Impact analysis of UML design changes using model slicing

9 - Reliability estimation considering warranty data, usage rate profile, and qualitative information on design changes

Design changes, during the detailed design phase of built environment projects, can have a detrimental effect on a project's duration and/or cost and as such need to be managed effectively. Accurate impact assessments are required to make informed decisions of whether or not design changes should be implemented. However, change management best practices give little guidance about how to carry out impact assessments. Interviews within the case study company (Arup) identified a tendency to rely heavily on the personal experience of engineering and project management practitioners when making impact assessments. This research is concerned with mitigating the risks associated with practitioners making judgments disproportionate to the true impact of a design change. A software support tool facilitating practitioners in making better informed impact assessments is proposed as a solution. The support tool incorporates design management and planning techniques and has been refined through a process of workshops with industry practitioners.

This study investigates the impact of design changes on time and cost control in the Namrole-Leksula I road project in Maluku Province. The research aims to identify key factors influencing design modifications and to develop strategies for managing their effects on project scheduling and budgeting. A quantitative-descriptive approach was employed, utilizing direct data collection, field technical surveys, and stakeholder interviews. The population comprises project execution personnel and government officials, with purposive sampling of 20 experts. Data were analyzed using Critical Path Method (CPM) tools and volume comparison techniques for work items. The results indicate that unstable subgrade soil, road width variability, and damaged structures significantly affected work volume and necessitated contract amendments without changing total project duration or budget. The study concludes that integrating CPM with field assessments provides effective management for mitigating risks from mid-project design changes while maintaining quality and timeline compliance. Future research should explore broader contexts and advanced monitoring tools.Abstract

Software change impact analysis (CIA) methods enable developers to understand potential impacts of a code change so that the change can be executed confidently without affecting reliability of the software. However, existing CIA approaches do not support CIA for all source code granularities. Additionally, they lack support for inter-granular change impact queries and hidden dependencies. This paper introduces Augur, an automated static code analysis-based CIA approach that addresses these shortcomings. Augur infers and maintains semantic and environment dependencies along with data and control dependencies between source code entities across granularities. Additionally, Augur uses Change Impact Query Language, a novel query language for impact analysis proposed in this paper, to support inter-granular CIA queries with batch querying feature. Augur has been realized as a Visual Studio extension called Augur-Tool. We have conducted quantitative evaluation on two open-source and two industrial projects to assess the accuracy of the tool. Results from the evaluation indicate that Augur provides CIA with high accuracy (average precision 55% and average recall 85%).

Lack of objective design change analysis model is a major problem for the accurate change impact prediction. To solve this problem, this paper proposes an ontology-based model named design change analysis model to organize the unstructured design properties as a basis for design change management. Design change analysis model is constructed by formalizing the mechanical design specifications in the form of design property network. Benefiting from the fine-grained organization, design change analysis model ensures the objectivity and accuracy of design change impact assessment. Since design change analysis model satisfies the attributions of small-world network, the change impact assessment should focus on more meaningful aspects including the linkage weight, node degree, and long-chain linkages of design change analysis model. With design change analysis model, the changeability of each design property which provides a quantified change propagation measurement could be evaluated. Additionally, different components could be distinguished in design change analysis model by using clustering algorithms without specializing them in advance. Design change analysis model modeled in web ontology language is a semantic enrichment model. It supports the semantic design change management due to the mathematic logic-based semantics of web ontology language and semantic web rule language. These lays a basis for updating changes among heterogeneous product development systems, and acquiring feasible change impacted properties.

Large systems often have a long life-span and their system and software architecture design comprise many intricately related elements. The verification and maintenance of these architecture designs require an understanding of how and why the system are constructed. Design rationale is the reasoning behind a design and it provides an explanation of the design. However, the reasoning is often undocumented or unstructured in practice. This causes difficulties in the understanding of the original design, and makes it hard to detect inconsistencies, omissions and conflicts without any explanations to the intricacies of the design. Research into design rationale in the past has focused on argumentation-based design deliberations. Argumentation-based design rationale models provide an explicit representation of design rationale. However, these methods are ineffective in communicating design reasoning in practice because they do not support tracing to design elements and requirements in an effective manner. In this thesis, we firstly report a survey of practising architects to understand their perception of the value of design rationale and how they use and document this knowledge. From the survey, we have discovered that practitioners recognize the importance of documenting design rationale and frequently use them to reason about their design choices. However, they have indicated certain barriers to the use and documentation of design rationale. The results have indicated that there is no systematic approach to using and capturing design rationale in current architecture design practice. Using these findings, we address the issues of representing and applying architecture design rationale. We have constructed a rationale-based architecture model to represent design rationale, design objects and their relationships, which we call Architecture Rationale and Element Linkage (AREL). AREL captures both qualitative and quantitative rationale for architecture design. Quantitative rationale uses costs, benefits and risks to justify architecture decisions. Qualitative rationale documents the issues, arguments, alternatives and tradeoffs of a design decision. With the quantitative and qualitative rationale, the AREL model provides reasoning support to explain why architecture elements exist and what assumptions and constraints they depend on. Using a causal relationship in the AREL model, architecture decisions and architecture elements are linked together to explain the reasoning of the architecture design. Architecture Rationalisation Method (ARM) is a methodology that makes use of AREL to facilitate architecture design. ARM uses cost, benefit and risk as fundamental elements to rank and compare alternative solutions in the decision making process. Using the AREL model, we have proposed traceability and probabilistic techniques based on Bayesian Belief Networks (BBN) to support architecture understanding and maintenance. These techniques can help to carry out change impact analysis and rootcause analysis. The traceability techniques comprise of forward, backward and evolution tracings. Architects can trace the architecture design to discover the change impacts by analysing the qualitative reasons and the relationships in the architecture design. We have integrated BBN to AREL to provide an additional method where probability is used to evaluate and reason about the change impacts in the architecture design. This integration provides quantifiable support to AREL to perform predictive, diagnostic and combined reasoning. In order to align closely with industry practices, we have chosen to represent the rationale-based architecture model in UML. In a case study, the AREL model is applied retrospectively to a real-life bank payment systems to demonstrate its features and applications. Practising architects who are experts in the electronic payment system domain have been invited to evaluate the case study. They have found that AREL is useful in helping them understand the system architecture when they compared AREL with traditional design specifications. They have commented that AREL can be useful to support the verification and maintenance of the architecture because architects do not need to reconstruct or second-guess the design reasoning. We have implemented an AREL tool-set that is comprised of commercially available and custom-developed programs. It enables the capture of architecture design and its design rationale using a commercially available UML tool. It checks the well-formedness of an AREL model. It integrates a commercially available BBN tool to reason about the architecture design and to estimate its change impacts.

The practice of cardiovascular surgery demands daily interface with sophisticated technologies including most commonly the cardiopulmonary bypass (CPB) machine. Although other industries have recognized the importance of considering human factors in the design of machines to reduce operator error, the evolution of the CPB machine over the past half-century has been characterized by incremental modifications of component parts with attention principally to mechanical efficiency and biocompatibility, but with little awareness of the impact of design changes on the human user. As a first step in the redesign of a safer pump, systematic observations of perfusionists during 10 adult and pediatric cases were conducted by staff cardiac surgeons and by human factors experts. Observations were classified according to accepted ergonomics principles. Perfusionists also performed usability evaluations and provided feedback concerning the design and functionality of bypass machines. Problems identified clustered around several usability themes. Issues with displays (8% of total comments) included location, legibility, format, and integration. Multiple problems with controls (11% of total comments) including location, sensitivity, and shape were identified, as were issues with audible alarms (6% of total comments). Component integration (14% of comments) and workspace design (21% of comments) were suboptimal as well. Procedural and communication issues (21% of comments) related to pump utilization, rather than pump design, were also identified, which stemmed from a lack of standardized operating room practices. Clinical issues (14% of comments) surrounding care of the patient were also identified but were not further analyzed, because these comments did not pertain to the design of the perfusion pump. Our observations confirmed the hypothesis that opportunities exist to incorporate usability and ergonomics insights into CPB machine design to optimize the human/technology interface. Such fundamental design considerations may improve the safety of the conduct of CPB and, consequently, outcomes after cardiovascular surgery.

Modelling and performance of a small siphonic hydropower system

<div class="htmlview paragraph">The method of fatigue life evaluation and validation testing under operational conditions is a prerequisite to achieve optimal designs with respect to weight and long-term durability of the structure considered.</div> <div class="htmlview paragraph">Criteria like driving behavior and braking performance, influenced by global stiffness as well as fatigue life evaluation were taken into account when optimizing a forged 6.5 front axle beam of a heavy truck. The procedure for weight optimization includes the following steps: <ul class="list disc"> <li class="list-item"><div class="htmlview paragraph">Stress analysis e.g. using strain gage techniques and/or Finite Element Method,</div></li> <li class="list-item"><div class="htmlview paragraph">Road load data acquisition and derivation of design spectrum describing customer usage,</div></li> <li class="list-item"><div class="htmlview paragraph">Fatigue testing under constant amplitude and/or variable amplitude loading to establish component related SN-curves and/or fatigue life curves,</div></li> <li class="list-item"><div class="htmlview paragraph">Fatigue life evaluation using damage accumulation hypothesis (Miner's Rule),</div></li> <li class="list-item"><div class="htmlview paragraph">Optimization and weight reduction (in this case 14% weight savings were achieved) based on fatigue life evaluation.</div></li> <li class="list-item"><div class="htmlview paragraph">Validation testing using multi-axial computer controlled, servohydraulic test rigs.</div></li> </ul></div> <div class="htmlview paragraph">Since vehicle manufacturers tend to leave more of the development responsibility to the component manufacturer, the methodology described is directed to the component manufacturer and is condensed, introducing the “service strength evaluation diagram” used for design optimization. Using this technique a designer can get a good feel for the relative impact of design changes with respect to durability life under service conditions.</div>

When modifying a cyber-physical system, the consequences of changes need to be understood beforehand to adequately assess risks and costs. Model-based change impact analysis is key for estimating the impact of a change before actually modifying the system. Existing change impact analysis approaches apply very similar algorithms for change propagation to instances of domain-specific metamodels. However, they lack fundamental concepts for domain-spanning change impact analysis. In this paper, we propose a generic methodology for domain-spanning change impact analysis to address limitations of existing approaches. Evaluation results show the relevancy and comprehensives of the methodology for several domains.

Software change impact analysis (CIA) is a key technique to identify the potential ripple effects of the changes to software. Coarse-grained CIA techniques such as file, class and method level techniques often gain less precise change impacts, which are difficult for practical use. Fine-grained CIA techniques, such as slicing, can be used to gain more precise change impacts, but need more time and space cost. In this paper, by combining the features of the coarse-grained technique and the fine-grained technique, a variable-method (VM) correlation-based CIA technique called VM-CIA is proposed to improve the precision of static CIA. First, the VM-CIA technique uses the abstract syntax tree (AST) of program to construct a novel intermediate representation called variable and method triple (VMT), which is used to analyze the correlation between the variables and methods. Second, the VM-CIA technique proposes the single-change impact analysis algorithm and multi-change impact analysis algorithm to compute the impact set based on the VMT representation. In addition, the VM-CIA technique can get a sorted impact set which is more accurate than the existing CIA techniques. The empirical results show that the VM-CIA technique can greatly improve the precision (19%) over traditional the CIA techniques, while at the cost of a little recall (5%). Moreover, the empirical studies also show that the VM-CIA technique predicts a ranked list of potential impact results according to the distance measure, which can greatly facilitate the practical use.

As the complexity of a software system grows, it becomes increasingly difficult for developers to be aware of all the dependencies that exist between artifacts (e.g., files or methods) of the system. Change impact analysis helps to overcome this problem, as it recommends to a developer relevant source-code artifacts related to her current changes. Association rule mining has shown promise in determining change impact by uncovering relevant patterns in the system's change history. State-of-the-art change impact mining algorithms typically make use of a change history of tens of thousands of transactions. For efficiency, targeted association rule mining focuses on only those transactions potentially relevant to answering a particular query. However, even targeted algorithms must consider the complete set of relevant transactions in the history. This paper presents ATARI, a new adaptive approach to association rule mining that considers a dynamic selection of the relevant transactions. It can be viewed as a further constrained version of targeted association rule mining, in which as few as a single transaction might be considered when determining change impact. Our investigation of adaptive change impact mining empirically studies seven algorithm variants. We show that adaptive algorithms are viable, can be just as applicable as the start-of-the-art complete-history algorithms, and even outperform them for certain queries. However, more important than the direct comparison, our investigation lays necessary groundwork for the future study of adaptive techniques and their application to challenges such as the on-the-fly style of impact analysis that is needed at the GitHub-scale.

Recognizing the potential interactions and synergies between adaptation and mitigation in land-use policies in general and forest policies in particular, research on climate change policy has increasingly focused on integrating both objectives simultaneously (hereafter “interaction model”). However, while support exists for the integration of adaptation and mitigation, very few policies have successfully integrated both objectives in practice (hereafter “separation model”). In addition to the interaction and separation models, we introduce the “adaptation-first model”—an approach to climate policy integration that centers adaptation at the core of forest management, with mitigation as one benefit amongst others—and assess whether it more effectively characterizes the practical realities of forest management than the separation or interaction models. Drawing on a review of policy documents, a survey (n = 48) and interviews (n = 22) with government managers in British Columbia (BC), Canada, we analyze which of the three models have been used for integrating climate objectives into BC’s forest policy and explore views of government managers on the relationships and trade-offs between adaptation and mitigation and which model should be prioritized for their integration into forest management. Our analysis of climate-focused forest policy documents indicates that a possible shift from the separation to the interaction model is taking place in BC. However, our results also indicate that while government managers support the interaction model in principle, they perceive numerous barriers to policy integration that may prevent the shift towards the interaction model to materialize in practice. Because of the fundamental perceived differences in the levels at which adaptation and mitigation intervene in decision-making, government managers in our study were generally more comfortable with the adaptation-first model, which ultimately suggests the need to rethink how we frame climate integration into forest management and policies.

Safety standards prescribe change impact analysis (CIA) during evolution of safety-critical software systems. Although CIA is a fundamental activity, there is a lack of empirical studies about how it is performed in practice. We present a case study on CIA in the context of an evolving automation system, based on 14 interviews in Sweden and India. Our analysis suggests that engineers on average spend 50–100 h on CIA per year, but the effort varies considerably with the phases of projects. Also, the respondents presented different connotations to CIA and perceived the importance of CIA differently. We report the most pressing CIA challenges, and several ideas on how to support future CIA. However, we show that measuring the effect of such improvement solutions is non-trivial, as CIA is intertwined with other development activities. While this paper only reports preliminary results, our work contributes empirical insights into practical CIA.

"Change Impact Analysis" is the process of determining the consequences of a modification to software. In theory, change impact analysis should be done during software maintenance, to make sure changes do not introduce new bugs. Many approaches and techniques are proposed to help programmers do change impact analysis automatically. However, it is still an open question whether and how programmers do change impact analysis. In this paper, we conducted two studies, one in-depth study and one breadth study. For the in-depth study, we recorded videos of nine professional programmers repairing two bugs for two hours. For the breadth study, we surveyed 35 professional programmers using an online system. We found that the programmers in our studies did static change impact analysis before they made changes by using IDE navigational functionalities, and they did dynamic change impact analysis after they made changes by running the programs. We also found that they did not use any change impact analysis tools.