a wide spectrum of actors involved, having different expertise and working conditions/cultures, asks for effective context sensitive solutions for knowledge capturing, analysis and diffusion. The paper presents a novel approach for context sensitivity of tools to support collaborative PSS development. The proposed solution is one of the first attempts to provide holistic methodology and set of software services allowing for context sensitivity of diverse PSS engineering tools. The context model based on ontology and the set of services for context monitoring and extraction are specified and developed. The application of the proposed solution in machine industry for collaborative PSS development is discussed.

A mixed reality environment for collaborative product design and development

Consolidation of structure of high noise data by a new noise index and reinforcement learning