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  • 1. Alégroth, Emil
    et al.
    Feldt, Robert
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV).
    Transitioning Manual System Test Suites to Automated Testing: An Industrial Case Study2013Ingår i: 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation, IEEE, 2013, s. 56-65Konferensbidrag (Refereegranskat)
    Abstract [en]

    Visual GUI testing (VGT) is an emerging technique that provides software companies with the capability to automate previously time-consuming, tedious, and fault prone manual system and acceptance tests. Previous work on VGT has shown that the technique is industrially applicable, but has not addressed the real-world applicability of the technique when used by practitioners on industrial grade systems. This paper presents a case study performed during an industrial project with the goal to transition from manual to automated system testing using VGT. Results of the study show that the VGT transition was successful and that VGT could be applied in the industrial context when performed by practitioners but that there were several problems that first had to be solved, e.g. testing of a distributed system, tool volatility. These problems and solutions have been presented together with qualitative, and quantitative, data about the benefits of the technique compared to manual testing, e.g. greatly improved execution speed, feasible transition and maintenance costs, improved bug finding ability. The study thereby provides valuable, and previously missing, contributions about VGT to both practitioners and researchers.

  • 2. Alégroth, Emil
    et al.
    Nass, Michael
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV).
    JAutomate: A Tool for System and Acceptance Test Automation2013Ingår i: 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation, IEEE, 2013, s. 439-446Konferensbidrag (Refereegranskat)
    Abstract [en]

    System- and acceptance-testing are primarily performed with manual practices in current software industry. However, these practices have several issues, e.g. they are tedious, error prone and time consuming with costs up towards 40 percent of the total development cost. Automated test techniques have been proposed as a solution to mitigate these issues, but they generally approach testing from a lower level of system abstraction, leaving a gap for a flexible, high system-level test automation technique/tool. In this paper we present JAutomate, a Visual GUI Testing (VGT) tool that fills this gap by combining image recognition with record and replay functionality for high system-level test automation performed through the system under test's graphical user interface. We present the tool, its benefits compared to other similar techniques and manual testing. In addition, we compare JAutomate with two other VGT tools based on their static properties. Finally, we present the results from a survey with industrial practitioners that identifies test-related problems that industry is currently facing and discuss how JAutomate can solve or mitigate these problems.

  • 3. Backlund, Emil
    et al.
    Bolle, Mikael
    Tichy, Matthias
    Olsson Holmström, Helena
    Malmö högskola, Teknik och samhälle.
    Bosch, Jan
    Automated User Interaction Analysis for Workflow-Based Web Portals2014Ingår i: Software Business: Towards Continuous Value Delivery, Springer, 2014, s. 148-162Konferensbidrag (Refereegranskat)
    Abstract [en]

    Success in the software market requires constant improvement of the software. These improvements however have to directly align with the needs of the users of the software. A recent trend in software engineering is to collect post-deployment data about how users use a software system. We report in this paper about a case study with an industrial partner in which (1) we identified which data has to be collected for a web-based portal system, (2) implemented the data collection, and (3) performed an experiment comparing the collected data with answers of the test subjects in a survey.

  • 4. Bosch, Jan
    et al.
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Data-Driven Continuous Evolution of Smart Systems2016Ingår i: Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, ACM Digital Library, 2016, s. 28-34Konferensbidrag (Refereegranskat)
    Abstract [en]

    As Marc Andreessen said in his Wall Street Journal OpEd, software is eating the world. The systems that we are building today and in the near future will exhibit levels of autonomy that will put new demands on the engineering of such systems. Although promising examples of autonomous systems exist, there is no established methodology for systematically building autonomous systems that employ modern software engineering technology such as continuous deployment and data-driven engineering. The contribution of this paper is twofold. First, it identifies and presents the challenge of continuous evolution of autonomous systems as a well-defined problem that needs to be addressed by software engineering research. Second, it presents a conceptual solution to this problem that integrates the development of new software for autonomous systems by R&D teams with systematic experimentation by autonomous systems.

  • 5. Bosch, Jan
    et al.
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS).
    Ecosystem traps and where to find them2018Ingår i: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, Vol. 30, nr 11, artikel-id e1961Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Today, companies operate in business ecosystems where they collaborate, compete, share, and learn from others with benefits such as to present more attractive offerings and sharing innovation costs. With ecosystems being the new way of operating, the ability to strategically reposition oneself to increase or shift power balance is becoming key for competitive advantage. However, companies run into a number of traps when trying to realize strategical changes in their ecosystems. In this paper, we identify 5 traps that companies fall into. First, the "descriptive versus prescriptive trap" is when companies assume that current boundaries between partners are immutable. Second, the "assumptions trap" is when powerful ecosystem partners assume that they understand what others regard as value-adding without validating their assumptions. Third, the "keeping it too simple trap" is when companies overlooks the effort required to align interests. Fourth, the "doing it all at once trap" is when companies disrupt an ecosystem assuming that all partners can change direction at the same time. Finally, the "planning trap" is when companies are unable to move forward without a complete plan. We provide empirical evidence for each trap, and we propose an ecosystem engagement process for how to avoid falling into these.

  • 6. Bosch, Jan
    et al.
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    From ad hoc to strategic ecosystem management: the "Three-Layer Ecosystem Strategy Model" (TeLESM)2017Ingår i: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, Vol. 29, nr 7, artikel-id e1876Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Recently, business ecosystems have been recognized as one of the most interesting phenomenon in software engineering research. Companies experience a paradigm shift where product development and innovation is moving outside the boundaries of the firm and where networks of stakeholders join forces to co-create value. While there is prominent research focusing on the managerial perspective of business ecosystems, few studies provide strategic guidance for how to intentionally manage the different ecosystems that companies operate in. Therefore, and on the basis of multicase study research, we provide empirical evidence on the challenges that software-intensive companies experience in relation to the different types of business ecosystems they operate in. We conduct a state-of-the-art literature review to identify strategies that are used to manage ecosystem engagements, and we develop a conceptual model in which we identify strategies for managing the innovation ecosystem, the differentiating ecosystem, and the commoditizing ecosystem. By categorising the different strategies in relation to the different types of ecosystems for which they are valid, the three-layer ecosystem strategy model provides comprehensive support for strategy selection. We validate the use of the identified strategies in 6 software-intensive case companies, and we provide empirical insights on the relevance and the desired use of these strategies as experienced by the case companies.

  • 7. Bosch, Jan
    et al.
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Toward Evidence-Based Organizations Lessons from Embedded Systems, Online Games, and the Internet of Things2017Ingår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 34, nr 5, s. 60-66Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Case studies investigated how companies in three domains transition to data-driven development. The results led to a model of the levels that software-intensive companies move through as they evolve from an opinionbased to an evidence-based organization.

  • 8. Bosch, Jan
    et al.
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV).
    Björk, Jens
    Ljungblad, Jens
    The Early Stage Software Startup Development Model: A Framework for Supporting Lean Principles in Software Startups2013Ingår i: Lean Enterprise Software and Systems. LESS 2013., Springer, 2013, s. 1-15Konferensbidrag (Refereegranskat)
    Abstract [en]

    Software startups are more popular than ever and growing in numbers. They operate under conditions of extreme uncertainty and face many challenges. Often, agile development practices and lean principles are suggested as ways to increase the odds of succeeding as a startup, as they both advocate close customer collaboration and short feedback cycles focusing on delivering direct customer value. However, based on an interview study we see that despite guidance and support in terms of well-known and documented development methods, practitioners find it difficult to implement and apply these in practice. To explore this further, and to propose operational support for software startup companies, this study aims at investigating (1) what are the typical challenges when finding a product idea worth scaling, and (2) what solution would serve to address these challenges. To this end, we propose the ‘Early Stage Software Startup Development Model’ (ESSSDM). The model extends already existing lean principles, but offers novel support for practitioners for investigating multiple product ideas in parallel, for determining when to move forward with a product idea, and for deciding when to abandon a product idea. The model was evaluated in a software startup project, as well as with industry professionals within the software startup domain.

  • 9. Dingsøyr, Torgeir
    et al.
    Moe, Nils Brede
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Towards an Understanding of Scaling Frameworks and Business Agility2018Ingår i: 19th International Conference On Agile Software Development (Xp '18), ACM Digital Library, 2018, artikel-id 6Konferensbidrag (Refereegranskat)
    Abstract [en]

    Large development projects and programs are conducted using agile development methods, with an increasing body of advice from practitioners and from research. This sixth workshop showed in increasing interest in scaling frameworks and in topics related to achieving business agility. This article summarizes four contributed papers, discussions in "open space" format and also presents a revised research agenda for large-scale agile development.

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  • 10.
    Eklund, Ulrik
    et al.
    Malmö högskola, Teknik och samhälle.
    Olsson Holmström, Helena
    Malmö högskola, Teknik och samhälle.
    Strøm, Niels Jørgen
    Industrial Challenges of Scaling Agile in Mass-Produced Embedded Systems2014Ingår i: Agile Methods. Large-Scale Development, Refactoring, Testing, and Estimation: XP 2014 International Workshops, Rome, Italy, May 26-30, 2014, Revised Selected Papers, Springer, 2014, s. 30-42Konferensbidrag (Refereegranskat)
    Abstract [en]

    When individual teams in mechatronic organizations attempt to adopt agile software practices, these practices tend to only affect mod- ules or sub-systems. The short iterations on team level do not lead to short lead-times in launching new or updated products since the overall R&D approach on an organization level is still governed by an overall stage gate or single cycle V-model. This paper identifies challenges for future research on how to combine the predictability and planning desired of mechanical manufacturing with the dynamic capabilities of modern agile software development. Scaling agile in this context requires an expansion in two dimensions: First, scal- ing the number of involved teams. Second, traversing necessary systems engineering activities in each sprint due to the co-dependency of software and hardware development.

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  • 11.
    Fabijan, Aleksander
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS).
    Dmitriev, Pavel
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Effective Online Controlled Experiment Analysis at Large Scale2018Ingår i: Proceedings of the EUROMICRO Conference, IEEE, 2018, s. 64-67Konferensbidrag (Refereegranskat)
    Abstract [en]

    Online Controlled Experiments (OCEs) are the norm in data-driven software companies because of the benefits they provide for building and deploying software. Product teams experiment to accurately learn whether the changes that they do to their products (e.g. adding new features) cause any impact (e.g. customers use them more frequently). Experiments also help reduce the risk from deploying software by minimizing the magnitude and duration of harm caused by software bugs, allowing software to be shipped more frequently. To make informed decisions in product development, experiment analysis needs to be granular with a large number of metrics over heterogeneous devices and audiences. Discovering experiment insights by hand, however, can be cumbersome. In this paper, and based on case study research at a large-scale software development company with a long tradition of experimentation, we (1) describe the standard process of experiment analysis, and (2) introduce an artifact to improve the effectiveness and comprehensiveness of this process.

  • 12.
    Fabijan, Aleksander
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS).
    Dmitriev, Pavel
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Online Controlled Experimentation at Scale: An Empirical Survey on the Current State of A/B Testing2018Ingår i: Proceedings of the EUROMICRO Conference, IEEE, 2018, s. 68-72Konferensbidrag (Refereegranskat)
    Abstract [en]

    Online Controlled Experiments (OCEs, aka A/B tests) are one of the most powerful methods for measuring how much value new features and changes deployed to software products bring to users. Companies like Microsoft, Amazon, and Booking.com report the ability to conduct thousands of OCEs every year. However, the competences of the remainder of the online software industry remain unknown. The main objective of this paper is to reveal the current state of A/B testing maturity in the software industry based on a maturity model from our previous research. We base our findings on 44 responses from an online empirical survey. Our main contribution of this paper is the current state of experimentation maturity as operationalized by the ExG model for a convenience sample of companies doing online controlled experiments. Our findings show that, among others, companies typically develop in-house experimentation platforms, that these platforms are of various levels of maturity, and that designing key metrics - Overall Evaluation Criteria - remains the key challenge for successful experimentation.

  • 13.
    Fabijan, Aleksander
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Dmitriev, Pavel
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Bosch, Jan
    The Online Controlled Experiment Lifecycle2020Ingår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 37, nr 2, s. 60-67Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Online Controlled Experiments (OCEs) enable an accurate understanding of customer value and generate millions of dollars of additional revenue at Microsoft. Unlike other techniques for learning from customers, OCEs establish an accurate and causal relationship between a change and the impact observed. Although previous research describes technical and statistical dimensions, the key phases of online experimentation are not widely known, their impact and importance are obscure, and how to establish OCEs in an organization is underexplored. In this paper, using a longitudinal in-depth case study, we address this gap by (1) presenting the Experiment Lifecycle, and (2) demonstrating with four example experiments their profound impact. We show that OECs help optimize infrastructure needs and aid in project planning and measuring team efforts, in addition to their primary goal of accurately identifying what customers value. We conclude that product development should fully integrate the Experiment Lifecycle to benefit from the OCEs.

  • 14.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Dmitriev, Pavel
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosh, Jan
    The Evolution of Continuous Experimentation in Software Product Development: From Data to a Data-Driven Organization at Scale2017Ingår i: International Conference on Software Engineering. Proceedings, IEEE, 2017, s. 770-780Konferensbidrag (Refereegranskat)
    Abstract [en]

    Software development companies are increasingly aiming to become data-driven by trying to continuously experiment with the products used by their customers. Although familiar with the competitive edge that the A/B testing technology delivers, they seldom succeed in evolving and adopting the methodology. In this paper, and based on an exhaustive and collaborative case study research in a large software-intense company with highly developed experimentation culture, we present the evolution process of moving from ad-hoc customer data analysis towards continuous controlled experimentation at scale. Our main contribution is the "Experimentation Evolution Model" in which we detail three phases of evolution: technical, organizational and business evolution. With our contribution, we aim to provide guidance to practitioners on how to develop and scale continuous experimentation in software organizations with the purpose of becoming data-driven at scale.

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  • 15.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Dmitriev, Pavel
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosh, Jan
    The Benefits of Controlled Experimentation at Scale2017Ingår i: 2017 43rd Euromicro Conference on Software Engineering and Advanced Applications (SEAA), IEEE, 2017, s. 18-26Konferensbidrag (Refereegranskat)
    Abstract [en]

    Online controlled experiments (for example A/B tests) are increasingly being performed to guide product development and accelerate innovation in online software product companies. The benefits of controlled experiments have been shown in many cases with incremental product improvement as the objective. In this paper, we demonstrate that the value of controlled experimentation at scale extends beyond this recognized scenario. Based on an exhaustive and collaborative case study in a large software-intensive company with highly developed experimentation culture, we inductively derive the benefits of controlled experimentation. The contribution of our paper is twofold. First, we present a comprehensive list of benefits and illustrate our findings with five case examples of controlled experiments conducted at Microsoft. Second, we provide guidance on how to achieve each of the benefits. With our work, we aim to provide practitioners in the online domain with knowledge on how to use controlled experimentation to maximize the benefits on the portfolio, product and team level.

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  • 16.
    Fabijan, Aleksander
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Dmitriev, Pavel
    Vermeer, Lukas
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Bosch, Jan
    Experimentation growth: Evolving trustworthy A/B testing capabilities in online software companies2018Ingår i: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, Vol. 30, nr 12, artikel-id e2113Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Companies need to know how much value their ideas deliver to customers. One of the most powerful ways to accurately measure this is by conducting online controlled experiments (OCEs). To run experiments, however, companies need to develop strong experimentation practices as well as align their organization and culture to experimentation. The main objective of this paper is to demonstrate how to run OCEs at large scale using the experience of companies that succeeded in scaling. Based on case study research at Microsoft, Booking.com, Skyscanner, and Intuit, we present our main contribution—The Experiment Growth Model. This four‐stage model addresses the seven critical aspects of experimentation and can help companies to transform their organizations into learning laboratories where new ideas can be tested with scientific accuracy. Ultimately, this should lead to better products and services.

  • 17.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Commodity Eats Innovation for Breakfast: A Model for Differentiating Feature Realization2016Ingår i: Product-Focused Software Process Improvement: 17th International Conference, PROFES 2016, Trondheim, Norway, November 22-24, 2016, Proceedings, Springer, 2016, s. 517-525Konferensbidrag (Refereegranskat)
    Abstract [en]

    Once supporting the electrical and mechanical functionality, software today became the main competitive advantage in products. However, in the companies that we study, the way in which software features are developed still reflects the traditional ‘requirements over the wall’ approach. As a consequence, individual departments prioritize what they believe is the most important and are unable to identify which features are regularly used – ‘flow’, there to be bought – ‘wow’, differentiating and that add value to customers, or which are regarded commodity. In this paper, and based on case study research in three large software-intensive companies, we (1) provide empirical evidence that companies do not distinguish between different types of features, which causes poor allocation of R&D efforts and suppresses innovation, and (2) develop a model in which we depict the activities for differentiating and working with different types of features and stakeholders.

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  • 18.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Bosch, Jan
    Customer Feedback and Data Collection Techniques in Software R&D: A Literature Review2015Ingår i: Software Business: 6th International Conference, ICSOB 2015, Braga, Portugal, June 10-12, 2015, Proceedings, Springer, 2015, s. 139-153Konferensbidrag (Refereegranskat)
    Abstract [en]

    In many companies, product management struggles in getting accurate customer feedback. Often, validation and confirmation of functionality with customers takes place only after the product has been deployed, and there are no mechanisms that help product managers to continuously learn from customers. Although there are techniques available for collecting customer feedback, these are typically not applied as part of a continuous feedback loop. As a result, the selection and prioritization of features becomes far from optimal, and product deviates from what the customers need. In this paper, we present a literature review of currently recognized techniques for collecting customer feedback. We develop a model in which we categorize the techniques according to their characteristics. The purpose of this literature review is to provide an overview of current software engineering research in this area and to better understand the different techniques that are used for collecting customer feedback.

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  • 19.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Data-Driven Decision-Making in Product R&D2015Ingår i: Agile Processes in Software Engineering and Extreme Programming: 16th International Conference, XP 2015, Helsinki, Finland, May 25-29, 2015, Proceedings, Springer, 2015, s. 350-351Konferensbidrag (Refereegranskat)
    Abstract [en]

    Software development companies experience the road mapping and requirements ranking process to be complex as product management (PdM) strives in getting timely and accurate feedback from the customers. Often, companies have insufficient knowledge about how their products are being used, what features the customers appreciate and which ones will generate revenue. To address this problem, this research aims at helping the companies in closing the 'open' feedback loop that exists between PdM and customers. Moreover, the research strives at exploring techniques that can be used to involve customers in continuous validation of software functionality in order to provide PdM with the evidence needed for accurate R&D investments.

  • 20.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Bosch, Jan
    Early Value Argumentation and Prediction: An Iterative Approach to Quantifying Feature Value2015Ingår i: Product-Focused Software Process Improvement, Springer, 2015, s. 16-23Konferensbidrag (Refereegranskat)
    Abstract [en]

    Companies are continuously improving their practices and ways of working in order to fulfill always-changing market requirements. As an example of building a better understanding of their customers, organizations are collecting user feedback and trying to direct their R&D efforts by e.g. continuing to develop features that deliver value to the customer. We (1) develop an actionable technique that practitioners in organizations can use to validate feature value early in the development cycle, (2) validate if and when the expected value reflects on the customers, (3) know when to stop developing it, and (4) identity unexpected business value early during development and redirect R&D effort to capture this value. The technique has been validated in three experiments in two cases companies. Our findings show that predicting value for features under development helps product management in large organizations to correctly re-prioritize R&D investments.

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  • 21.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    The Lack of Sharing of Customer Data in Large Software Organizations: Challenges and Implications2016Ingår i: Agile Processes, in Software Engineering, and Extreme Programming, Springer, 2016, s. 39-52Konferensbidrag (Refereegranskat)
    Abstract [en]

    With agile teams becoming increasingly multi-disciplinary and including all functions, the role of customer feedback is gaining momentum. Today, companies collect feedback directly from customers, as well as indirectly from their products. As a result, companies face a situation in which the amount of data from which they can learn about their customers is larger than ever before. In previous studies, the collection of data is often identified as challenging. However, and as illustrated in our research, the challenge is not the collection of data but rather how to share this data among people in order to make effective use of it. In this paper, and based on case study research in three large software-intensive companies, we (1) provide empirical evidence that ‘lack of sharing’ is the primary reason for insufficient use of customer and product data, and (2) develop a model in which we identify what data is collected, by whom data is collected and in what development phases it is used. In particular, the model depicts critical hand-overs where certain types of data get lost, as well as the implications associated with this. We conclude that companies benefit from a very limited part of the data they collect, and that lack of sharing of data drives inaccurate assumptions of what constitutes customer value.

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  • 22.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Time to Say 'Good Bye': Feature Lifecycle2016Ingår i: Proceedings 42nd Euromicro Conference on Software Engineering and Advanced Applications SEAA 2016, IEEE, 2016, s. 9-16Konferensbidrag (Refereegranskat)
    Abstract [en]

    With continuous deployment of software functionality, a constant flow of new features to products is enabled. Although new functionality has potential to deliver improvements and possibilities that were previously not available, it does not necessary generate business value. On the contrary, with fast and increasing system complexity that is associated with high operational costs, more waste than value risks to be created. Validating how much value a feature actually delivers, project how this value will change over time, and know when to remove the feature from the product are the challenges large software companies increasingly experience today. We propose and study the concept of a software feature lifecycle from a value point of view, i.e. how companies track feature value throughout the feature lifecycle. The contribution of this paper is a model that illustrates how to determine (1) when to add the feature to a product, (2) how to track and (3) project the value of the feature during the lifecycle, and how to (4) identify when a feature is obsolete and should be removed from the product.

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  • 23.
    Fabijan, Aleksander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosh, Jan
    Differentiating Feature Realization in Software Product Development2017Ingår i: Product-Focused Software Process Improvement: Product-Focused Software Process Improvement. PROFES 2017., Springer, 2017, s. 221-236Konferensbidrag (Refereegranskat)
    Abstract [en]

    Software is no longer only supporting mechanical and electrical products. Today, it is becoming the main competitive advantage and an enabler of innovation. Not all software, however, has an equal impact on customers. Companies still struggle to differentiate between the features that are regularly used, there to be for sale, differentiating and that add value to customers, or which are regarded commodity. Goal: The aim of this paper is to (1) identify the different types of software features that we can find in software products today, and (2) recommend how to prioritize the development activities for each of them. Method: In this paper, we conduct a case study with five large-scale software intensive companies. Results: Our main result is a model in which we differentiate between four fundamentally different types of features (e.g. ‘Checkbox’, ‘Flow’, ‘Duty’ and ‘Wow’). Conclusions: Our model helps companies in (1) differentiating between the feature types, and (2) selecting an optimal methodology for their development (e.g. ‘Output-Driven’ vs. ‘Outcome-Driven’).

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  • 24. Felderer, Michael
    et al.
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Rabiser, Rick
    Introduction to the special issue on quality engineering and management of software-intensive systems2019Ingår i: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 149, s. 533-534Artikel i tidskrift (Övrigt vetenskapligt)
  • 25. Figalist, Iris
    et al.
    Elsner, Christoph
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Scaling Agile Beyond Organizational Boundaries: Coordination Challenges in Software Ecosystems2019Ingår i: Agile Processes in Software Engineering and Extreme Programming: 20th International Conference, XP 2019, Montréal, QC, Canada, May 21–25, 2019, Proceedings, Springer, 2019, s. 189-206Konferensbidrag (Refereegranskat)
    Abstract [en]

    The shift from sequential to agile software development originates from relatively small and co-located teams but soon gained prominence in larger organizations. How to apply and scale agile practices to fit the needs of larger projects has been studied to quite an extent in previous research. However, scaling agile beyond organizational boundaries, for instance in a software ecosystem context, raises additional challenges that existing studies and approaches do not yet investigate or address in great detail. For that reason, we conducted a case study in two software ecosystems that comprise several agile actors from different organizations and, thereby, scale development across organizational boundaries, in order to elaborate and understand their coordination challenges. Our results indicate that most of the identified challenges are caused by long communication paths and a lack of established processes to facilitate these paths. As a result, the participants in our study, among others, experience insufficient responsivity, insufficient communication of prioritizations and deliverables, and alterations or loss of information. As a consequence, agile practices need to be extended to fit the identified needs.

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  • 26. Johansson, Enrico
    et al.
    Bergdahl, Daniel
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Quantitative Requirements Prioritization from a Pre-development Perspective2015Ingår i: Software Process Improvement and Capability Determination: 15th International Conference, SPICE 2015, Gothenburg, Sweden, June 16-17, 2015. Proceedings, Springer, 2015, s. 58-71Konferensbidrag (Refereegranskat)
    Abstract [en]

    Feature content in system releases tends to be prioritized using limited amounts of qualitative user input and based on the opinions of those in product management. This leads to several problems due to the wasteful allocation of R&D resources. In this paper, we present the results of our efforts to collect quantitative customer input before the start of development using mock-ups and surveys for a mobile application developed by Sony Mobile. Our research shows that (1) collecting quantitative feedback before development is feasible, (2) the data collected deviates from the original feature prioritization, i.e. it is beneficial and (3) the data gives further insight in requirement prioritization than a qualitative method could have provided.

  • 27.
    Johansson, Enrico
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bergdahl, Daniel
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Requirement Prioritization with Quantitative Data: A Case Study2015Ingår i: Product-Focused Software Process Improvement: 16th International Conference, PROFES 2015, Bolzano, Italy, December 2-4, 2015, Proceedings, Springer, 2015, s. 89-104Konferensbidrag (Refereegranskat)
    Abstract [en]

    Feature content in system releases tends to be prioritized using limited amounts of qualitative user input and based on the opinions of those in product management. This leads to several problems including the wasteful allocation of R&D resources. In this paper, we present the results of our efforts to collect quantitative customer input before the start of development using a mock-up for a mobile application developed by Sony Mobile Communications Inc. Our research shows that (1) product managers change their prioritization when quantitative data is presented to them; (2) product managers change their prioritization which is converged to the prioritization indicated by the quantitative data (3) the quantitative data is regarded as beneficial by the product managers.

  • 28.
    John, Meenu Mary
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Helena Holmström
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Bosch, Jan
    Chalmers University of Technology.
    Developing ML/DL Models: A Design Framework2020Ingår i: International Conference on Software and Systems Process, October 10–11, 2020, Seoul, Republic of Korea, 2020Konferensbidrag (Refereegranskat)
    Abstract [en]

    Artificial Intelligence is becoming increasingly popular with organizations due to the success of Machine Learning and Deep Learning techniques. Using these techniques, data scientists learn from vast amounts of data to enhance behaviour in software-intensive systems. Despite the attractiveness of these techniques, however, there is a lack of systematic and structured design process for developing ML/DL models. The study uses a multiple-case study approach to explore the different activities and challenges data scientists face when developing ML/DL models in software-intensive embedded systems. In addition, we have identified seven different phases in the proposed design process leading to effective model development based on the case study. Iterations identified between phases and events which trigger these iterations optimize the design process for ML/DL models. Lessons learned from this study allow data scientists and engineers to develop high-performance ML/DL models and also bridge the gap between high demand and low supply of data scientists.

  • 29. Karvonen, Teemu
    et al.
    Lwakatare, Lucy Ellen
    Sauvola, Tanja
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Kuvaja, Pasi
    Oivo, Markku
    Hitting the Target: Practices for Moving Toward Innovation Experiment Systems2015Ingår i: Software Business: 6th International Conference, ICSOB 2015, Braga, Portugal, June 10-12, 2015, Proceedings, Springer, 2015, s. 117-131Konferensbidrag (Refereegranskat)
    Abstract [en]

    The benefits and barriers that software development companies face when moving beyond agile development practices are identified in a multiple-case study in five Finnish companies. The practices that companies need to adopt when moving towards innovation experiment systems are recognised. The background of the study is the Stairway to Heaven (StH) model that describes the path that many software development companies take when advancing their development practices. The development practices in each case are investigated and analysed in relation to the StH model. At first the results of the analysis strengthened the validity of the StH model as a path taken by software development companies to advance their development practices. Based on the findings, the StH model was extended with a set of additional practices and their adoption levels for each step of the model. The extended model was validated in five case companies.

  • 30. Lwakatare, Lucy Ellen
    et al.
    Karvonen, Teemu
    Sauvola, Tanja
    Kuvaja, Pasi
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Oivo, Markku
    Towards DevOps in the Embedded Systems Domain: Why is It so Hard?2016Ingår i: 2016 49th Hawaii International Conference on System Sciences (HICSS), IEEE, 2016, s. 5437-5446Konferensbidrag (Refereegranskat)
    Abstract [en]

    DevOps is a predominant phenomenon in the web domain. Its two core principles emphasize collaboration between software development and operations, and the use of agile principles to manage deployment environments and their configurations. DevOps techniques, such as collaboration and behaviour-driven monitoring, have been used by web companies to facilitate continuous deployment of new functionality to customers. The techniques may also offer opportunities for continuous product improvement when adopted in the embedded systems domain. However, certain characteristics of embedded software development present obstacles for DevOps adoption, and as yet, there is no empirical evidence of its adoption in the embedded systems domain. In this study, we present the challenges for DevOps adoption in embedded systems using a multiple-case study approach with four companies. The contribution of this paper is to introduce the concept of DevOps adoption in the embedded systems domain and then to identify key challenges for the DevOps adoption.

  • 31. Lwakatare, Lucy
    et al.
    Raj, Aiswarya
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Crnkovic, Ivica
    A taxonomy of software engineering challenges for machine learning systems: An empirical investigation2019Ingår i: Agile Processes in Software Engineering and Extreme Programming: 20th International Conference, XP 2019, Montréal, QC, Canada, May 21–25, 2019, Proceedings, Springer, 2019, s. 227-243Konferensbidrag (Refereegranskat)
    Abstract [en]

    Artificial intelligence enabled systems have been an inevitable part of everyday life. However, efficient software engineering principles and processes need to be considered and extended when developing AI- enabled systems. The objective of this study is to identify and classify software engineering challenges that are faced by different companies when developing software-intensive systems that incorporate machine learning components. Using case study approach, we explored the development of machine learning systems from six different companies across various domains and identified main software engineering challenges. The challenges are mapped into a proposed taxonomy that depicts the evolution of use of ML components in software-intensive system in industrial settings. Our study provides insights to software engineering community and research to guide discussions and future research into applied machine learning.

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  • 32. Mattos, David Issa
    et al.
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    More for Less: Automated Experimentation in Software-Intensive Systems2017Ingår i: Product-Focused Software Process Improvement, Springer, 2017, s. 146-161Konferensbidrag (Refereegranskat)
    Abstract [en]

    Companies developing autonomous and software-intensive systems show an increasing need to adopt experimentation and data-driven strategies in their development process. With the growing complexity of the systems, companies are increasing their data analytic and experimentation teams to support data-driven development. However, organizations cannot increase in size at the same pace as the system complexity grows. Experimentation teams could run a larger number of experiments by letting the system itself to coordinate its own experiments, instead of the humans. This process is called automated experimentation. However, currently, no tools or frameworks address the challenge of running automated experiments. This paper discusses, through a set of architectural design decisions, the development of an architecture framework that supports automated continuous experiments. The contribution of this paper is twofold. First, it presents, through a set of architectural design decisions, an architecture framework for automated experimentation. Second, it evaluates the architecture framework experimentally in the context of a human-robot interaction proxemics distance problem. This automated experimentation framework aims to deliver more value from the experiments while using fewer R&D resources.

  • 33. Mattos, David Issa
    et al.
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Your System Gets Better Every Day You Use It: Towards Automated Continuous Experimentation2017Ingår i: 2017 43rd Euromicro Conference on Software Engineering and Advanced Applications (SEAA), IEEE, 2017, s. 256-265Konferensbidrag (Refereegranskat)
    Abstract [en]

    Innovation and optimization in software systems can occur from pre-development to post-deployment stages. Companies are increasingly reporting the use of experiments with customers in their systems in the post-deployment stage. Experiments with customers and users are can lead to a significant learning and return-on-investment. Experiments are used for both validation of manual hypothesis testing and feature optimization, linked to business goals. Automated experimentation refers to having the system controlling and running the experiments, opposed to having the R&D organization in control. Currently, there are no systematic approaches that combine manual hypothesis validation and optimization in automated experiments. This paper presents concepts related to automated experimentation, as controlled experiments, machine learning and software architectures for adaptation. However, this paper focuses on how architectural aspects that can contribute to support automated experimentation. A case study using an autonomous system is used to demonstrate the developed initial architecture framework. The contributions of this paper are threefold. First, it identifies software architecture qualities to support automated experimentation. Second, it develops an initial architecture framework that supports automated experiments and validates the framework with an autonomous mobile robot. Third, it identifies key research challenges that need to be addressed to support further development of automated experimentation.

  • 34. Mattos Issa, David
    et al.
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Challenges and Strategies for Undertaking Continuous Experimentation to Embedded Systems: Industry and Research Perspectives2018Ingår i: XP 2018: Agile Processes in Software Engineering and Extreme Programming, Springer, 2018, s. 277-292Konferensbidrag (Refereegranskat)
    Abstract [en]

    Context: Continuous experimentation is frequently used in web-facing companies and it is starting to gain the attention of embedded systems companies. However, embedded systems companies have different challenges and requirements to run experiments in their systems. Objective: This paper explores the challenges during the adoption of continuous experimentation in embedded systems from both industry practice and academic research. It presents strategies, guidelines, and solutions to overcome each of the identified challenges. Method: This research was conducted in two parts. The first part is a literature review with the aim to analyze the challenges in adopting continuous experimentation from the research perspective. The second part is a multiple case study based on interviews and workshop sessions with five companies to understand the challenges from the industry perspective and how they are working to overcome them. Results: This study found a set of twelve challenges divided into three areas; technical, business, and organizational challenges and strategies grouped into three categories, architecture, data handling and development processes. Conclusions: The set of identified challenges are presented with a set of strategies, guidelines, and solutions. To the knowledge of the authors, this paper is the first to provide an extensive list of challenges and strategies for continuous experimentation in embedded systems. Moreover, this research points out open challenges and the need for new tools and novel solutions for the further development of experimentation in embedded systems.

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  • 35. Mattos Issa, David
    et al.
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Multi-armed bandits in the wild: Pitfalls and strategies in online experiments2019Ingår i: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Delivering faster value to customers with online experimentation is an emerging practice in industry. Multi-Armed Bandit (MAB) based experiments have the potential to deliver even faster results with a better allocation of resources over traditional A/B experiments. However, the incorrect use of MAB-based experiments can lead to incorrect conclusions that can potentially hurt the company's business. The objective of this study is to understand the pitfalls and restrictions of using MABs in online experiments, as well as the strategies that are used to overcome them. This research uses a multiple case study method with eleven experts across five software companies and simulations to triangulate the data of some of the identified limitations. This study analyzes some limitations faced by companies using MAB and discusses strategies used to overcome them. The results are summarized into practitioners’ guidelines with criteria to select an appropriated experimental design. MAB algorithms have the potential to deliver even faster results with a better allocation of resources over traditional A/B experiments. However, potential mistakes can occur and hinder the potential benefits of such approach. Together with the provided guidelines, we aim for this paper to be used as reference material for practitioners during the design of an online experiment.

  • 36. Mattos Issa, David
    et al.
    Fabijan, Aleksander
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Dimitriev, Pavel
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    An Activity and Metric Model for Online Controlled Experiments2018Ingår i: PROFES 2018: Product-Focused Software Process Improvement, Springer, 2018, s. 182-198Konferensbidrag (Refereegranskat)
    Abstract [en]

    Accurate prioritization of efforts in product and services development is critical to the success of every company. Online controlled experiments, also known as A/B tests, enable software companies to establish causal relationships between changes in their systems and the movements in the metrics. By experimenting, product development can be directed towards identifying and delivering value. Previous research stresses the need for data-driven development and experimentation. However, the level of granularity in which existing models explain the experimentation process is neither sufficient, in terms of details, nor scalable, in terms of how to increase number and run different types of experiments, in an online setting. Based on a case study of multiple products running online controlled experiments at Microsoft, we provide an experimentation framework composed of two detailed experimentation models focused on two main aspects; the experimentation activities and the experimentation metrics. This work intends to provide guidelines to companies and practitioners on how to set and organize experimentation activities for running trustworthy online controlled experiments.

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  • 37. Mattos Issa, David
    et al.
    Mårtensson, Erling
    Bosch, Jan
    Olsson Holmström, Helena
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Optimization Experiments in the Continuous Space the Limited Growth Optimistic Optimization Algorithm2018Ingår i: SSBSE 2018: Search-Based Software Engineering, Springer, 2018, s. 293-308Konferensbidrag (Refereegranskat)
    Abstract [en]

    Online controlled experiments are extensively used by web-facing companies to validate and optimize their systems, providing a competitive advantage in their business. As the number of experiments scale, companies aim to invest their experimentation resources in larger feature changes and leave the automated techniques to optimize smaller features. Optimization experiments in the continuous space are encompassed in the many-armed bandits class of problems. Although previous research provides algorithms for solving this class of problems, these algorithms were not implemented in real-world online experimentation problems and do not consider the application constraints, such as time to compute a solution, selection of a best arm and the estimation of the mean-reward function. This work discusses the online experiments in context of the many-armed bandits class of problems and provides three main contributions: (1) an algorithm modification to include online experiments constraints, (2) implementation of this algorithm in an industrial setting in collaboration with Sony Mobile, and (3) statistical evidence that supports the modification of the algorithm for online experiments scenarios. These contributions support the relevance of the LG-HOO algorithm in the context of optimization experiments and show how the algorithm can be used to support continuous optimization of online systems in stochastic scenarios.

  • 38.
    Olsson, Helena Holmström
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Bosch, Jan
    Going digital: Disruption and transformation in software-intensive embedded systems ecosystems2020Ingår i: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, artikel-id e2249Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Digitalization is transforming industry to an extent that we have only seen the beginnings of. Across domains, companies experience rapid changes to their existing practices due to new technologies and new entrants that current businesses. While digitalization brings endless opportunities, it comes with challenges that require companies to strategically engage with partners in their surrounding ecosystems. In this paper, we study how companies in the embedded systems domain experience the process of transitioning from product-based companies to businesses where software, data, and artificial intelligence (AI) play an increasingly important role. To manage this, these companies need to evolve their existing ecosystems while at the same time create new ecosystems around new technologies. This involves maintaining existing technologies such as mechanics and electronics while at the same time expanding these with software, data, and AI. We provide a strategic decision framework that helps software-intensive embedded systems companies to successfully navigate the digital transformation. We do this in two steps. First, we present three models that provide the technical content of the strategic decision framework. Second, we provide an overview of the strategic alternatives that incumbents and new entrants have available when existing technologies are commoditizing and new technologies are introduced.

  • 39.
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö högskola, Internet of Things and People (IOTAP).
    So Much Data - So Little Value: A multi-case study on improving the impact of data-driven development practices2017Ingår i: 20th Conferencia Iberoamericanaen Software Engineering (CIbSE 2017), CIBSE , 2017, s. 249-262Konferensbidrag (Refereegranskat)
  • 40.
    Olsson Holmström, Helena
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV).
    The ‘Three Layer Ecosystem Strategy Model’ (TeLESM)2015Ingår i: Proceedings of the1st Scandinavian Workshop on theEngineering of Systems-of-Systems(SWESoS 2015), Swedish Institute of Computer Science (SICS) , 2015Konferensbidrag (Refereegranskat)
  • 41.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Collaborative Innovation: A Model For Selecting The Optimal Ecosystem Innovation Strategy2016Ingår i: 2016 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), IEEE, 2016, s. 206-213Konferensbidrag (Refereegranskat)
    Abstract [en]

    Traditionally, innovation initiatives in software-intensive systems companies are viewed as either internal innovation, such as technology driven innovation based on ideas generated within a company, as collaborative innovation where a number of stakeholders co-create value, or as external innovation in which companies adopt strategies to capture and expand on ideas created by other stakeholders. However, and based on longitudinal case study research in six software-intense companies in the embedded systems domain, we see that most innovation strategies involve a mix of internal, collaborative and external elements. Due to the dichotomy in approaches however, companies often fail to select the optimal innovation strategy for the specific innovation challenge at hand. As a result, innovation initiatives suffer and companies and their ecosystem partners cannot fully capitalize on the value created. In this paper, we present a conceptual framework in which we identify twelve different ecosystem-centric innovation strategies. For each strategy, we identify the internal, the collaborative and the external elements. Also, and based on our empirical findings, we provide guidelines on the optimal selection of strategies.

  • 42.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV).
    Bosch, Jan
    Ecosystem-Driven Software Development: A case study on the emerging challenges in inter-organizational R&D2014Ingår i: ICSOB 2014: Software Business. Towards Continuous Value Delivery, Springer, 2014, s. 16-26Konferensbidrag (Refereegranskat)
    Abstract [en]

    Most companies today experience a situation in which they are part of a complex business ecosystem of stakeholders that influence business outcomes. Especially for companies transitioning from selling products to becoming systems, solutions and services providers, this is causing a significant shift in their business strategies and relationships. Instead of focusing on internal processes, companies need to strategically position themselves in a dynamic network of actors to accelerate synergies and value co-creation. However, while this shift in business strategy is inevitable, it is not without challenges. An understanding for how to align internal, as well as external processes is critical, as well as a careful assessment on how to establish strategic partnerships in a dynamic network of interests. Based on on-going research, this paper outlines the emerging challenges that most software development companies face when adopting an ecosystem-driven approach, and the different mitigation strategies to manage these.

  • 43.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Teknik och samhälle. Malmö högskola, Internet of Things and People (IOTAP).
    Bosch, Jan
    From Opinions to Data-Driven Software R&D: A Multi-Case Study On How To Close The 'Open Loop' Problem2014Ingår i: Proceedings of the Euromicro Conference, IEEE, 2014, s. 9-16Konferensbidrag (Refereegranskat)
    Abstract [en]

    In most software development companies the road mapping and requirements prioritization process is a complex process in which product management experiences difficulties in getting timely and accurate customer feedback. The feedback loop from customers is slow and often there is a lack of mechanisms that allow for efficient customer data collection and analysis. As a result, there is the risk that requirements prioritization becomes opinion-based rather than data-driven, and that R&D investments are made without an accurate way of continuously validating whether they correspond to customer needs. We call this phenomenon the 'open loop' problem, referring to the challenges for product management to get accurate and timely feedback from customers. To address this problem, we develop the HYPEX model (Hypothesis Experiment Data-Driven Development) that supports companies in running feature experiments to shorten customer feedback loops. We evaluate the model in three software development companies and observe how feature experiments increase the opportunity for data-driven software development.

  • 44.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Bosch, Jan
    From Requirements To Continuous Re-prioritization Of Hypotheses2016Ingår i: Proceedings of the International Workshop on Continuous Software Evolution and Delivery (CSED '16), ACM Digital Library, 2016, s. 63-69Konferensbidrag (Refereegranskat)
    Abstract [en]

    Typically, customer feedback collected in the prestudy, and during the early stages of software development, determines what new features to develop. However, once the decision to develop a new feature is taken, companies stop validating if this feature adds value to its intended customers. Instead, focus is shifted towards developing and implementing the feature. As a result, re-prioritization of feature content is rare, and companies find it difficult to continuously assess and validate feature value. In this paper, we explore the data collection practices in five software development companies. We introduce a model that allows continuous re-prioritization of features. Our model advocates a development approach in which requirements are viewed as hypotheses that need to be continuously validated, and where customer feedback is used to continuously re-prioritize feature content. We identify how the model helps companies transition from early specification of requirements towards continuous re-prioritization of hypotheses.

  • 45.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV).
    Bosch, Jan
    No More Bosses?: A multi-case study on the emerging use of non-hierarchical principles in large-scale software development2016Ingår i: Product-focused software process improvement: 17th international conference PROFES 2016, Springer, 2016, s. 86-101Konferensbidrag (Refereegranskat)
  • 46.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Teknik och samhälle.
    Bosch, Jan
    Post-deployment Data Collection in Software-Intensive Embedded Products2013Ingår i: Software Business: From Physical Products to Software Services and Solutions, Springer, 2013, s. 79-89Konferensbidrag (Refereegranskat)
    Abstract [en]

    To stay competitive, software development companies need to constantly evolve their software development practices. Companies that succeed in shortening customer feedback loops, minimizing the time between customer proof points and learn from customer usage data will be able to accelerate innovation and improve the accuracy of their development investments. While contemporary research reports on a number of well-established techniques for actively involving customers before and during development, there is less evidence on how to successfully use post-deployment customer data as input to the development process. As a result, companies invest significantly in development efforts without having an accurate way of continuously validating whether the functionality they develop is of direct value to customers once the product is taken into use. In this paper, we explore techniques for involving customers and for collecting customer data in pre-development, during development and in the post-deployment phase of software development. We do so by studying three software development companies involved in large-scale development of embedded software. We present an inventory of the techniques they use for collecting customer feedback and we outline the key opportunities for more effective development and evolution based on post-deployment data collection.

  • 47.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV). Malmö högskola, Internet of Things and People (IOTAP).
    Bosch, Jan
    Self-Learning, Self-Actuation and Decentralized Control: How Emergent System Capabilities Change Software Development2016Ingår i: Proceedings of the 2nd edition of Swedish Workshop on the Engineering of Systems of Systems(SWESOS 2016), Department of computer science and engineering, Chalmers; University of Gothenburg , 2016, s. 30-33Konferensbidrag (Refereegranskat)
    Abstract [en]

    With recent and rapid advances in areas such as online games, embedded systems and Internet of Things,the traditional notion of what constitutes a system is fundamentally changing.Similarly to Systems of Systems (SoS) these systems are heterogeneous, autonomous and allow dynamic and emergent configurations that evolve and adjust over time. Also, these systems allow automated optimization of system performance.Regarded as the new digital business paradigm, these types of systems offer fundamentally new ways for software development companies in their service-and value creation. At the same time, they present challenges in these organizations. In this paper, and based on multiple case study research in three different domains, we identify emergent system characteristics that pose new challenges on software development and we outline the transition towards new ways-of-working in software development.

  • 48.
    Olsson Holmström, Helena
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Singing the Praise of Empowerment: Or Paying the Cost of Chaos2018Ingår i: Proceedings of the EUROMICRO Conference, IEEE, 2018, s. 17-21Konferensbidrag (Refereegranskat)
    Abstract [en]

    Empowerment is based on the belief that employees have the ability, and the desire, to shoulder more responsibility and perform better when given freedom. In an empowered organization, authority is given to employees with the intent to increase responsiveness to customers, improve decision-making power and to increase team motivation and skills. However, while most studies picture empowerment as the "ideal state" and the place where all organizations strive to be, our research shows that fully empowered teams without strategic guidance suffer from a number of problems. Based on multi-case study research in eleven software-intensive companies, we see that companies need to allow for different levels of empowerment depending on what they aim to achieve, characteristics of the industry domain, the business model and other factors, and that strategic guidance is critical to set direction and for avoiding chaos. To help companies approach the optimal level of empowerment, we provide a framework consisting of two inter-connected models that help companies to, rather than staying in their current hierarchical structures, transition to a level of empowerment that maximizes business value and performance.

  • 49.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Strategic Ecosystem Management: A Multi-case Study in the B2B Domain2015Ingår i: Product-Focused Software Process Improvement: 16th International Conference, PROFES 2015, Bolzano, Italy, December 2-4, 2015, Proceedings, Springer, 2015, s. 3-15Konferensbidrag (Refereegranskat)
    Abstract [en]

    In today's business environment, value creation is a collaborative effort in which companies depend on a number of external stakeholders. This implies a shift towards inter-organizational relationships and dependencies between companies. In this shift, companies seek strategies for how to effectively coordinate standardization efforts, share maintenance costs, and engage in open innovation initiatives, while at the same time increase control and accelerate development of differentiating functionality. On the basis of a multi-case study in six B2B software development companies, this paper explores the challenges involved in managing different ecosystem types. Based on the 'Three Layer Product Model' [1], we distinguish between innovation ecosystems, differentiating ecosystems and commoditizing ecosystems. We outline the challenges the companies experience in managing these, and we develop a model in which we identify the characteristics of each ecosystem type. Our model helps companies manage the different ecosystems they operate in. Finally, we present a framework in which we categorize the strategies employed by the case companies depending on the competitiveness of a specific product or product category.

  • 50.
    Olsson Holmström, Helena
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Bosch, Jan
    Strategic Ecosystem Management: A multi-case study on challenges and strategies for different ecosystem types2015Ingår i: Proceedings 41st Euromicro Conference On Software Engineering and advanced applications Seaa 2015, IEEE, 2015, s. 398-401Konferensbidrag (Refereegranskat)
    Abstract [en]

    In today's business environment, value creation is a collaborative effort in which companies depend on a number of external stakeholders. This implies a shift towards inter-organizational relationships and dependencies between companies. In this shift, companies seek strategies for how to effectively coordinate standardization efforts, share maintenance costs, and engage in open innovation initiatives, while at the same time increase control and accelerate development of differentiating functionality. On the basis of a multi-case study in six B2B software development companies, this paper explores the challenges involved in managing different ecosystem types. Based on the 'Three Layer Product Model' [1], we distinguish between innovation ecosystems, differentiating ecosystems and commoditizing ecosystems. We outline the challenges the companies experience in managing these, and we develop a model in which we identify the drivers, the purpose, the stakeholders and the characteristics of each ecosystem type.

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