Reuse has often been claimed in the software engineering literature to improve thequality and reduce the cost of software. Motivated by the idea that these gains canbe multiplied if reuse can be achieved earlier in the software life-cycle, a subset ofthe requirements engineering literature has focused, since the inception of the field,on investigating approaches to reuse at the requirements level. A wide array of differentapproaches now exist within this space. However, these approaches offer varyingdegrees of generality and utility. Generality is important because it enables a requirementsengineer to utilise the same reuse library across multiple projects. Utility isimportant because it is a measure of the extent to which effort is reduced by utilising areuse approach. This thesis presents Reuse-Oriented Requirements Engineering (RORE): a systematicframework to support the production of requirements models by reuse. RORE aimsto improve on existing requirements-reuse approaches in respect of the generalityutilitytrade-off. RORE seeks to do this by bringing together the strengths of two existingrequirements-level reuse approaches: The Domain Theory and Problem-OrientedSoftware Engineering (POSE - a refinement of Jackson’s Problem Frames Approach).This thesis evaluates RORE with respect to both generality and utility, and comparesRORE against both frameworks. The major conclusion of the thesis is that while ROREimproves on each framework in respect of some, but not all, evaluation metrics, ROREdoes succeed in offering a level of generality which compares favourably to existinghighly general approaches, and without significantly reducing the utility of the approach.

Context: Requirement validation is a phase of the software development life cycle where requirements are validated to get rid of inconsistency, incompleteness. Stakeholders involved in the validation process to make requirements are suitable for the product. Requirement validation techniques are for validating the requirements. Selection of requirements validation techniques related to the factors that need to consider while validating requirements makes the validation process better. This paper is about the factors that influence the selection of requirements validation technique and analyzing the most critical factors. Objectives: Our research aim is to find the factors influencing the selection of requirements validation techniques and evaluating critical factor from the factors list. To achieve our goal, we are following these objectives. To get a list of validation techniques that are currently being used by organizations, and to enlist the factors that influence the requirements validation technique. Methods: To identify the factors influencing the selection of requirement validation techniques and evaluating the critical factors, we conducted both a literature review and survey. Results: From the literature review, two articles considered as our starter set, and through snowball sampling, a total of fifty-four articles were found relevant to the study. From the results of the literature review, we have formulated a questionnaire and conducted a survey. A total of thirty-three responses have gathered from the survey. The survey obtains the factors influencing the requirement validation techniques. Conclusions: The factors we got from the survey possess a mixed view like each factor has its critically in different aspects of validation. Selecting one critical factor is not possible during the selection of the requirements validation technique. So, we shortlisted the critical factors that have more influence in the selection of requirement validation techniques, Factors, Requirements validation techniques.

Requirements engineering (RE) involves human-centric activities that require interaction among different stakeholders. Traditionally, RE has been considered as a centralized, collocated, and phase-specific process. However, in open source software (OSS) development environments, the core RE activities are iterative and dynamic and follow a rather decentralized software engineering paradigm. This crosscutting characteristic of open source RE can be conceptualized using the “Twin Peaks” model that weaves RE together with software architecture. Although many weaving mechanisms have been proposed in recent years, the lack of theoretical underpinning limits a mechanism’s applicability and usefulness in different scenarios. In this research, we hypothesize stakeholders’ social interaction as an ecologically valid weaving mechanism of the “Twin Peaks” in open source RE. In this work, we use the phrase “stakeholders’ social interaction” to indicate interaction among stakeholders regarding the software system that takes place through some communication means, such as posting comments and artifacts over the issue tracking system. We investigate the influence of stakeholders’ social interaction in different RE activities, in particular, requirements identification, creativity in RE, and requirements implementation of OSS systems. This research enables us to gain valuable insights to generate guidelines for enhancing software engineering practice in relevant areas.

Software intensive systems are developed to provide solutions in some problem domain and software engineering principles are employed to develop and implement that system. Software engineering principles should enhance the development and production of software artifacts and yet the artifacts often lack in quality. Crucial in the development process are requirements engineering activities and methods for software documentation. This research focused on requirements engineering activities, software requirements documentation and employed a new approach in these activities that incorporated ontology engineering principles. Ontology engineering refers to the set of activities concerned with the ontology development process, the ontology life cycle, the methods for building ontologies, and the tool suites and languages that support them. Ontologies facilitate domain knowledge reuse and sharing and provides a common vocabulary to system developers. The motivation of this research came from Ambr´osio and Kaiya, advocating the definition of the Software Requirements Knowledge Area of the Software Engineering Body of Knowledge (SWEBOK ) within an ontology system. The resulting system utilized the benefits of intelligent reasoning to elicit, automatically verify, extract and document software requirements. The requirements engineering process was modeled in an ontology. An ontology is a machine-readable data structure that distinctly defines concepts and describes relationships among those concepts. The requirements engineering process and ontology were the focal points in this research. A baseline ontology for software requirements engineering was created. The following are contributions of this research. A methodology was designed to enhance the software documentation production process. An initial ontology model of SWEBOK recommended data items was created. A method was provided to verify software requirements as they were elicited, entered and maintained in an ontology. A method was created that electronically provided provenance of software requirements. Software was created to automatically extract the software requirements from within an ontology.

The success of software development projects heavily depends on effectively capturing and meeting stakeholders' requirements. However, involving multiple stakeholders with diverse backgrounds and objectives often leads to conflicts among these requirements. These conflicts represent inconsistencies in the system design, resulting in various challenges, including project delays, increased costs, and potential system failures. Previous research has primarily focused on identifying conflicts with algorithms or negotiation, while conversational AI's potential to detect conflicts in real-time has been neglected. This thesis study addresses the challenge of requirement conflicts by proposing a novel approach that leverages conversational AI in the form of a chatbot. The chatbot, developed using the Rasa platform, enables real-time detection of conflicts, focusing on three general types: duplicated (similar), incompatible, and contradictory requirements. During the study, the design science research method is employed to guide the chatbot's development. Further, an experiment is applied to evaluate the chatbot's performance compared with domain experts using four different datasets. The experiment results are presented using F1 scores, which calculate precision and recall for both the chatbot and the experts on each dataset. Overall, the chatbot scored 0.8, while the experts achieved a slightly higher score of 0.86. To determine if there was a statistically significant difference between the two performances, a Wilcoxon signed-rank test was conducted on the results. The analysis showed no significant difference in the F1 score between the chatbot and the experts, indicating the chatbot's feasibility and effectiveness in detecting conflicts. The contribution of this thesis study can advance requirements engineering by providing a user-friendly and efficient method for real-time conflict detection, enhancing the quality and overall success of software development projects.

This thesis was conducted by two students as part of their Strategic Information Systems Management degree program at Stockholm University. As presented in this study, the manual elicitation processes in Requirements Engineering are error-prone and time-consuming. Traditional approaches and techniques often produce requirements that are characterized by ambiguity, inadequacy, incompleteness, inconsistency, and obsolescence. The research problem is focused on the lack of clear understanding regarding AI's specific role in supporting the identification of precise and detailed requirements, and the need for summarizing findings of related work. The goal of this thesis is to investigate the impact of AI in Requirements Engineering, focusing primarily on Requirements Elicitation and Analysis. After presenting essential background knowledge of Requirements Engineering, traditional elicitation methods, and Artificial Intelligence, a systematic literature review was performed to unveil Artificial Intelligence methods, techniques, and tools used in Requirements Elicitation and Analysis. With the assistance of the PRISMA methodology, the key findings and results were summarized and presented. The majority of the online literature focused on various issues connected with traditional methods and presented how Artificial Intelligence Chatbots, Text Mining and Natural Language Processing techniques, Virtual Reality, Sentiment Analysis, Crowdsourcing, Deep Learning Techniques, Gamification, and Bayesian Networks are improving the quality and speed of Requirements Elicitation. One of the main challenges faced is that there is no extensive comparison with traditional methods and metrics on how Artificial Intelligence overall helps Requirements Elicitation – only metrics per case. Also, there is not explicit definition regarding which AI methodologies and tools are appropriate for each elicitation and analysis method.

Denna rapport avser att undersöka för- och nackdelar med att utveckla ett för ändamålet specialanpassat system eller utnyttja de standardsystem, som i det aktuella fallet tryckerikoncernen JMS redan äger och använder. Genom en mer noggrann definiering av ickefunktionella krav på bland annat användbarhet har en specialanpassad prototyp framställts. I projektet användes metoder för kravinsamling som ledde till en kravspecifikation och i sin tur slutade med en färdig prototyp. Prototypen jämfördes med två standardsystem genom användartester och intervjuer. Prototypen visade sig leva upp till de krav som upptäcktes. Majoriteten av testpersonerna föredrog ett enklare avskalat system, vilket prototypen upplevdes som, före system med mycket information och funktioner. Med tanke på kostnaden rekommenderas dock JMS att försöka strukturera upp ett av de i företaget befintliga systemen och använda detta istället för att utveckla och implementera ytterligare ett nytt system i företaget. / This report intends to explore the pros and cons of developing a customized system or use the standard system, which in this case printing JMS Group already owns and uses. With a more accurate definition of non-functional requirements such as usability, has a custom-made prototype been built. The project used methods of requirements gathering that led to a specification and ended with a finished prototype. The prototype was compared with two standard systems through user testing and interviews. The prototype proved to live up to the requirements discovered. The majority of test subjects preferred a simpler clean system, which the prototype was, to systems with a lot of information and functions. Given the cost JMS was recommended to structure one of the systems that they already owns and uses instead of developing and implementing a new system further in the company.

A lot of research is done in requirements engineering and testing but often the extensive literature is missing on defining good methods for linking functional requirements with test cases. Most of the delays occurring in the software development projects are because of incomplete or inaccurate functional requirements. The two main goals of our project are to achieve a successful software project by First, to design a template, which will merge functional requirements with test cases and second is to find the benefits of the aligning requirements to test cases. Changing, updating and tracing the requirements during the development of the project is not an easy task. The main reason for project failure is due to possibility of not fulfilling specified project requirements, so one way to solve this problem is to merge functional requirements with test cases. Thus removes the need of creating a separate requirements document, which will improve the traceability process between requirements and testing, thus leads to high quality and efficient development. The template helps us to drive a successful project by identifying the issues at an earlier stage of the development cycle.

A key factor in creating software of good quality is that the requirements for the project being developed are as unambiguous and clear as possible, so the developers will be able to develop the product quickly and effectively. So, there is a need for tools that help requirements engineers create quality requirements. The attributes that define a poorly written requirement are called bad smells. In this thesis we investigate the NALABS tools bad smell detecting capabilities when analyzing industrial requirements. First, we performed a literature study to investigate what types of bad smells exist for requirements and how they were specified. After that we used a case study to examine how many smells and of what categories the NALABS tool detects, when it analyzes industrial requirements. Lastly, we used a small experiment to examine how accurately NALABS detects smells, by designing a simple console application that counted instances of bad smell words in a set of keywords that were from the NALABS tool. The results we gathered gave us an indication that NALABS detects bad smells in all the categories of bad smells that are implemented in it, to a varying degree. Through this thesis we hope to extend the knowledge about bad requirements smells, clarify what attributes of a requirement might be a bad smell, and investigate to what degree the NALABS tool can detect bad smells in industrial requirements.

For many software projects, keeping requirements on track needs an effective and efficient path from data to decision. Visual analytics creates such a path that enables the human to extract insights by interacting with the relevant information. While various requirements visualization techniques exist, few have produced end-to-end values to practitioners. In this dissertation, we advance the literature on visual requirements analytics by characterizing its key components and relationships in a framework. We follow the goal-question-metric paradigm to define the framework by teasing out five conceptual goals (user, data, model, visualization, and knowledge), their specific operationalizations, and their interconnections. The framework allows us to not only assess existing approaches, but also create tool enhancements in a principled manner. We evaluate our enhanced tool supports both qualitatively and quantitatively. First, we evaluate our tool supports qualitatively through a case study where massive, heterogeneous, and dynamic requirements are processed, visualized, and analyzed. Working together with practitioners on a contemporary software project within its real-life context leads to the main ending that visual analytics can help tackle both open-ended visual exploration tasks and well-structured visual exploitation tasks in requirements engineering. In addition, the study helps the practitioners to reach actionable decisions in a wide range of areas relating to their project, ranging from theme and outlier identification, over requirements tracing, to risk assessment. Overall our work illuminates how the data-to-decision analytical capabilities could be improved by the increased interactivity of requirements visualization. Although many new visual analytics tools, techniques and methods are being developed, still there is a lack of understanding of how to evaluate the performance of such tools. We conducted an experiment to assess the performance (time and correctness) of our visual analytics tool support in solving requirements engineering tasks. Our study provides initial evidence and insights for visual analytics in requirements engineering and sheds light on many challenging open questions.