Abstract The physics of notations (PoN) is a framework for designing cognitively effective notations. Cognitive effectiveness refers to the ease (speed and accuracy) by which model readers read models. In 2019, a PoN‐Enabled notation for use case diagrams was proposed. It has been empirically proven that the cognitive effectiveness of this new notation is superior to the original use case notation. The new notation however relies in part on the use of color. The accessibility of this new design has not been validated for use by the colorblind community, or any users who need to use a grayscale version of the models created. The PoN framework was not designed to explicitly account for the colorblind community or users who can only access grayscale versions of models. Inclusivity should not be an afterthought in software engineering practice or research. To this end, this paper empirically evaluates the cognitive effectiveness of the PoN‐enabled use case notation in situations where it is viewed in grayscale.

In 2009, Moody introduced nine principles for evaluating, improving and designing cognitively effective notations called the “Physics of Notations” [49] motivating many research works ever since, being cited more than 1250 times at the time of writing this paper. Many research works have adopted the nine principles of the Physics of Notations to improve existing notations or devise new notations. Modeling is a two-step process that has the goal of communicating a mental concept by a model constructor (step one) to a model reader (step two). A subset of the research works utilizing the Physics of Notations have empirically validated the cognitive effectiveness of the new notations by their readers. However, there lacks any empirical evidence that investigates the effect of using Physics of Notations-enabled notations in model construction. This is a serious matter to be investigated as naturally model construction preludes model comprehension. Poorly constructed models can at best be poorly comprehended by its readers having dire consequences in downstream development activities. This paper reports on three different experiments that use software engineering professionals as subjects. The experiments investigate the effect of using notations that adhere to the Physics if Notations principles on model construction efforts. The results do not indicate an outright advantage for model constructors who utilize Physics of Notations-enabled notations in comparison to using their original versions of these notations.

Secure software engineering entails that security concerns needs to be considered from the early phases of development, as early as the requirements engineering phase. Misuse cases is a well-known security analysis and specifications techniques, based on the popular use case modeling technique, that takes place in the requirements engineering phase. Similar to use case modeling, misuse case modellers are prone to committing modeling mistakes and applying antipatterns. As a result, misuse case models need to be analysed to determine if they contain fallacious design decisions. Changes, known as refactoring, to the misuse case diagrams are then required to remedy any design issues and such changes which would normally be manually applied. However, manual application of such changes in misuse case models are prone to human error, further compounding the design issues in a given misuse case model. To this end, this paper presents a model transformation approach to systematically apply changes to misuse case models. A case study related to a book store is presented to illustrate the application and feasibility of the approach.

Continuous increase in urban population causes enormous pressure on the limited resources of cities including transport, energy, water, housing, public services, and others. Hence, the need to plan and develop smart cities-based solutions for enhanced urban governance is becoming more evident. The technological framework for smart cities services connect hundreds of data collecting device networks (e.g., sensor networks) with central server or cloud through Internet. Scheduling of these enormous data (or big data) both at the device networks and central server/cloud is significantly important to facilitate timely and priority-based smart city services. This paper introduces a cloud- based big data framework and Priority-based, Dynamic and Time sensitive data processing and Scheduling (PDTS) approach that works both for the device networks and cloud-based big data framework. Simulation results demonstrate that the proposed PDTS approach reduces the number of data transmission and data processing time as opposed to data scheduling only in cloud-based big data framework.

Model driven security has become an active area of research during the past decade. While many research works have contributed significantly to this objective by extending popular modeling notations to model security aspects, there has been little modeling support for state-based views of security issues. This paper undertakes a scientific approach to propose a new notational set that extends the UML (Unified Modeling Language) statecharts notation. An online industrial survey was conducted to measure the perceptions of the new notation with respect to its semantic transparency as well as its coverage of modeling state based security aspects. The survey results indicate that the new notation encompasses the set of semantics required in a state based security modeling language and was largely intuitive to use and understand provided very little training. A subject-based empirical evaluation using software engineering professionals was also conducted to evaluate the cognitive effectiveness of the proposed notation. The main finding was that the new notation is cognitively more effective than the original notational set of UML statecharts as it allowed the subjects to read models created using the new notation much quicker.

CONTEXT: Previous work suggests that half of the companies that have tried global software development (GSD) have failed to realise the anticipated outcomes, the root cause of which is often related to requirements problems. Despite the importance of this problem, little research has been carried out to improving requirements engineering process in the GSD projects. OBJECTIVE: In this paper an ongoing project is discussed which will bring together the work of researchers and software development experts to develop a framework for the requirements engineering process of global software development projects (GlobReq). Managers of GSD projects will be able to use GlobReq to plan a requirements engineering process suitable for a specific GSD project. In this paper the need for such a framework along with the proposed methodology, novelty and the preliminary results are discussed. METHODOLOGY: The basis of the GlobReq framework is Sommerville et al's framework of 66 requirements best practices as well as our empirical study with GSD organisations. INITIAL RESULTS: The initial findings from 5 organisations are interesting to observe that not all 66 RE best practices are perceived as high value practices for GSD projects.

Use case modeling is popular technique to elicit and model functional requirements of a software development project. Requirements are seldom stable and consistently change throughout the life cycle of a project. It is crucial to understand how and why a system's functional requirements has reached its current state. To this end, this paper presented UseCaseDiff, an algorithm to automatically detect structural changes between subsequent versions of a use case model. The approach was applied to two subsequent versions of a use case model for a distributed biodiversity database system. The results validate the correctness of the algorithm in detecting the structural differences between the subsequent versions of the use case model.

Use case modeling is an effective technique used to capture functional requirements. Use case models are mainly composed of textual descriptions written in natural language and simple diagrams that adhere to a few syntactic rules. This simplicity can be deceptive as many modelers create use case models that are incorrect, inconsistent, and ambiguous and contain restrictive design decisions. In this paper, a new methodology is described that utilizes antipatterns to detect potentially defective areas in use case models. This paper introduces the tool ARBIUM, which will support the proposed technique and aid analysts to improve the quality of their models. ARBIUM presents a framework that will allow developers to define their own antipatterns using OCL and textual descriptions. The proposed approach and tool are applied to a distributed biodiversity database use case model to demonstrate its feasibility. Our results indicate that they can improve the overall clarity and precision of use case models

Use case (UC) models describe functional requirements as a set of interactions between a software system and its environment. In essence, UC descriptions state a set of workflows that would allow a system's user to benefit from its services. It is critical that designers have a common and precise understanding of what these workflows are. Otherwise they are in danger of building the 'wrong' system. Traditionally, UC descriptions are authored using natural language, which as shown in this article, proves to be a poor vehicle, and insufficient, to describe the underlying workflows. Simply, the inherit ambiguity in natural language leads to misinterpretations and misunderstandings. UC diagrams do not provide any information about the dependencies between workflows spanning several UCs. In this paper, we present the process AGADUC, which systematically generate activity-like diagrams that represent the embedded workflows in the UC textual descriptions. A GADUC provides a great deal of information regarding how UCs are dependent on each other, without the need to iterate through several pages of UC descriptions. Using activity-like diagram ensures that all stakeholders have a precise and consistent understanding of the workflows. A case study conducted on a simplified Library case is presented and have shown that AGADUC overcomes many limitations in traditional UC models. The featured tool AREUCD automates the AGADUC process and it is demonstrated within the case study