Factors shaping the evolution of electronic documentation systems

The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments

Supporting Software Development by an Integrated Documentation Model for Decisions

Decision-making is a vital activity during software development. Decisions made during requirements engineering, software design, and implementation guide the development process. In order to make decisions, developers may apply different strategies. For instance, they can search for alternatives and evaluate them according to given criteria, or they may rely on their personal experience and heuristics to make single solution claims. Thereby, knowledge emerges during the process of decision making, as the content, outcome, and context of decisions are explored by developers. For instance, different solution options may be considered to address a given decision problem. In particular, such knowledge is growing rapidly, when multiple developers are involved. Therefore, it should be documented to make decisions comprehensible in the future. However, this documentation is often not performed by developers in practice. First, developers need to find and use a documentation approach, which provides support for the decision making strategies applied for the decision to be documented. Thus, documentation approaches are required to support multiple strategies. Second, due to the collaborative nature of the decision making process during one or more development activities, decision knowledge needs to be captured and structured according to one integrated model, which can be applied during all these development activities. This thesis uncovers two important reasons, why the aforementioned requirements are currently not fulfilled sufficiently. First, it is investigated, which decision making strategies can be identified in the documentation of decisions within issue tickets from the Firefox project. Interestingly, most documented decision knowledge originates from naturalistic decision making, whereas most current documentation approaches structure the captured knowledge according to rational decision making strategies. Second, most decision documentation approaches focus on one development activity, so that for instance decision documentation during requirements engineering and implementation are not supported within the same documentation model. The main contribution of this thesis is a documentation model for decision knowledge, which addresses these two findings. In detail, the documentation model supports the documentation of decision knowledge resulting from both naturalistic and rational decision making strategies, and integrates this knowledge within flexible documentation structures. Also, it is suitable for capturing decision knowledge during the three development activities of requirements engineering, design, and implementation. Furthermore, a tool support is presented for the model, which allows developers to integrate decision capturing and documentation in their activities using the Eclipse IDE

Analysis and design of multiagent systems using MAS-CommonKADS

This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADSwith techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network

Third Conference on Artificial Intelligence for Space Applications, part 2

Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed

The Maritime Domain Awareness Center– A Human-Centered Design Approach

This paper contends that Maritime Domain Awareness Center (MDAC) design should be a holistic approach integrating established knowledge about human factors, decision making, cognitive tasks, complexity science, and human information interaction. The design effort should not be primarily a technology effort that focuses on computer screens, information feeds, display technologies, or user interfaces. The existence of a room with access to vast amounts of information and wall-to-wall video screens of ships, aircraft, weather data, and other regional information does not necessarily correlate to possessing situation awareness. Fundamental principles of human-centered information design should guide MDAC design and technology selection, and it is imperative that they be addressed early in system development. The design approach should address the reason and purpose for a given MDAC. Subsequent design efforts should address ergonomic interaction with information – the relationship of the brain to the information ecosystem provided by the MDAC, and the cognitive science of situation awareness and decision making. This understanding will guide technology functionality. The system user and decision maker should be the focus of the information design specifications, and this user population must participate and influence the information design. Accordingly, this paper provides a “design gestalt” by which to approach the design and development of an MDAC

Collecting Unsolicited User-Generated Change Requests

Unlike aircrew directly associated with acquisitions, line operators are not fully engaged in the methods to push materiel hardware or software change requests up the chain, to a decision maker, and then to the engineers. The Air Force trains these end users to logically apply expert systems knowledge to execute the mission but has not fully leveraged this resource for properly identifying and correcting operational shortfalls in an aircraft\u27s design. Focusing on the Remotely Piloted Aircraft (RPA) community, the research goal is to determine if the Air Force should establish a formal program for collecting and prioritizing unsolicited user change requests from operators, and if so, how should the process be implemented and what characteristics should the system possess. This Delphi study sought consensus from a panel of MQ-1 and MQ-9 expert operators on desired characteristics and basic architecture. The analysis revealed that the deficiency reporting program, traditionally focused on Test and Evaluation squadrons, meets many of the desired characteristics but could be improved to meet all of them. Additionally, cockpit development could improve through supplementing the already established Cockpit Working Groups with a commercially developed tool with many of the desired characteristics

Recovering Trace Links Between Software Documentation And Code

Introduction Software development involves creating various artifacts at different levels of abstraction and establishing relationships between them is essential. Traceability link recovery (TLR) automates this process, enhancing software quality by aiding tasks like maintenance and evolution. However, automating TLR is challenging due to semantic gaps resulting from different levels of abstraction. While automated TLR approaches exist for requirements and code, architecture documentation lacks tailored solutions, hindering the preservation of architecture knowledge and design decisions. Methods This paper presents our approach TransArC for TLR between architecture documentation and code, using componentbased architecture models as intermediate artifacts to bridge the semantic gap. We create transitive trace links by combining the existing approach ArDoCo for linking architecture documentation to models with our novel approach ArCoTL for linking architecture models to code. Results We evaluate our approaches with five open-source projects, comparing our results to baseline approaches. The model-to-code TLR approach achieves an average F1-score of 0.98, while the documentation-to-code TLR approach achieves a promising average F1-score of 0.82, significantly outperforming baselines. Conclusion Combining two specialized approaches with an intermediate artifact shows promise for bridging the semantic gap. In future research, we will explore further possibilities for such transitive approaches

Let’s augment the future together!:Augmented reality troubleshooting support for IT/OT rolling stock failures

The railway industry is moving to a socio-technological system that relies on computer-controlled and human-machine interfaces. Opportunities arise for creating new services and commercial business cases by using technological innovations and traffic management systems. The convergence of Information Technology (IT) with Operational Technology (OT) is critical for cost-effective and reliable railway operations. However, this convergence introduces complexities, leading to more intricate rolling stock system failures. Hence, operators necessitate assistance in their troubleshooting and maintenance strategy to simplify the decision-making and action-taking processes. Augmented Reality (AR) emerges as a pivotal tool for troubleshooting within this context. AR enhances the operator’s ability to visualize, contextualize, and understand complex data by overlaying real-time and virtual information onto physical objects. AR supports the identification of IT/OT rolling stock system failures, offers troubleshooting directions, and streamlines maintenance procedures, ultimately enhancing decision-making and action-taking processes. This thesis investigates how AR can support operators in navigating troubleshooting and maintenance challenges posed by IT/OT rolling stock system failures in the railway industry

Recovering Trace Links Between Software Documentation And Code

Introduction Software development involves creating various artifacts at different levels of abstraction and establishing relationships between them is essential. Traceability link recovery (TLR) automates this process, enhancing software quality by aiding tasks like maintenance and evolution. However, automating TLR is challenging due to semantic gaps resulting from different levels of abstraction. While automated TLR approaches exist for requirements and code, architecture documentation lacks tailored solutions, hindering the preservation of architecture knowledge and design decisions. Methods This paper presents our approach TransArC for TLR between architecture documentation and code, using componentbased architecture models as intermediate artifacts to bridge the semantic gap. We create transitive trace links by combining the existing approach ArDoCo for linking architecture documentation to models with our novel approach ArCoTL for linking architecture models to code. Results We evaluate our approaches with five open-source projects, comparing our results to baseline approaches. The model-to-code TLR approach achieves an average F1-score of 0.98, while the documentation-to-code TLR approach achieves a promising average F1-score of 0.82, significantly outperforming baselines. Conclusion Combining two specialized approaches with an intermediate artifact shows promise for bridging the semantic gap. In future research, we will explore further possibilities for such transitive approaches

Analysis of Human Affect and Bug Patterns to Improve Software Quality and Security

The impact of software is ever increasing as more and more systems are being software operated. Despite the usefulness of software, many instances software failures have been causing tremendous losses in lives and dollars. Software failures take place because of bugs (i.e., faults) in the software systems. These bugs cause the program to malfunction or crash and expose security vulnerabilities exploitable by malicious hackers. Studies confirm that software defects and vulnerabilities appear in source code largely due to the human mistakes and errors of the developers. Human performance is impacted by the underlying development process and human affects, such as sentiment and emotion. This thesis examines these human affects of software developers, which have drawn recent interests in the community. For capturing developers’ sentimental and emotional states, we have developed several software tools (i.e., SentiStrength-SE, DEVA, and MarValous). These are novel tools facilitating automatic detection of sentiments and emotions from the software engineering textual artifacts. Using such an automated tool, the developers’ sentimental variations are studied with respect to the underlying development tasks (e.g., bug-fixing, bug-introducing), development periods (i.e., days and times), team sizes and project sizes. We expose opportunities for exploiting developers’ sentiments for higher productivity and improved software quality. While developers’ sentiments and emotions can be leveraged for proactive and active safeguard in identifying and minimizing software bugs, this dissertation also includes in-depth studies of the relationship among various bug patterns, such as software defects, security vulnerabilities, and code smells to find actionable insights in minimizing software bugs and improving software quality and security. Bug patterns are exposed through mining software repositories and bug databases. These bug patterns are crucial in localizing bugs and security vulnerabilities in software codebase for fixing them, predicting portions of software susceptible to failure or exploitation by hackers, devising techniques for automated program repair, and avoiding code constructs and coding idioms that are bug-prone. The software tools produced from this thesis are empirically evaluated using standard measurement metrics (e.g., precision, recall). The findings of all the studies are validated with appropriate tests for statistical significance. Finally, based on our experience and in-depth analysis of the present state of the art, we expose avenues for further research and development towards a holistic approach for developing improved and secure software systems