Many test prioritisation techniques have been proposed in order to improve test effectiveness of Continuous Integration (CI) pipelines. Particularly, diversity-based testing (DBT) has shown promising and competitive results to improve test effectiveness. However, the technical and practical challenges of introducing test prioritisation in CI pipelines are rarely discussed, thus hindering the applicability and adoption of those proposed techniques. This research builds on our prior work in which we evaluated diversity-based techniques in an industrial setting. This work investigates the factors that influence the adoption of DBT both in connection to improvements in test cost-effectiveness, as well as the process and human related challenges to transfer and use DBT prioritisation in CI pipelines. We report on a case study considering the CI pipeline of Axis Communications in Sweden. We performed a thematic analysis of a focus group interview with senior practitioners at the company to identify the challenges and perceived benefits of using test prioritisation in their test process. Our thematic analysis reveals a list of ten challenges and seven perceived effects of introducing test prioritisation in CI cycles. For instance, our participants emphasized the importance of introducing comprehensible and transparent techniques that instill trust in its users. Moreover, practitioners prefer techniques compatible with their current test infrastructure (e.g., test framework and environments) in order to reduce instrumentation efforts and avoid disrupting their current setup. In conclusion, we have identified tradeoffs between different test prioritisation techniques pertaining to the technical, process and human aspects of regression testing in CI. We summarize those findings in a list of seven advantages that refer to specific stakeholder interests and describe the effects of adopting DBT in CI pipelines.

Continuous integration and delivery consolidate several activities, ranging from frequent code changes to compiling, building, testing, and deployment to customers. During these activities, software professionals seek additional information to perform the task at hand. Developers that spend a considerable amount of time and effort to identify such information can be distracted from doing productive work. By identifying the types of information that software professionals seek, we can better understand the processes, practices, and tools that are required to develop a quality product on time. A better understanding of the information needs of software practitioners has several benefits, such as staying competitive, increasing awareness of the issues that can hinder a timely release, and building a visualization tool that can help practitioners to address their information needs. We conducted a multiple-case holistic study with 5 different companies (34 unique participants) to identify information needs in continuous integration and delivery. This study attempts to capture the importance, frequency, required effort (e.g., sequence of actions required to collect information), current approach to handling, and associated stakeholders with respect to identified needs. We identified 27 information needs associated with different stakeholders (i.e., developers, testers, project managers, release team, and compliance authority). The identified needs were categorized as testing, code & commit, confidence, bug, and artifacts. We discussed whether the information needs were aligned with the tools used to address them.

Purpose: The information technology (IT) sector has been seen as central to society's transformation to a more just and sustainable society, which underlines teachers’ responsibility to foster engineers who can contribute specifically to such ends. This study aims to report an effort to significantly update an existing engineering programme in IT with this ambition and to analyse the effects and challenges associated with the transformation.

Design/methodology/approach: This study is based on a combination of action-oriented research based on implementing key changes to the curriculum; empirical investigations including surveys and interviews with students and teachers, and analysis of these; and a science and technology studies-inspired analysis.

Findings: Respondents were generally positive towards adding topics relating to sustainability. However, in the unmaking of traditional engineering subjects, changes created a conflict between core versus soft subjects in which the core subjects tended to gain the upper hand. This conflict can be turned into productive discussions by focusing on what kinds of engineers the authors’ educate and how students can be introduced to societal problems as an integrated part of their education.

Practical implications: This study can be helpful for educators in the engineering domain to support them in their efforts to transition from a (narrow) focus on traditional disciplines to one where the bettering of society is at the core.

Originality/value: This study provides a novel approach to the transformation of engineering education through a theoretical analysis seldom used in studies of higher education on a novel case study.

 Denna rapport beskriver en studie vars syfte har varit att undersöka vilka utmaningar och möjligheter som finns med att på ett systematiskt sätt arbeta för att främja ett lärande för hållbar utveckling vid LiU. Vår utgångspunkt har varit universitetskanslerämbetets tematiska utvärdering från 2017 av lärosätenas arbete med att främja en hållbar utveckling genom sina utbildningar. Vi har genomfört en studie med programansvariga vid utbildningar som ges vid institutionen för ekonomisk och industriell utveckling, IEI varav en del på filosofisk och andra på teknisk fakultet. Dels har vi gått igenom utbildningsplanerna för programmen, dels har vi genomfört en enkätundersökning och en uppsättning fokusgruppsdiskussioner med programansvariga.

Ett mindre antal av programmen och specifikt civilingenjörsutbildningen i Energi, Miljö & Management (EMM) har i utbildningsplaner referenser till specifika mål för en hållbar utveckling som man avser förbereda sina studenter att kunna bidra till. De flesta programs primära fokus ligger dock på anställningsbarhet för sina studenter. Från enkäten och fokusgruppsdiskussioner har vi förstått att det för många programansvariga har varit det första tillfället de fått att fundera över hur deras utbildningar eventuellt bidrar till att förbereda studenter för att hantera utmaningar kopplade till en hållbar utveckling. I våra resultat märks också en tydlig ambivalens och tveksamhet inför både vad man gör just nu, vad man vill göra och vilken sorts drivkrafter och styrning man önskar i det arbetet. Flera programansvariga hävdar å ena sidan att begreppet är svårdefinierat, men att man å andra sidan är säker på att man arbetar i en riktning som gör att utbildningarna bidrar till att främja en hållbar utveckling. Man hävdar att en del lärare vid de egna programmen kan sakna kompetens att hantera problem med flera dimensioner, men anser samtidigt att de egna lärarna har den kompetens som behövs för utbildnings-programmen. Man ser positivt på studenters och externa finansiärers önskemål om förändringar av utbildningarna, men är samtidigt tveksam till många av de sätt som LiU skulle kunna använda för att stödja arbetet med för-ändringar.

Baserat på vår analys av programansvarigas respons och universitetskanslersämbetets rekommendationer ger vi avslutningsvis rekommendationer för fortsatt arbete med frågan om lärande för hållbar utveckling på LiU.

High-fidelity simulations of pandemic outbreaks are resource consuming. Cluster-based solutions have been suggested for executing such complex computations. We present a cloud-based simulation architecture that utilizes computing resources both locally available and dynamically rented online. The approach uses the Condor framework for job distribution and management of the Amazon Elastic Computing Cloud (EC2) as well as local resources. The architecture has a web-based user interface that allows users to monitor and control simulation execution. In a benchmark test, the best costadjusted performance was recorded for the EC2 H-CPU Medium instance, while a field trial showed that the job configuration had significant influence on the execution time and that the network capacity of the master node could become a bottleneck. We conclude that it is possible to develop a scalable simulation environment that uses cloud-based solutions, while providing an easy-to-use graphical user interface.

This paper examines the affordances of a component in a seri-ous game, specifically how one material design choice affectedthe interactions and opportunities for agency and learning. Thegame examined is a megagame, a large-scale (20-100 participants)social learning environment combining board-gaming with role-playing. The megagame poses participants the challenge of creatinga sustainable society, and focuses on developing participants’ un-derstanding of how different stakeholders in a regional energysystem and society are interconnected. Negotiation over conflictinggoals was a primary activity in the game, and agreements wereformalized through paper contracts. Contracts were designed toact as boundary objects between player teams, and defined theirfinancial exchanges. This exploratory study finds evidence in theinteractions between participants that the paper contract systemfacilitated opportunities for participants to develop understandingabout the interdependencies between teams and resources, andto exert agency over their role in these relations. Players activelymaintained and prioritized the correspondence between copies ofcontracts as a means of regulating both the game’s economic sys-tem in the game and their mutual intersubjectivity. Overall, thestudy highlights the importance enabling participants to experiencehow joint actions cumulatively produce future consequences, andhow opportunities for agency and negotiation educate about theongoing global polycrises of energy, climate and social tension.

Climate change is tightly coupled to the usage of energy in differentforms. Creating and using sustainable energy solutions is increasinglybeing recognized as the greatest challenge of our time. Theenergy crisis concerns everyone who consumes energy or servicesthat rely on energy to be performed, in practice almost everythingwe buy. However, the temporal and psychological distance to climatechange has led to a situation where the consequences of ourenergy usage often is considered a future problem or “someoneelse’s” problem. Current methods to increase awareness and understandingof climate change and the need to create sustainableenergy solutions are usually based on simulation or negotiationgames. Methods similar to crisis management exercises are uncommon.In this paper, we propose to use Megagames, large scale socialgames, as a method for increasing the awareness of the challengesrelated to creating sustainable energy solutions. Examples fromtwo Megagame test runs are provided and discussed.

Researchers in military command and control (C2) have for several decades sought to help commanders by introducing automated, intelligent decision support systems. These systems are still not widely used, however, and some researchers argue that this may be due to those problems that are inherent in the relationship between the affordances of technology and the requirements by the specific contexts of work in military C². In this thesis, we study some specific properties of three support techniques for analyzing and automating aspects of C² scenarios that are relevant for the contexts of work in which they can be used.

The research questions we address concern (1) which affordances and constraints of these technologies are of most relevance to C², and (2) how these affordances and limitations can be managed to improve the utility of intelligent decision support systems in C². The thesis comprises three case studies of C² scenarios where intelligent support systems have been devised for each scenario.

The first study considered two military planning scenarios: planning for medical evacuations and similar tactical operations. In the study, we argue that the plan production capabilities of automated planners may be of less use than their constraint management facilities. ComPlan, which was the main technical system studied in the first case study, consisted of a highly configurable, collaborative, constraint-management framework for planning in which constraints could be used either to enforce relationships or notify users of their validity during planning. As a partial result of the first study, we proposed three tentative design criteria for intelligent decision support: transparency, graceful regulation and event-based feedback.

The second study was of information management during planning at the operational level, where we used a C² training scenario from the Swedish Armed Forces and the documents produced during the scenario as a basis for studying properties of Semantic Desktops as intelligent decision support. In the study, we argue that (1) due to the simultaneous use of both documents and specialized systems, it is imperative that commanders can manage information from heterogeneous sources consistently, and (2) in the context of a structurally rich domain such as C², documents can contain enough information about domain-specific concepts that occur in several applications to allow them to be automatically extracted from documents and managed in a unified manner. As a result of our second study, we present a model for extending a general semantic desktop ontology with domain-specific concepts and mechanisms for extracting and managing semantic objects from plan documents. Our model adheres to the design criteria from the first case study.

The third study investigated machine learning techniques in general and text clustering in particular, to support researchers who study team behavior and performance in C². In this study, we used material from several C² scenarios which had been studied previously. We interviewed the participating researchers about their work profiles, evaluated machine learning approaches for the purpose of supporting their work and devised a support system based on the results of our evaluations. In the study, we report on empirical results regarding the precision possible to achieve when automatically classifying messages in C² workflows and present some ramifications of these results on the design of support tools for communication analysis. Finally, we report how the prototype support system for clustering messages in C² communications was conceived by the users, the utility of the design criteria from case study 1 when applied to communication analysis, and the possibilities for using text clustering as a concrete support tool in communication analysis.

In conclusion, we discuss how the affordances and constraints of intelligent decision support systems for C² relate to our design criteria, and how the characteristics of each work situation demand new adaptations of the way in which intelligent support systems are used.

ComPlan (A Combined, Collaborative Command and Control Planning tool) is an approach to providing knowledge-based decision support in the context of command and control. It combines technical research on automated planning tools with human-centered research on mission planning. At its core, ComPlan uses interconnected views of a planning situation to present and manipulate aspects of a scenario. By using domain knowledge flexibly, it presents immediate and directly visible feedback on constraint violations of a plan, facilitates mental simulation of events, and provides support for synchronization of concurrently working mission planners. The conceptual framework of ComPlan is grounded on three main principles from human-centered research on command and control: transparency, graceful regulation, and event-based feedback. As a result, ComPlan provides a model for applying a human-centered perspective on plan authoring tools for command and control, and a demonstration for how to apply that model in an integrated plan-authoring environment.

This thesis describes two approaches for using critiquing as decision support for military mission planning. In our work, we have drawn from both human-centered research as well as results on decision support systems research for military mission planning when devising approaches for knowledge acquisition and decision support for mission planning.

Our two approaches build on a common set of requirements which have been developed as the consequence of both literature analyses as well as interview studies. In short, these criteria state that critiquing systems should be developed with transparency, ease of use and integration in traditional work flow in mind. The use of these criteria is illustrated in two approaches to decision support in two different settings: a collaborative real-time war-gaming simulation and a planning tool for training mission commanders.

Our first approach is demonstrated by the DKExpert system, in which end-users can create feedback mechanisms for their own needs when playing a two-sided war-game scenario in the DKE simulation environment. In DKExpert, users can choose to trigger feedback during the game by instructing a rule engine to recognize critical situations. Our second approach, ComPlan, builds on the insights on knowledge and planning representation gained from DKExpert and introduces an explicit representation of planning operations, thereby allowing for better analysis of planning operations and user-controlled feedback. ComPlan also demonstrates a design for critiquing support systems that respects the traditional work practice of mission planners while allowing for intelligent analysis of military plans. 

In the current thematic collection of Högre Utbildning, we present eight contributions on how to change higher education in ways which will enable students to contribute to a sustainable future, including three invited papers on the systematic transformation of higher education necessary to addressour existential societal challenges.

There is a significant gap between the services provided by dedicated information systems and general desktop systems for document communication and preparation. This situation is a serious knowledge-management problem, which often results in information loss, poor communication, and confusion among users. Semantic desktops promise to bring knowledge-based services to common desktop applications and, ultimately, to support knowledge management by adding advanced functionality to familiar computing environments. By custom tailoring these systems to different application domains, it is possible to provide dedicated services that assist users in combining document handling and communication with structured workflow processes and the services provided by dedicated systems. This paper presents a model for developing custom-tailored document processing for semantic-desktop systems. Our approach has been applied to the domain of military command and control, which as based on highly-structured document-driven processes. Key Words: semantic desktop, document-driven processes, semantic documents, planning

Our understanding of distributed decision making in professional teams and their performance comes in part from studies in which researchers gather and process information about the communications and actions of teams. In many cases, the data sets available for analysis are large, unwieldy and require methods for exploratory and dynamic management of data. In this paper, we report the results of interviewing eight researchers on their work process when conducting such analyses and their use of support tools in this process. Our aim with the study was to gain an understanding of their workflow when studying distributed decision making in teams, and specifically how automated pattern extraction tools could be of use in their work. Based on an analysis of the interviews, we elicited three issues of concern related to the use of support tools in analysis: focusing on a subset of data to study, drawing conclusionsfrom data and understanding tool limitations. Together, these three issues point to two observations regarding tool use that are of specific relevance to the design of intelligent support tools based on pattern extraction: open-endedness and transparency.

We present results from a study on constructing and evaluating a support tool for the extraction of patterns in distributed decision -making processes, based on design criteria elicited from a study on the work process involved in studying such decision-making. Specifically, we devised and evaluated an analysis tool for C² researchers who study simulated decision-making scenarios for command teams. The analysis tool used text clustering as an underlying pattern extraction technique and was evaluated together with C² researchers in a workshop to establish whether the design criteria were valid and the approach taken with the analysis tool was sound. Design criteria elicited from an earlier study with researchers (open-endedness and transparency) were highly consistent with the results from the workshop. Specifically, evaluation results indicate that successful deployment of advanced analysis tools requires that tools can treat multiple data sources and offer rich opportunities for manipulation and interaction (open-endedness) and careful design of visual presentations and explanations of the techniques used (transparency). Finally, the results point to the high relevance and promise of using text clustering as a support for analysis of C² data.

Semantic Desktops hold promise to provide intelligent information-management environments that can respond to users’ needs. A critical requirement for creating such environments is that the underlying ontology reflects the context of work properly. For specialized work domains where people deal with rich information sources in a context-specific manner, there may be a significant amount of domain-specific information available in text documents, emails and other domain-dependent data sources. We propose that this can be exploited to great effect in a Semantic Desktop to provide much more effective knowledge management. In this paper, we present extensions to an existing semantic desktop through content- and structure-based information extraction, domain-specific ontological extensions as well as visualization of semantic entities. Our extensions are justified by needs in strategic decision making, where domain-specific, well-structured knowledge is available in documents and communications but scattered across the desktop. The consistent and efficient use of these resources by a group of co-workers is critical to success. With a domain-aware semantic desktop, we argue that decision makers will have a much better chance of successful sense making in strategic decision making.

In military command and control, success relies on being able to perform key functions such as communicating intent. Most staff functions are carried out using standard means of text communication. Exactly how members of staff perform their duties, who they communicate with and how, and how they could perform better, is an area of active research. In command and control research, there is not yet a single model which explains all actions undertaken by members of staff well enough to prescribe a set of procedures for how to perform functions in command and control. In this context, we have studied whether automated classification approaches can be applied to textual communication to assist researchers who study command teams and analyze their actions. Specifically, we report the results from evaluating machine leaning with respect to two metrics of classification performance: (1) the precision of finding a known transition between two activities in a work process, and (2) the precision of classifying messages similarly to human researchers that search for critical episodes in a workflow. The results indicate that classification based on text only provides higher precision results with respect to both metrics when compared to other machine learning approaches, and that the precision of classifying messages using text-based classification in already classified datasets was approximately 50%. We present the implications that these results have for the design of support systems based on machine learning, and outline how to practically use text classification for analyzing team communications by demonstrating a specific prototype support tool for workflow analysis.

Emergency management in highly dynamic situations consists of exploring options to solve a planning problem. This task can be supported through the use of visual cues that are based on domain knowledge of the current domain. We present an approach to use visualization of critical constraints in timelines and hierarchical views as decision support in mass-casualty emergency situations.

Management and response in the case of an emergency is a very demanding task. Rescue missiuns can involve numerous individuals and teams working together to save lives and property. The outcome of a rescue mission depends to a large extent on the responding units' ability to co-operate and the overall co-ordination of their efforts. This in turn makes it imponant to investigate how to support the decision makers in emergency situations.

Recently, network organizations have been suggested as a solution for future crisis management and warfare. This will, however, have consequences for the development of decision support and critiquing systems. This paper suggests that there are special conditions that need to be taken into account when providing the means for decision-making in networked organizations. Hence, three research problems are suggested that need to be investigated in order to develop useful critiquing systems for future command and control systems.

This Innovative Practice Full Paper presents an approach to integrate three critical elements in Computer Science education.The call to imbue computer science graduates with strategic skills needed to address our pressing global sustainability challenges is extremely important, and a great challenge to degree programmes in computer science and software engineering. Doing this successfully requires great care, and possibly several iterations across an entire curriculum. In this regard, learning for sustainability faces similar challenges as understanding scientific results and ethics. Improving skills in searching for, reading, and producing academic texts are often neglected, as are skills in understanding ethics; what norms and values that guide our choices of methods for solving problems. To handle the fact that these subjects (academic writing, ethics and sustainability) are treated separately, and thereby lowering student engagement with the topics, we have successfully integrated them into one coherent subject of Professionalism in Computer Science. By integrating the three subjects, we do three things: a) describe a multi-faceted but integrated engineering role; b) integrate the three aspects of the role we focus on in education and steer away from the view that these are add-ons; and c) increase the motivation of students to take on these aspects of the engineering role.Our approach uses a flipped-classroom style with students playing educational games, participating in discussion seminars and conducting critical analyses of other students’ choices in IT system design. Much emphasis is on the students academic writing abilities, including critical information search and a student peer-review procedure. Also, we do this using an integrated assessment format where teachers from different disciplinary backgrounds jointly assess material from students, which stimulates discussions among ourselves about what and how to assess, and provides a practical way to integrate assessments. We present results from attitude surveys, course evaluations and the contents of the students’ analyses in their final essays. In conclusion, our approach demonstrates a clear shift in how students perceive sustainability, showing that it is possible to achieve changes in attitude towards the subjects as such and their importance for computer scientists.

The CDIO Initiative is going through a process of reconsidering and updating the CDIO approach for engineering education development. Previous work resulted in substantial updates of the twelve CDIO standards and the introduction of “optional” CDIO standards. This paper reports on a similar review and update of the CDIO Syllabus to version 3.0. It has been developed by a working group consisting of four sub-groups and iterated and refined guided by feedback from the whole CDIO community. There are mainly three external drivers that motivate the changes: sustainability, digitalization, and acceleration. There is also an internal driver in the form of lessons learned within the CDIO community, from using the Syllabus in curriculum and course development. Approximately 70 updates are proposed, amongst them three additions on the X.X level, namely 1.4 Knowledge of Social Sciences and Humanities, 3.1 Teamwork and Collaboration, and 5.3 Research.