Operational semantics of goal models in adaptive agents

Goal models are an example of requirement modeling language that has been applied to support the runtime monitoring and diagnosis of software systems and to steer self-adaptive systems. When creating a goal model, requirement engineers make assumptions concerning how the goals relate to each other and when they should be considered as satisfied. In dynamic environments, however, the assumptions made in the model may be (or become) invalid. This may result in a system that does not satisfy the stakeholders' needs and, when the model is used in adaptive systems, ineffective reconfigurations. Only few and preliminary works address the automated validation of goal or requirement models. In this paper we propose the use of probabilistic models (Bayesian Networks) to determine the validity of the assumptions underlying a goal model. We employ empirical data and probabilistic inference to automatically determine a quantitative degree of validity of goal model assumptions. We illustrate the approach on a smart traffic scenario.

Embedded systems are used for critical applications that must adhere to safety constraints. Developers of these systems face three key challenges when attempting to apply existing requirements analysis approaches: (1) declaratively specifying functional requirements, non-functional requirements, and constraints; (2) operationally modeling the required behavior; and (3) analyzing the requirements models of the behavior for adherence to the constraints. To address these challenges, this paper introduces Cobra patterns that provide UML and goal model templates to be instantiated in tandem to create models that capture system requirements and their constraints. Structural consistency is established through the construction of the goal and UML models. Behavioral consistency is achieved by analyzing the UML models for adherence to the constraints specified in the goal model.

Professional software engineers are the key assets of the core competency of a company developing highly complicated safety-critical software-intensive automotive systems. Professional software engineers have been generally trained through an education and training program home-brewed in the company. However, the conventional curriculum of the program is developed in a rather ad hoc way, and hard to qualify the trainees. In this article, we propose a curriculum development methodology for professional software engineers based on goal model. We define a strategic goal of professional software engineers, and derive three tactical educational sub-goals of acquisition of advanced software engineering, the practice of software engineering and establishment of philosophy of leadership. We propose a methodology to develop a body of knowledge of automotive software engineering, curriculum, and associated teaching methods based on the educational goal model. We applied the methodology to the education and training program for automotive professional software engineers at DENSO. Comparing the previous program, we demonstrate the effectiveness of the proposed methodology.

A critical phase in the task of software engineering is represented by the elicitation of requirements from the users. The paper presents a cognitive approach to the elicitation of functional requirements of software systems founded on the modelling of the application domain. The framework outlined is grounded on an incremental process aimed at building a description of the real world, as perceived by the user and expressed in an informal way, in terms of physical objects and activities on them. The domain model is developed by applying the analyst stereotypical knowledge to the real world as described by the user, and requires the identification of knowledge chunks that may consent the process of specification reuse in different application domains. >

[Background]: Developing conceptual models is an integral part of the requirements engineering (RE) process. Goal models are requirements engineering conceptual models that allow diagrammatic representation of stakeholder intentions and how they affect each other. A specific goal modeling language construct, the contribution of goal satisfaction of one goal to another, plays a central role in supporting decision problem exploration within goal models. [Aims]: We report on an experiment whose aim was to measure the user perception of the meaning of the aforementioned modeling construct. [Method]: A set of contributions under different scenarios were given to experimental participants who were asked what they thought the effect of the contribution was. [Results]: We found that participants are not always in agreement either within themselves or with the designers' intentions on the meaning of the language. [Conclusions]: The results call for possible adaptations to the way goal modeling languages are used.

In the software engineering (SE) domain the EU challenge on semantic systems and services motivates better support of knowledge creation as well as better access of SE stakeholders to the knowledge they need to perform their activities. Application Lifecycle Management (ALM) is the coordination of development lifecycle activities by process automation, management of relationships between artifacts, and reporting on development progress. ALM focuses on the integration of knowledge between the tools that support SE roles and thus seems particularly well suited to leverage benefits from advanced semantic technologies and services that overcome limitations from semantic gaps in today's heterogeneous SE platforms. In this paper, we present a semantic requirements tracing approach (SemTrace), which makes the implicit interdependencies between requirements and other artifacts explicit. We evaluate the proposed approach in a change impact analysis use case. Initial results show that the SemTrace approach allows for a flexibly identification of semantically connected artifacts in SE projects.

We explore the use of a semantic model to support a group of strategic business analysts in their daily work. In particular, we present a set of modeling constructs for representing goals, events and actors that are relevant to the work of analysts. We also describe a qualitative goal analysis procedure which makes it possible to reason about a goal model under different assumptions. The paper also reports on an incremental document classification scheme that can be used to classify relevant documents with respect to the concepts constituting the semantic model.

Definition of programming languages consists of the formal definition of syntax and semantics. One of the most popular semantic methods used in various stages of software engineering is structural operational semantics. It describes program behavior in the form of state changes after execution of elementary steps of program. This feature makes structural operational semantics useful for implementation of programming languages and also for verification purposes. In our paper we present a new approach to structural operational semantics. We model behavior of programs in category of states, where objects are states, an abstraction of computer memory and morphisms model state changes, execution of a program in elementary steps. The advantage of using categorical model is its exact mathematical structure with many useful proved properties and its graphical illustration of program behavior as a path, i.e. a composition of morphisms. Our approach is able to accentuate dynamics of structural operational semantics. For simplicity, we assume that data are intuitively typed. Visualization and facility of our model is not only a new model of structural operational semantics of imperative programming languages but it can also serve for education purposes.

Many of the current traditional system engineering (TSE) approaches for elicitation of requirements are insufficient when deployed in complex situations. TSE approach to requirement elicitation is based on assumption of stable environmental conditions. However, the elicitation of requirements for complex systems (i.e., interdependent critical infrastructures) requires innovative approaches that should go beyond technical aspects of a situation. Complex situations arise when multiple complex infrastructures interdependently interact to provide goods and services for public health and safety. The elicitation of requirements for such a system must consider the nature of system of interest, its environment and system observer. On this backdrop, this paper reviews complexity associated with attained requirements for complex infrastructures, failures and provides an overview of a proposed high-level framework for infrastructure requirement elicitation.

Modelling human-centric aspects of end-users with iStar

Context: Self-adaptive systems have been studied in software engineering over the past few decades attempting to address challenges within the field. There is a continuous significant need to fully understand the behavior and characteristics of the systems that operate in dynamic environments. By learning the behavior pattern of the environment, we can avoid unnecessary adaptations imbalance efforts for adaptation. As such, there exist research in the area of machine learning aimed at understanding dynamic environments regarding self-adaptive systems. Objective: This study aims to help software practitioners to address adaptation concerns by performing a systematic literature review that provides a comprehensive overview of using machine learning (ML) in self-adaptive systems. We summarize state-of-the-art Of the ML approaches used to handle self-adaptation to help software engineers in the proper selection of ML techniques based on the adaptation concern. Method: This review examines research published between 2001 and 2019 on ML implementation in self-adaptive systems, focusing on the adaptation aspects and purposes. The review was conducted by analyzing major scientific databases that resulted in 78 primary studies from 315 papers from an automatic search. Result: Finally, this study recommends three future research directions to enhance the application of machine learning in self-adaptive systems.

After business analysis and software economics lay the foundation, requirements engineering structures the phase of eliciting, analysing, specifying and verifying the objectives and constraints for a software system under development. It is not yet fully investigated how to systematically integrate environmental sustainability into this discipline in order to achieve ‘greener’ software systems. This chapter outlines an approach of how to incorporate environmental sustainability as an objective from the very start in requirements engineering by using a reference artefact model with a goal model and continuous deduction and refinement. Thereby, software engineers are enabled to strategically align the objective of environmental sustainability with the other objectives for the software system under development.

Human values are principles that guide human actions and behaviour in personal and social life. With the pervasive influence of software in our lives, it becomes imperative to align and reflect these values in them. Therefore, ignoring human values during the early stages of software development can detrimentally impact the adoption and sustained usage of software products. Human values are inherently embedded in software engineering artefacts and decision-making processes; however, early elicitation of stakeholder values increases the chances of their inclusion into the developed system. In this study, we leverage Pharaon, a research and innovation initiative under the European Union's Horizon 2020 program, as a case study. We analysed stakeholder requirements expressed as motivational goal models consisting of functional, quality, and emotional goals in three large-scale trial applications of the project. We successfully identified 9 out of 10 human values according to the theory of human values by Schwartz from the motivational goal models that represent the requirements of our project. Our findings highlight the dominant trend of stakeholder values being embedded in emotional goals and show that almost 45% of the identified values belong to the value categories of Security and Self-direction. Our research extends prior work in emotional goal modelling in requirements engineering by linking emotional goals to various stakeholder roles and identifying their values based on the Schwartz theory of human values.

Requirements Engineering (RE) is a critical process in Software Engineering (SE) activities. RE helps stakeholders to manage requirements appropriately before dedicated requirements are used to design and implement software. The first stage in RE process is known as requirements elicitation whereby during elicitation, stakeholders will perform a set of activities to permit understanding in problem domain for respected scenario and hence proposing a set of established requirements in developing software. In elicitation, stakeholders need to collaborate and communicate in order to produce unambiguous requirements and create mutual agreement for software design and development. This can produce desired solution for all stakeholders. Soft issue is one of non-technical requirements that can associate with social presence, social interaction elements such as comfort, connectedness and motivation. This requirements need to be emphasized during RE process especially for a system that is categorized in Computer- Supported Collaboration Working (CSCW) domain. Users need CSCW domain system to carry out virtual communication, knowledge sharing via system's features. The aim of this paper is to carry out a preliminary study on RE process and requirements elicitation activities by identifying whether soft issues have been engaged in existing requirements elicitation process. Another aim is to compare stakeholders' roles based on selected articles. The method to investigate requirements elicitation process is done by identifying existing elicitation processes as well as involvement of stakeholders' collaboration during elicitation. According to the study, the comparison of existing requirements elicitation processes and comparison of job roles have been produced as a result in this paper.

Organizations increasingly have to cope with the digital transformation, which is ubiquitous in today’s society. Strategic analysis is an important first step towards the success of digital transformation initiatives, whereby all the elements (e.g., business processes and IT infrastructure) that are required to achieve the transformation can be aligned to the strategic goals and decisions. In this paper, we work towards a modeling method to perform model-based strategic analysis. We explicitly account for information technology (IT) infrastructure because of its key role for digital transformation. Specifically, (1) based on a conducted study on business scholar literature and existing work in conceptual modeling, a set of requirements is first identified; (2) then, we propose a modeling method that integrates, among others, goal modeling, strategic modeling, and IT infrastructure modeling. The method exploits, among others, three previously designed domain specific modeling languages in the Multi-Perspective Enterprise Modeling (MEMO) family: GoalML, SAML and ITML; (3) we illustrate the use of the modeling method in terms of a digital transformation initiative in the electricity sector; and finally, (4) we evaluate the proposed modeling method by comparing it with the conventional SWOT analysis and reflecting upon the fulfillment of the identified requirements.