Context. Internet of Things (IoT) is a new trending phase of technology. IoT refers to communication and connectivity between things such as technological devices, actuators, sensors, and people or processes with unique identifiers. The importance of IoT is to improve the daily living standards of an average user. IoT is made for the people and used by the people for many reasons such as improved health, business innovations, and personal health trackers. Examples of IoT applications and services today include  Smart thermostats like NEST, connected cars like Car2Go, activity trackers like BASIS, smart outlets like Belkin, Parking sensors like streetline and so much more services being developed. Objectives. The main goal of this study is to identify the challenges users face in understanding IoT and monitoring it as it undergoes change through self-adaptation. Once the challenges have been known then the gap between system requirements and user requirements can be bridged. The study also states the different ways the developers can improve the IoT services and applications for the users through user feedback. Methods. In this paper, an observational study is conducted. Within the study, two data collection methods were used; observational of the users and post observation questionnaires. The observational study was done by video recording users while using the IoT application. This was to obtain information about the IoT. The post observational questionnaires were to obtain information about the users’ judgement of their IoT experience. The IoT application used in this study is a Smart Home Starter Kit. The users are to secure a room with the Smart Home Starter kit. Later on, the users are presented with a post observational questionnaire to further elaborate on their experience in case the researcher missed something while recording. The study was performed with 5 users. The users were found through convenience sampling at the Karlskrona central train station and the Hogsland Park. They were then asked, if they were willing to take part in the study. This number of users was enough to reach saturation needed for the research. The author used a deductive approach together with conventional content analysis method to analyze the data and its quality. Results. The research questions of the study focused mainly on learning, maintaining awareness and re-process of the IoT. Re-process of the IoT refers to implementing the IoT with the new information received from user feedback. This enables the IoT to become more user compatible and friendly. When the results of the study were mapped to the research questions, the author deduced that learnability requirements were lacking. The users suggested simpler step by step guidelines would have made their experience with IoT much better. Thus the IoT developers would implement the user feedback through simple online tutorials, an online technician that could guide the users through the IoT application. Conclusions. In comparison to related work, the author concluded that there is still a big knowledge gap between the system requirements and the user requirements of the IoT. Many related papers are more focused on what IoT applications to develop and design than the users of the IoT applications. That is where this paper comes in, to bridge the gap. Without focus on users and their needs, then complex IoT systems will fail to accomplish their goal. The users suggested simple step by step approach on how to use the IoT due to the learnability problem that is faced by the majority of them. The product developers can make simpler and more user friendly IoT applications with these results. In the future, User requirements could further get categorized according to the different types of IoT and users. This would make it simpler for the researcher as the scope is narrowed down and at the same time for the IoT developers, as they know what to implement in the IoT applications.

This thesis addresses the integration of software agent technology, simulation and mathematical optimization within the domain of production and transportation. It has been argued that agentbased approaches and mathematical optimization can complement each other in the studied domain. These technologies have often been used separately, but the existing amount of literature concerning how to combine them is rather limited, especially in the domain of production and transportation. This domain is considered complex since; for instance, the decision making is characterized by many decision makers that are influencing each other. Also, problems in the domain are typically large and combinatorial. The transportation of goods has both positive and negative effects on society. A positive effect is the possibility for people to consume products that have been produced at distant locations. Examples of negative effects are: emissions, congestion, accidents, and large costs for infrastructure investments. Increasing competition, experienced by manufacturers and haulers, acts as a motivation for improving the utilization of often limited and expensive production and transportation resources. It is important to maximize the positive effects of transportation while the negative effects are minimized. We present a rather general agent-based simulator (TAPAS) for simulation of production and transportation. By using agent technology, we have been able to simulate the decision making and interaction between decision makers, which is difficult using traditional simulation techniques. We provide a technical description of how TAPAS was modeled, and examples of how it can be used. An optimization model for a real world ``Integrated Production, Inventory, and Distribution Routing Problem’’ (IPIDRP) has been developed. The identified IPIDRP is in the domain of production and transportation problems. For solving and analyzing the problem, we developed a solution method based on the principles of Dantzig- Wolfe decomposition, which was implemented as a multi-agent system inside TAPAS. The purpose is to improve resource utilization and to analyze the potential effects of introducing VMI (Vendor Managed Inventory). Experiments are performed for quantifying the benefits of VMI and for estimating the effects of an agentification of the decomposition approach. Some advantages and disadvantages of an agentification are discussed in this thesis. The work indicates high potentials for integrating agent technology and mathematical optimization. One direction for future work is to use TAPAS as a tool for evaluating the results that are produced by the optimization algorithm. For real world systems, evaluation of optimization results can be expensive and difficult to carry out, and we believe that simulation can be useful for evaluation purposes.

In software companies today we see a trend of changing development processes, as well as test processes, in order to reduce the number of faults in their software; and by reducing the number of faults, reducing the number of failures. It is hard to know if a change to a process has a positive or negative effect on the faults and failures of the software. Measuring the total number of faults and failures is a way of telling if the process has been changed for better or worse. The problem with measuring all faults in a software project is that it takes a lot of reviewing and testing. To know how many failures can be provoked from the software, the software needs to be run for a long time after release. In both these instances the information on the total number of faults or failures of the software is simply available too late. The use of fault and failure prediction and estimation methods allows project members and managers to get information about the total number of faults and failures of the software. The predictions and estimations can be repeated at different points during a development project. The contribution of the thesis consists of models and methods for fault and failure prediction and estimation. In this thesis three new methods of easy, early and cost-efficient fault and failure prediction and estimation are presented. The methods are created to take in new information as it becomes available, and are not meant for point estimates or predictions, but to continuously follow-up the estimates and predictions. The three methods presented are a first step towards the creation of a framework for fault and failure estimation and prediction. The framework consists of estimation and prediction models used at different points throughout a project. The goal of the framework is to be able to follow, and continuously improve the estimates and predictions of faults and failures in software projects.

The main focus of the research presented in this thesis is a usability evaluation framework for mass market mobile devices, allowing measurement, comparison and presentation of the usability of hand held devices. The research has been a cooperation between an academic and an industrial partner, based on an action research approach, following the processes of Cooperative Method Development (CMD). It has used a case study approach, where the data has been analysed using techniques taken from grounded theory. Ethnography and participatory design have been central to both the research and the cooperation. With its basis in the evaluation framework, and its use of quantitative measurements and qualitative judgments framed by a focus on usability testing, this thesis contributes to aspects related to capturing real world usage in a continuously changing society, and supporting information needs in the process of building software. The evaluation framework can be used as a quality assurance tool in a wide perspective. It measures usability and the user experience, quickly and flexibly, and in so doing measures aspects of quality in use. It has been tested in a complex industrial development project and is a valuable and flexible tool that is easy for a usability expert to learn and use, to measure and help build quality on the customer’s terms. The results we have arrived at are of practical and theoretical interest within software engineering and the industrial telecom sphere. Several features and aspects of the evaluation framework are new and challenging. These are: its mix of qualitative and quantitative methods, allowing it to target many different stakeholders; experience in applying these methods in the technology-focused and rapidly changing mobile phone area; the challenge of addressing end users in a mass market; the challenge of finding presentation models for the many different stakeholders; the challenge of making sure the framework can be used in different stages in the industrial software development process. The framework is related to three areas of software engineering, Market Driven Requirements Engineering, Statistical Usage Testing, and Organisation and Product Together. Our work includes a discussion of the need for agility, which has not so far been focused upon and discussed within the area of software engineering and usability. The combination of factors included in the framework means that is unique in solving a number of the problems that are found in these different areas within software engineering, especially in a rapidly changing marketplace. We also contribute to the field, through the qualitative element of the evaluation framework, which is inspired by ethnography and participatory design. It thereby makes a contribution that can improve practice in the field of software engineering, and that contributes to the theoretical work that is being performed within these different research areas.

The sustainable development of a software product depends on a number of groups working together to achieve a common goal. However, each of the groups interacts with the product in different ways, and can have conflicting aims and objectives. For example, developers trying to correct issues in the software architecture, which will impact future releases of the product, can be stopped by a project manager who is charged with delivering a release on time and within budget. While the functional requirements of a software product are usually documented, there are a number of other investments in software development that are not always as explicitly agreed upon but are still essential to a product's long-term success. The major investment types include software product quality -- a main control variable in software development, and intellectual capital (IC) -- being the key input and tool used in software development. As management requires measurement, it is necessary understand the priorities placed on investment options by the various groups involved in the development of a software product. The objective of this thesis is to develop a method capable of both determining the priorities of different groups, and the level of alignment between these groups in terms of their priorities. Evolving the method from a study into the values used to select requirements for a release of software, Ericsson supported the development of a methodology to determine and compare the priorities of different groups for software product quality, and IC. The method elicited the required information from a series of case studies to build up a picture of the priorities placed on major investment options and constraints -- features, quality, IC, time and cost. The results highlight strengths, and areas for improvement -- through the identification of differing priorities and ambiguities in management of different aspects studied. In conducting this research, systematic biases in the selection of requirements appear to be occurring, adding an objective to understand how bias impacts decision making in a requirements engineering context. This thesis provides a method that determines the priorities on the level of investment on different options in the development of software products. It is concluded that people involved in the development of software need to be aligned on issues of software product quality as these priorities set expectations. The same was not found true for issues of IC, where groups can complete tasks without negatively impacting others, as long as the organisation works effectively as a single entity. On the issue of biases in the prioritisation of these aspects, prospect theory is found to apply to requirements selection in an academic experiment -- suggesting people will prefer functionality over software product quality, and to meet the known requirements of customers over predicting general market requirements.

Context: At the core of choosing what features and level of quality to realize, and thus offer a market or customer, rests on the ability to take decisions. Decision-making is complicated by heterogeneous understanding of issues such as priority, implication of realization, and interpretations of strategy as pertaining to the short- and long-term development of software intensive systems. The complexity is further compounded by the amount of decision support material that has to be taken into account and the sheer volume of possible alternatives that have to be triaged and prioritized, thousands, or even tens of thousands of requirements can be the reality facing industry. There is a need to develop the functionality that is strategically most important while satisfying customers and being competitive, cost efficient, and minimizing risk. In order to achieve a balance between these factors, it is important that within an organization, all stakeholders agree on the strategic aspects to be considered and their corresponding relative importance. Objective: The objective of this thesis is to provide strategic decision-making support for product management of software intensive products. Method: A number of empirical studies, set in both academia and industry have been performed. The research methods used span from systematic reviews, case studies to experiments, all aligned to identify possibilities for improvement, devise solutions, and validate these solutions in several steps. Result: The methods presented in this thesis can be used to evaluate strategic alignment and identify possible root causes for misalignments. To strengthen strategic alignment, the methods and results in the thesis can be used by product managers for making effective and efficient strategic decisions regarding portfolios and products, following a systematic and aligned process. Conclusions: The area of product management in the context of market-driven software intensive product development is a field with unique challenges. The specifics of the solutions are based on industry case studies performed to gauge state of the art as well as map the main challenges. The decision-making support developed takes the form of models and methods that support software product management in strategic alignment, requirements triage and portfolio level decisions.

Context: Requirements engineering (RE) for software products offered to a mass market is concerned with deciding which of the diverse and large amounts of potential requirements to implement into future releases of a product. While being the key for achieving success, these decisions are very complex. Therefore, the need for decision support is well acknowledged. However, despite a growing body of research in this area, software companies are still experiencing problems in making informed decisions on which requirements to include in the software, or knowing how to maximize the potential ROI of a software release. Objective: The purpose of this thesis is to provide an increased understanding of how better decisions regarding the content of software products can be achieved. The research addresses two currently unresolved areas: balancing investments in different requirement types (commercial requirements, internal quality aspects and innovations) and identifying reasonable requirement analysis effort for informed requirements selection decisions. In order to address these areas the thesis focuses on investigating: 1) how uncertainty in the value proposition of a requirement is influencing the balance between investments in different requirement types; and 2) challenges and opportunities introduced by agile practices to RE decisions. Method: The presented research has an exploratory character and consists of empirical studies conducted both in industrial and academic settings. Results: The results include findings from an academic experiment and an industrial case study indicating that commercial requirements will be preferred over innovations and internal quality aspects. This is because innovations and internal quality aspects are associated with higher uncertainty in their value offering compared to commercial requirements and thereby are perceived to have higher level of business risk. The thesis also offers findings from an industrial case study, showing a misalignment between agile principles and the ability to take informed release planning decisions. Further, a framework (NORM) for finding an appropriate balance between information needs of RE decisions and requirements analysis effort is suggested. Conclusions: Uncertainty associated with the value proposition of different requirement types influences the requirements selection decisions, resulting in a dominance of commercial requirements. Thus, in order to achieve a better balance between investments in commercial requirements, internal quality and innovation it is important that uncertainty in the value offering of requirements is explicitly managed by methods providing support for RE decisions in a market-driven context. Agile methods provide opportunities to minimize overhead caused by excessive analysis of requirements, however adopting agile approaches in their current form pose challenges for performing product management and taking informed RE decisions in a market-driven context. Therefore, a balance between agility and information needs of RE decisions must be found. In combination, the thesis results offer a new insight and form a ground for defining improved approaches for supporting requirement selection decisions.

Context: Distributed teams characterize Global Software Engineering (GSE). GSE stakeholders are from different cultures, geographic places and potentially time zones. These conditions have significant consequences on communication, coordination and control of software projects. Given these constraints, distributed teams need to highly rely on each other. Trust is the glue that holds them together and enables more open communication, which increases their performance and quality of delivered products. Simultaneously, in striving for more efficient software development approaches, Agile values and principles were formulated. Agile methods encourage establishing close collaboration between customers and developers, continuous requirements gathering and frequent face-to-face communications. Objective: The major objective of the research is to study efficient software development approaches particularly in (globally) distributed settings. Thus, the dynamics of trust in GSE are investigated for bringing useful trust improvement suggestions to project managers. Furthermore, Agile practices that have been efficiently applied in GSE are identified through two different systematic literature review approaches (i.e. systematic literature review and backward snowballing). The differences identified in the use of Agile practices lead to a need to better understand and assess Agility. Method: The research methods, include systematic literature reviews and case studies, are applied in different empirical cases. Then, a variety of secondary data collection methods are utilized such as semi-structured interviews, questionnaires, open discussions and presentations. Result: Achieving trust was realized to be crucial and the success factor for trust was the “awareness” of particular GSE challenges, which shall be communicated properly to all distributed team members and proper actions shall be taken to address them. Besides, the literature indicated several successful combinations of Agile and GSE. However, despite utilizing two different literature search methods the identified patterns were similar. The most common practices were “standup meetings” and “sprints/iterations”. Nevertheless, the current literature reports “Agile” as a general term and “distributed team” as the most common team/organization setting, which motivated examining the applicability of existing Agile assessment tools in an industrial setting. We found one of the studied tools sufficiently applicable in the context of the case organization. Conclusions: Trust achievement is crucial for efficient GSE collaborations regardless of the applied software development approach. Although Agile promotes trust among team members, it was formulated without considering teams’ distribution. Hence, combining Agile and GSE is challenging. The literature contains several successful cases of implementing Agile in GSE while practitioners and researchers are not yet consistent regarding their perception of Agile practices and documenting them. Therefore, they need to collaborate closely, illustrate the practices, agree on the terminology, how to document the context, and how to profile/assess Agility. For this purpose, we examined the applicability of a set of Agile assessment tools and proposed one tool for the case organization.

Background: Computer users often need to distinguish between good and bad instances of software and e-mail messages without the aid of experts. This decision process is further complicated as the perception of spam and spyware varies between individuals. As a consequence, users can benefit from using a decision support system to make informed decisions concerning whether an instance is good or bad. Objective: This thesis investigates approaches for estimating the utility of e-mail and software. These approaches can be used in a personalized decision support system. The research investigates the performance and accuracy of the approaches. Method: The scope of the research is limited to the legal grey- zone of software and e-mail messages. Experimental data have been collected from academia and industry. The research methods used in this thesis are simulation and experimentation. The processing of user input, along with malicious user input, in a reputation system for software were investigated using simulations. The preprocessing optimization of end user license agreement classification was investigated using experimentation. The impact of social interaction data in regards to personalized e-mail classification was also investigated using experimentation. Results: Three approaches were investigated that could be adapted for a decision support system. The results of the investigated reputation system suggested that the system is capable, on average, of producing a rating ±1 from an objects correct rating. The results of the preprocessing optimization of end user license agreement classification suggested negligible impact. The results of using social interaction information in e-mail classification suggested that accurate spam detectors can be generated from the low-dimensional social data model alone, however, spam detectors generated from combinations of the traditional and social models were more accurate. Conclusions: The results of the presented approaches suggestthat it is possible to provide decision support for detecting software that might be of low utility to users. The labeling of instances of software and e-mail messages that are in a legal grey-zone can assist users in avoiding an instance of low utility, e.g. spam and spyware. A limitation in the approaches is that isolated implementations will yield unsatisfactory results in a real world setting. A combination of the approaches, e.g. to determine the utility of software, could yield improved results.

Context: The existing body of knowledge falls short of providing comprehensive empirical evidence on the impact that global software development (GSD) strategies have on software quality during software evolution. The realization of expected benefits of such GSD strategies, e.g. reduced costs, should not be taken for granted. Challenges faced can negatively impact quality, which can consequently inhibit the realization of the potential benefits. Objective: This licentiate thesis provides empirical evidence pertaining to the effect on quality for evolving systems in distributed development environments. The aim is to provide empirical evidence that can be useful input in the decision-making process for future GSD projects that are executed in distributed development environments. Method: The findings presented in this licentiate thesis are obtained from three empirical studies and one extensive systematic literature review. The empirical studies were conducted at two large multinational corporations. Meanwhile, the purpose of the systematic review was to obtain empirical information that was used to successfully execute one of the empirical studies. All empirical work was done using both quantitative data (e.g., defect data, features per release, source code measures, release history) and qualitative data (e.g., interviews, focus group meetings, questionnaires, and analysis of company documentations). Result: Transfers have a potentially negative impact on quality and efficiency. Observations that were made on quantitative data in all three empirical studies were triangulated with subjective opinions that were obtained from practitioners. When studying the quality of a large software system, a significant decrease in quality was identified; similarly in a study focusing on maintenance work efficiency two studied large software products showed a noticeable decrease. Meanwhile, there was no discernible impact on quality for two products, as a result of distributed development and the handover of responsibilities between involved sites. Transfer critical factors, which can impact quality, as well as transfer enabling factors, which can alleviate transfer-related issues, were also identified from these empirical studies. Conclusions: Companies that engage in software transfers should expect a decline in quality during and immediately after a transfer. There are practices, such as, engaging in distributed development, and the gradual handover of responsibilities, that can alleviate transfer-related issues. The findings in this licentiate thesis can be a valuable input in the decision-making process for companies engaging in transfers in GSD contexts, and thus help in making informed decisions in current or future transfers. Moreover, this licentiate thesis shows that analyzing the evolution of size and complexity properties of a product’s source code, and defect data, can also provide useful objective data to support decision-making during similar projects.