What have we learnt from the challenges of (semi-) automated requirements traceability? A discussion on blockchain applicability.

Over the last 3 decades, researchers have attempted to shed light into the requirements traceability problem by introducing tracing tools, techniques, and methods with the vision of achieving ubiquitous traceability. Despite the technological advances, requirements traceability remains problematic for researchers and practitioners. This study aims to identify and investigate the main challenges in implementing (semi-)automated requirements traceability, as reported in the recent literature. A systematic literature review was carried out based on the guidelines for systematic literature reviews in software engineering, proposed by Kitchenham. We retrieved 4530 studies by searching five major bibliographic databases and selected 70 primary studies. These studies were analysed and classified according to the challenges they present and/or address. Twenty-one challenges were identified and were classified into five categories. Findings reveal that the most frequent challenges are technological challenges, in particular, low accuracy of traceability recovery methods. Findings also suggest that future research efforts should be devoted to the human facet of tracing, to explore traceability practices in organisational settings, and to develop traceability approaches that support agile and DevOps practices. Finally, it is recommended that researchers leverage blockchain technology as a suitable technical solution to ensure the trustworthiness of traceability information in interorganisational software projects.publishedVersio

Systematic Model-based Design Assurance and Property-based Fault Injection for Safety Critical Digital Systems

With advances in sensing, wireless communications, computing, control, and automation technologies, we are witnessing the rapid uptake of Cyber-Physical Systems across many applications including connected vehicles, healthcare, energy, manufacturing, smart homes etc. Many of these applications are safety-critical in nature and they depend on the correct and safe execution of software and hardware that are intrinsically subject to faults. These faults can be design faults (Software Faults, Specification faults, etc.) or physically occurring faults (hardware failures, Single-event-upsets, etc.). Both types of faults must be addressed during the design and development of these critical systems. Several safety-critical industries have widely adopted Model-Based Engineering paradigms to manage the design assurance processes of these complex CPSs. This thesis studies the application of IEC 61508 compliant model-based design assurance methodology on a representative safety-critical digital architecture targeted for the Nuclear power generation facilities. The study presents detailed experiences and results to demonstrate the benefits of Model testing in finding design flaws and its relevance to subsequent verification steps in the workflow. Additionally, to study the impact of physical faults on the digital architecture we develop a novel property-based fault injection method that overcomes few deficiencies of traditional fault injection methods. The model-based fault injection approach presented here guarantees high efficiency and near-exhaustive input/state/fault space coverage, by utilizing formal model checking principles to identify fault activation conditions and prove the fault tolerance features. The fault injection framework facilitates automated integration of fault saboteurs throughout the model to enable exhaustive fault location coverage in the model

From Bugs to Decision Support – Leveraging Historical Issue Reports in Software Evolution

Software developers in large projects work in complex information landscapes and staying on top of all relevant software artifacts is an acknowledged challenge. As software systems often evolve over many years, a large number of issue reports is typically managed during the lifetime of a system, representing the units of work needed for its improvement, e.g., defects to fix, requested features, or missing documentation. Efficient management of incoming issue reports requires the successful navigation of the information landscape of a project. In this thesis, we address two tasks involved in issue management: Issue Assignment (IA) and Change Impact Analysis (CIA). IA is the early task of allocating an issue report to a development team, and CIA is the subsequent activity of identifying how source code changes affect the existing software artifacts. While IA is fundamental in all large software projects, CIA is particularly important to safety-critical development. Our solution approach, grounded on surveys of industry practice as well as scientific literature, is to support navigation by combining information retrieval and machine learning into Recommendation Systems for Software Engineering (RSSE). While the sheer number of incoming issue reports might challenge the overview of a human developer, our techniques instead benefit from the availability of ever-growing training data. We leverage the volume of issue reports to develop accurate decision support for software evolution. We evaluate our proposals both by deploying an RSSE in two development teams, and by simulation scenarios, i.e., we assess the correctness of the RSSEs' output when replaying the historical inflow of issue reports. In total, more than 60,000 historical issue reports are involved in our studies, originating from the evolution of five proprietary systems for two companies. Our results show that RSSEs for both IA and CIA can help developers navigate large software projects, in terms of locating development teams and software artifacts. Finally, we discuss how to support the transfer of our results to industry, focusing on addressing the context dependency of our tool support by systematically tuning parameters to a specific operational setting

Regulatory Compliance in Multi-Tier Supplier Networks

Over the years, avionics systems have increased in complexity to the point where 1st tier suppliers to an aircraft OEM find it financially beneficial to outsource designs of subsystems to 2nd tier and at times to 3rd tier suppliers. Combined with challenging schedule and budgetary pressures, the environment in which safety-critical systems are being developed introduces new hurdles for regulatory agencies and industry. This new environment of both complex systems and tiered development has raised concerns in the ability of the designers to ensure safety considerations are fully addressed throughout the tier levels. This has also raised questions about the sufficiency of current regulatory guidance to ensure: proper flow down of safety awareness, avionics application understanding at the lower tiers, OEM and 1st tier oversight practices, and capabilities of lower tier suppliers. Therefore, NASA established a research project to address Regulatory Compliance in a Multi-tier Supplier Network. This research was divided into three major study efforts: 1. Describe Modern Multi-tier Avionics Development 2. Identify Current Issues in Achieving Safety and Regulatory Compliance 3. Short-term/Long-term Recommendations Toward Higher Assurance Confidence This report presents our findings of the risks, weaknesses, and our recommendations. It also includes a collection of industry-identified risks, an assessment of guideline weaknesses related to multi-tier development of complex avionics systems, and a postulation of potential modifications to guidelines to close the identified risks and weaknesses

Evolution of security engineering artifacts: a state of the art survey

Security is an important quality aspect of modern open software systems. However, it is challenging to keep such systems secure because of evolution. Security evolution can only be managed adequately if it is considered for all artifacts throughout the software development lifecycle. This article provides state of the art on the evolution of security engineering artifacts. The article covers the state of the art on evolution of security requirements, security architectures, secure code, security tests, security models, and security risks as well as security monitoring. For each of these artifacts the authors give an overview of evolution and security aspects and discuss the state of the art on its security evolution in detail. Based on this comprehensive survey, they summarize key issues and discuss directions of future research

IMPROVING TRACEABILITY RECOVERY TECHNIQUES THROUGH THE STUDY OF TRACING METHODS AND ANALYST BEHAVIOR

Developing complex software systems often involves multiple stakeholder interactions, coupled with frequent requirements changes while operating under time constraints and budget pressures. Such conditions can lead to hidden problems, manifesting when software modifications lead to unexpected software component interactions that can cause catastrophic or fatal situations. A critical step in ensuring the success of software systems is to verify that all requirements can be traced to the design, source code, test cases, and any other software artifacts generated during the software development process. The focus of this research is to improve on the trace matrix generation process and study how human analysts create the final trace matrix using traceability information generated from automated methods. This dissertation presents new results in the automated generation of traceability matrices and in the analysis of analyst actions during a tracing task. The key contributions of this dissertation are as follows: (1) Development of a Proximity-based Vector Space Model for automated generation of TMs. (2) Use of Mean Average Precision (a ranked retrieval-based measure) and 21-point interpolated precision-recall graph (a set-based measure) for statistical evaluation of automated methods. (3) Logging and visualization of analyst actions during a tracing task. (4) Study of human analyst tracing behavior with consideration of decisions made during the tracing task and analyst tracing strategies. (5) Use of potential recall, sensitivity, and effort distribution as analyst performance measures. Results show that using both a ranked retrieval-based and a set-based measure with statistical rigor provides a framework for evaluating automated methods. Studying the human analyst provides insight into how analysts use traceability information to create the final trace matrix and identifies areas for improvement in the traceability process. Analyst performance measures can be used to identify analysts that perform the tracing task well and use effective tracing strategies to generate a high quality final trace matrix

Deducing Requirements From Agile Software Processes

In classical engineering practice, the elicitation of requirements is an important early project phase. Requirements help to define the project goals and scope, they serve as a basis for cost estimation, and in validated projects they are the cornerstone of the traceability matrix. However, requirements elicitation is difficult because of the abstract nature of the process and because there is uncertainty at the start of a project about what can be done. In recent software development practice, waterfall methods have fallen into disfavor, and agile methods are preferred. Agile methods avoid formal requirements specification, and instead use techniques such as scrums and user stories to specify development phases that are performed iteratively. In agile methods, requirements remain implicit and undocumented. While agile may avoid the difficulties of formal elicitation of requirements, it may in the process bypass the activity of analysis of user needs, and the generation of a baseline against which the implemented system can be validated. In this thesis we show that requirements can be deduced from the user stories and process maps that result from agile methodologies. A modified failure mode effects analysis approach is used to identify risks, failure modes, and countermeasures, and to evaluate risks and countermeasures by computing severity and likelihood of the risks, and the benefits of the countermeasures. The deduction of requirements from agile artifacts encourages an agile team to think through its preferences and proposed implementations, and objectively rate them. It captures the rationale for the user stories and process maps, and provides traceability from business goals to the functional requirements

SUPPORTING ENGINEERING DESIGN OF ADDITIVELY MANUFACTURED MEDICAL DEVICES WITH KNOWLEDGE MANAGEMENT THROUGH ONTOLOGIES

Medical environments pose a substantial challenge for engineering designers. They combine significant knowledge demands with large investment for new product development and severe consequences in the case of design failure. Engineering designers must contend with an often-chaotic environment to which they have limited access and familiarity, a user base that is difficult to engage and highly diverse in many attributes, and a market structure that often pits stakeholders against one another. As medical care in general moves towards personalized models and surgical tools towards less invasive options emerging manufacturing technologies in additive manufacturing offer significant potential for the design of highly innovative medical devices. At the same time however these same technologies also introduce yet more challenges to the design process. This dissertation presents a knowledge-based approach to addressing the existing and emerging challenges of medical device design. The approach aims to address these challenges using knowledge captured in a suite of modular ontologies modeling knowledge domains that must be considered in medical device design. These include ontologies for understanding clinical context, human factors, regulation, enterprise, and manufacturability. Together these ontologies support design ideation, knowledge capture, and design verification. These ontologies are subsequently used to formulate a comprehensive knowledge framework for medical device design, and to enable an innovative design process. Case studies analyzing the design of surgical tools in several medical specialties are used to assess the capabilities of this approach