Increasingly complex dynamics in the software operations pose formidable software evolution challenges to the software industry. Examples of these dynamics include the globalization of software markets, the massive increase of interconnected devices worldwide with the internet of things, and the digital transformation to large-scale cyber-physical systems. To tackle these challenges, researchers and practitioners have developed impressive bodies of knowledge, including adaptive and autonomic systems, run-time models, continuous software engineering, and the practice of combining software development and operations (i.e., DevOps). Despite the tremendous strides the software engineering community has made toward managing highly dynamic systems, software-intensive industries face major challenges to match the ever-increasing pace. To cope with this rapid rate at which operational contexts for software systems change, organizations are required to automate and expedite software evolution on both the development and operations sides. The aim of our research is to develop continuous and autonomic methods, infrastructures, and tools to realize software evolution holistically. In this dissertation, we shift the prevalent autonomic computing paradigm and provide new perspectives and foci on integrating autonomic computing techniques into continuous software engineering practices, such as DevOps. Our methods and approaches are based on online experimentation and evolutionary optimization. Experimentation allows autonomic managers to make in- formed data-driven and explainable decisions and present evidence to stakeholders. As a result, autonomic managers contribute to the continuous and holistic evolution of design, configuration and deployment artifacts, providing guarantees on the validity, quality and effectiveness of enacted changes. Ultimately, our approach turns autonomic managers into online stakeholders whose contributions are subject to quality control. Our contributions are threefold. We focus on effecting long-lasting software changes through self-management, self-improvement, and self-regulation. First, we propose a framework for continuous software evolution pipelines for bridging offline and online evolution processes. Our framework’s infrastructure captures run-time changes and turns them into configuration and deployment code updates. Our functional validation on cloud infrastructure management demonstrates its feasibility and soundness. It effectively contributes to eliminate technical debt from the Infrastructure-as-Code (IAC) life cycle, allowing development teams to embrace the benefits of IAC without sacrificing existing automation. Second, we provide a comprehensive implementation for the continuous IAC evolution pipeline. Third, we design a feedback loop to conduct experimentation-driven continuous exploration of design, configuration and deployment alternatives. Our experimental validation demonstrates its capacity to enrich the software architecture with additional components, and to optimize the computing cluster’s configuration, both aiming to reduce service latency. Our feedback loop frees DevOps engineers from incremental improvements, and allows them to focus on long-term mission-critical software evolution changes. Fourth, we define a reference architecture to support short-lived and long-lasting evolution actions at run-time. Our architecture incorporates short-term and long-term evolution as alternating autonomic operational modes. This approach keeps internal models relevant over prolonged system operation, thus reducing the need for additional maintenance. We demonstrate the usefulness of our research in case studies that guide the designs of cloud management systems and a Colombian city transportation system with historical data. In summary, this dissertation presents a new approach on how to manage software continuity and continuous software improvement effectively. Our methods, infrastructures, and tools constitute a new platform for short-term and long-term continuous integration and software evolution strategies and processes for large-scale intelligent cyber-physical systems. This research is a significant contribution to the long-standing challenges of easing continuous integration and evolution tasks across the development-time and run-time boundary. Thus, we expand the vision of autonomic computing to support software engineering processes from development to production and back. This dissertation constitutes a new holistic approach to the challenges of continuous integration and evolution that strengthens the causalities in current processes and practices, especially from execution back to planning, design, and development. / Graduate

Abstract Continuous software engineering (CSE) has instigated academic debate regarding the rapid, parallel cycles of releasing software and customer experimentation. This approach, originating from Web 2.0 and the software-as-a-service domain, is widely recognised among software-intensive companies today. Earlier studies have indicated some challenges in the use of CSE, especially in the context of business-to-business and product-oriented, embedded systems development. Consequently, research must address more explicit definitions and theoretical models for analysing the prerequisites and organisational capabilities related to the use of CSE. This dissertation investigates various approaches to conducting empirical evaluations related to CSE. The study aims to improve existing models of CSE and to empirically validate them in the context of software companies. The study also aims to accumulate knowledge regarding the use of CSE, as well as its impacts. The case study method is applied for the collection and analysis of empirical data. Twenty-seven interviews are conducted at five companies. In addition, a systematic literature review is used to synthesise the empirical research on agile release engineering practices. Design science research is used to portray the model design and the evaluation process of this dissertation. Three approaches for evaluating CSE are constructed: (1) LESAT for software focuses on enterprise transformation using an organisational self-assessment approach, (2) STH+ extends the “Stairway to Heaven” model and evaluates company practices with respect to evolutionary steps towards continuous experimentation-driven development, and (3) CRUSOE defines 7 key areas and 14 diagnostic questions related to the product-intensive software development ecosystem, strategy, architecture, and organisation, as well as their continuous interdependencies. This dissertation states the relevance of CSE in the context of product-intensive software development. However, more adaptations are anticipated in practices that involve business and product development stakeholders, as well as company external stakeholders. / Tiivistelmä Jatkuva ohjelmistotuotanto on herättänyt keskustelua nopeasta, samanaikaisesta ohjelmistojulkaisemisesta ja asiakaskokeiluista. Toimintatapa on peräisin Web 2.0 ja software-as-a-service yhteydestä, mutta se tunnetaan nykyään yleisesti ohjelmistoja kehittävissä yrityksissä. Aiemmat tutkimukset ovat osoittaneet haasteita jatkuvan ohjelmistotuotannon käytössä. Erityisesti haasteita on havaittu yritykseltä yritykselle liiketoiminnassa ja tuotepainotteisten sulautettujen järjestelmien yhteydessä. Näin ollen on havaittu tarve tutkimuksen avulla kehittää täsmällisempiä määritelmiä ja teoreettisia malleja, joilla voidaan analysoida jatkuvan ohjelmistotuotannon käyttöön liittyviä edellytyksiä ja organisaatioiden kyvykkyyksiä. Tässä väitöskirjassa tutkitaan malleja, joilla voidaan empiirisesti arvioida jatkuvaa ohjelmistotuotantoa. Tutkimuksella pyritään parantamaan nykyisiä malleja ja arvioimaan niiden käyttöä ohjelmistoyrityksissä. Lisäksi tutkimuksella pyritään kasvattamaan tietoa jatkuvasta ohjelmistotuotannosta ja sen vaikutuksista. Tiedon keräämiseen ja analysointiin käytettiin tapaustutkimus menetelmää. Kaksikymmentäseitsemän haastattelua tehtiin viidessä yrityksessä. Lisäksi tehtiin ketterään ohjelmistojulkaisuun keskittyvä systemaattinen kirjallisuuskatsaus. Väitöskirjassa käytetään Design Science Research menetelmää kuvaamaan tutkimuksen eri vaiheita, joissa malleja suunniteltiin ja arvioitiin. Tutkimuksessa rakennettiin kolme tapaa jatkuvan ohjelmistotuotannon arvioimista varten: (1) LESAT for Software keskittyy organisaation muutoskyvykkyyden arviointiin käyttäen itsearviointimenetelmää, (2) STH+, laajentaa ”Stairway to Heaven” mallia ja arvioi yrityksen käytäntöjä eri evoluutioaskelmilla matkalla kohti kokeilupainotteista tuotekehitystä, (3) CRUSOE määrittelee seitsemän pääaluetta ja 14 kysymystä liittyen tuotekehityksen ekosysteemiin, strategiaan, arkkitehtuuriin, organisointiin sekä näiden välisiin jatkuviin riippuvuuksiin. Väitöskirja osoittaa jatkuvan ohjelmistokehityksen olevan merkityksellinen myös tuotepainotteisessa ohjelmistokehityksessä. Nähtävissä kuitenkin on, että useita nykykäytäntöjä on tarvetta muokata. Erityisesti muokkaustarvetta on tuotekehityksen ja liiketoiminnan sidosryhmiin ja yrityksen ulkoisiin sidosryhmiin liittyvissä käytännöissä.