Navigating the academic Swedish software engineering landscape can be difficult. As a Swedsoft activity, I created Swe-SE-SCI to list all Swedish Software Engineering (SE) scholars with permanent positions at Swedish non-profit research organizations. The ambition is to maintain an index of all Swedish SE scholars with first-authored publications in SCI-listed SE journals, i.e., “SSS scholars”. Swe-SE-SCI mines DBLP publication lists to identify typical research topics of Swedish SE research organizations and apparent research interests of SSS scholars.
A reliable and updated index of academic SE in Sweden could bring several benefits. The primary goal is to constitute a gateway for industry to find expertise among researchers – hopefully supporting knowledge transfer, industry-academia collaboration, and more relevant research. Swe-SE-SCI can also be used to find academic partners in new research projects and suitable PhD committee members. The index can also help news media find experts when comments on specific topics are needed.
Affiliations are ranked by the number of first-authored SCI publications by SSS scholars. Individual SSS scholars are ranked by their SSS rating – our in-house metric. In contrast to non-decreasing citation-based metrics, the SSS rating fluctuates as it promotes active research with a focus to publish in SCI-listed SE journals. A detailed description is available at the bottom of this page.
August 2020 – Swe-SE-SCI
The Swe-SE-SCI index shows that the top-5 SE research organizations are BTH, Chalmers/Gothenburg, Lund University, RISE, and KTH.
Looking at individual SSS scholars, familiar full professors top the list. We also find some new names in Sweden (Felderer and Baudry) as well as some emerging top scholars.
August update: Added missing SSS scholar: Mira Kajko-Mattsson, KTH. One new “signature work”: When to update systematic literature reviews in software engineering. (J. Syst. Softw.) by Mendes et al.
| Affiliation | #SSS scholars | #SCI publications | Research topics | |
|---|---|---|---|---|
| Blekinge Institute of Technology | 18 | 92 | Topic 1: development effort management improve teaching industry analysis; Topic 2: empirical systematic company global practice agile data; Topic 3: requirements test process projects knowledge risk framework; Topic 4: quality models cost decision applications literature scale; Topic 5: web testing estimation industrial model product project | |
| Chalmers / Gothenburg University | 20 | 55 | Topic 1: modeling design analysis data measurement service challenges; Topic 2: systems model product component variability architecture open; Topic 3: development test evolution support automated systematic testing; Topic 4: industrial quality sustainability ecosystems empirical large process; Topic 5: requirements models management lines embedded code supporting | |
| Lund University | 7 | 26 | Topic 1: product risk project analysis methods academia support; Topic 2: regression line large systematic practices method design; Topic 3: testing test model distances language source framework; Topic 4: development management attribute selection effects quality process; Topic 5: requirements open grammars processes scale evidence extreme | |
| RISE Research Institutes of Sweden | 10 | 19 | Topic 1: time model artificial making mapping trees tools; Topic 2: systems architecture decision service traceability architecting insurance; Topic 3: models framework impact neural architectural quality electronic; Topic 4: cost analysis development embedded real cyber defect; Topic 5: estimation automotive enterprise networks safety open fuzzy | |
| KTH Royal Institute of Technology | 7 | 18 | Topic 1: analysis enterprise process checking networked java design; Topic 2: corrective agile automated verification method critical models; Topic 3: management test cm3 vulnerability framework eliciting evaluating; Topic 4: model maintenance systems testing problem automatic network; Topic 5: architecture modeling theory probabilistic attacks risk business | |
| Mälardalen University | 6 | 15 | Topic 1: analysis time development models mixed messages network; Topic 2: systems component response vehicular controller area modelling; Topic 3: model end safety timing process applications complex; Topic 4: modeling industrial systematic tool assessment compliant critical; Topic 5: embedded distributed uml reuse code lines framework | |
| Linneaus Univerity | 5 | 9 | Topic 1: systems antipatterns adaptive pervasive control modeling response; Topic 2: physical management soa resilience networking time decentralized; Topic 3: detection middleware model context work performance wireless; Topic 4: design patterns security specification applications surveillance modelling; Topic 5: service analysis self formal critical resource subscribe | |
| Skövde University | 3 | 6 | Topic 1: model companies mutants openness projects alignment; Topic 2: systems tool models biological maintenance organisational; Topic 3: experiences swedish time involvement mutation fork; Topic 4: open source standards development organisations embedded; Topic 5: method perceptions long analysis term interoperability | |
| Linköping University | 3 | 5 | Topic 1: dynamic interprocedural languages tools programs; Topic 2: slicing object modelica equation algorithmic; Topic 3: language incremental development physical testing; Topic 4: debugging modeling environment parallel openmodelica | |
| Karlstad University | 2 | 5 | Topic 1: kanban testing combinatorial aware; Topic 2: swarm generation test mapping; Topic 3: interaction systematic development particle | |
| Malmö University | 2 | 3 | Topic 1: data embedded; Topic 2: ecosystem embedded | |
| Örebro University | 1 | 3 | Topic 1: requirements prioritization distribution; Topic 2: framework compositional phase; Topic 3: analysis data component | |
| Stockholm University | 1 | 1 | Topic 1: services frameworks governance flexible; Topic 2: business capability service organizations; Topic 3: requirements processes modeling enterprise | |
| Jönköping University | 1 | 1 | Topic 1: learning end license; Topic 2: spyware agreements license; Topic 3: user spyware agreements |
| Scholar | Affiliation | SSS rating | Apparent research interests | |
|---|---|---|---|---|
| Claes Wohlin | Blekinge Institute of Technology | 63.2 | empirical, project, success, journals, factors, analysis, methods, reliability, systematic, data | |
| Jan Bosch | Chalmers / Gothenburg University | 53.52 | product, architecture, lines, ecosystems, object, variability, families, development, data, component | |
| Per Runeson | Lund University | 36.8 | testing, test, unit, open, industry, inspection, collaboration, academia, product, detection | |
| Emilia Mendes | Blekinge Institute of Technology | 33.35 | web, effort, estimation, company, applications, cost, hypermedia, bayesian, improve, value | |
| Benoit Baudry | KTH Royal Institute of Technology | 29.31 | test, model, testability, design, automatic, testing, genetic, validation, optimization, improving | |
| Tony Gorschek | Blekinge Institute of Technology | 26.56 | requirements, model, empirical, product, process, management, transfer, practice, abstraction, development | |
| Robert Feldt | Chalmers / Gothenburg University | 24.74 | test, search, genetic, programming, diverse, diversity, empirical, cases, versions, testing | |
| Miroslaw Staron | Chalmers / Gothenburg University | 23.53 | measurement, industrial, development, systems, large, projects, model, defect, method, measures | |
| Björn Regnell | Lund University | 22.99 | requirements, quality, model, mobile, scale, testing, large, domain, scenario, reqt | |
| Michael Felderer | Blekinge Institute of Technology | 21.57 | testing, risk, security, test, industrial, defect, system, requirements, systems, results | |
| Krzysztof Wnuk | Blekinge Institute of Technology | 20.92 | requirements, decision, management, scoping, large, scale, industrial, open, visualization, innovation | |
| Martin Monperrus | KTH Royal Institute of Technology | 20.83 | model, measurement, automated, automatic, system, repair, modèles, detecting, calls, surveillance | |
| Martin Höst | Lund University | 18.45 | product, source, processes, development, management, project, open, commercial, systematic, knowledge | |
| Jürgen Börstler | Blekinge Institute of Technology | 17.71 | teaching, role, object, play, learning, concepts, projects, programs, pedagogies, programmieren | |
| Ivica Crnkovic | Chalmers / Gothenburg University | 16.75 | component, systems, development, embedded, scm, process, components, management, change, predictability | |
| Daniel Méndez Fernández | Blekinge Institute of Technology | 15.94 | requirements, artefact, naming, pain, practice, results, germany, improvement, first, design | |
| Darja Smite | Blekinge Institute of Technology | 15.26 | global, development, learned, lessons, offshoring, coordination, cost, evidence, empirical, agile | |
| Mikael Svahnberg | Blekinge Institute of Technology | 14.61 | quality, architecture, attributes, product, architectures, method, requirements, consensus, building, identifying | |
| Eric Knauss | Chalmers / Gothenburg University | 13.8 | requirements, continuous, supporting, clarification, anforderungen, agile, system, ecosystems, feedback, heuristic | |
| Markus Borg | RISE Research Institutes of Sweden | 13.71 | traceability, impact, reports, analysis, information, issue, change, context, bug, time | |
| Patrizio Pelliccione | Chalmers / Gothenburg University | 12.79 | systems, cars, framework, specifications, architectural, component, evolution, beyond, chairs, sequences | |
| Efi Papatheocharous | RISE Research Institutes of Sweden | 12.65 | cost, estimation, decision, artificial, fuzzy, neural, networks, development, agile, systems | |
| Federico Ciccozzi | Mälardalen University | 11.96 | systems, model, uml, embedded, models, code, generation, execution, modelling, complex | |
| Gregory Gay | Chalmers / Gothenburg University | 11.94 | test, generation, real, coverage, search, model, program, automated, faults, steering | |
| Emelie Engström | Lund University | 11.54 | test, regression, testing, line, product, selection, systematic, empirical, industrial, taxonomy | |
| Wasif Afzal | Mälardalen University | 10.28 | systematic, runtime, testing, fault, megamodelling, complex, systems, framework, megam, test | |
| Michael Unterkalmsteiner | Blekinge Institute of Technology | 10.15 | requirements, improvement, process, alignment, test, systematic, retrieval, scale, measurement, literature | |
| Nauman Bin Ali | Blekinge Institute of Technology | 10.08 | systematic, simulation, search, literature, industrial, process, reviews, testing, assisted, industry | |
| Regina Hebig | Chalmers / Gothenburg University | 10.05 | model, evolution, development, mde, languages, processes, transformation, xtend, complex, impact | |
| Richard Berntsson-Svensson | Chalmers / Gothenburg University | 9.9 | requirements, quality, quper, practice, industrial, companies, model, creativity, techniques, investigation | |
| Jennifer Horkoff | Chalmers / Gothenburg University | 9.35 | goal, modeling, requirements, analysis, interactive, models, model, systematic, enterprise, experiences | |
| Riccardo Scandariato | Chalmers / Gothenburg University | 9.29 | security, design, learned, distributed, networks, securechange, automated, logical, systems, lifelong | |
| Björn Lundell | Skövde University | 9.17 | open, source, tool, method, standards, swedish, perceptions, systems, experiences, companies | |
| Elizabeth Bjarnason | Lund University | 8.89 | requirements, distances, development, evidence, practices, cases, gaps, method, large, timelines | |
| Davide Fucci | Blekinge Institute of Technology | 8.75 | test, development, replication, effects, sleep, first, external, requirements, conformance, impact | |
| Mauro Caporuscio | Linneaus Univerity | 8.34 | service, middleware, applications, pervasive, systems, networking, time, run, subscribe, performance | |
| Pontus Johnson | KTH Royal Institute of Technology | 8.33 | analysis, architecture, theory, modeling, probabilistic, enterprise, general, business, extended, attack | |
| Antonio Cicchetti | Mälardalen University | 8.08 | model, evolution, web, development, systems, applications, view, models, weaving, managing | |
| Panagiota Chatzipetrou | Örebro University | 7.97 | analysis, component, framework, data, statistical, requirements, prioritization, goals, attributes, effort | |
| Thorsten Berger | Chalmers / Gothenburg University | 7.92 | variability, modeling, feature, management, systems, efficiency, domain, large, industry, models | |
| Fabian Fagerholm | Blekinge Institute of Technology | 7.74 | projects, agile, education, experience, continuous, patterns, lean, onboarding, developers, source | |
| Mira Kajko-Mattsson | KTH Royal Institute of Technology | 7.61 | maintenance, model, management, process, problem, corrective, cm3, agile, maturity, eliciting | |
| Philipp Leitner | Chalmers / Gothenburg University | 7.57 | service, services, cloud, violations, level, web, testing, performance, practice, compositions | |
| Emil Alégroth | Blekinge Institute of Technology | 7.35 | testing, gui, visual, industrial, practice, test, empirical, debt, testware, automated | |
| Birgit Penzenstadler | Chalmers / Gothenburg University | 7.29 | sustainability, requirements, systems, design, model, domain, systematic, green, automotive, system | |
| Jakob Axelsson | RISE Research Institutes of Sweden | 7.18 | systems, system, time, embedded, real, architecting, automotive, analysis, hardware, architectural | |
| Ulrik Franke | RISE Research Institutes of Sweden | 6.92 | enterprise, architecture, insurance, cyber, service, analysis, framework, availability, bayesian, trees | |
| Helena Holmström Olsson | Malmö University | 6.62 | embedded, data, ecosystem, mind, praise, telesm, online, cost, management, paying | |
| Jan-Philipp Steghöfer | Chalmers / Gothenburg University | 6.51 | systems, self, agile, organising, open, die, scrum, organic, computing, evolutionary | |
| Robert Lagerström | KTH Royal Institute of Technology | 6.32 | architecture, enterprise, systems, analysis, modifiability, cost, maintainability, metamodel, models, measuring | |
| Hannes Holm | KTH Royal Institute of Technology | 5.5 | attacks, vulnerability, system, expert, investigation, empirical, security, scanning, application, web | |
| Peter Fritzson | Linköping University | 5.17 | object, language, modeling, modelica, environment, debugging, equation, system, openmodelica, incremental | |
| Barbara Gallina | Mälardalen University | 5.17 | safety, process, reuse, lines, model, 26262, systems, iso, analysis, enabling | |
| Bestoun S. Ahmed | Karlstad University | 4.9 | testing, interaction, combinatorial, swarm, particle, systematic, aware, automated, optimization, applications | |
| Jonas Lundberg | Linneaus Univerity | 4.2 | analysis, response, resilience, design, points, air, cognitive, work, traffic, precise | |
| Ludwik Kuzniarz | Blekinge Institute of Technology | 4.06 | uml, models, model, multimedia, teaching, development, initial, modeling, domain, stereotypes | |
| Francis Palma | Linneaus Univerity | 4.06 | detection, antipatterns, specification, patterns, soa, prioritization, restful, linguistic, service, test | |
| Mariam Kamkar | Linköping University | 4.05 | slicing, dynamic, interprocedural, debugging, program, programs, applied, algorithmic, testing, preface | |
| Gul Calikli | Chalmers / Gothenburg University | 4.04 | confirmation, bias, effects, analysis, company, experience, modeling, empirical, factors, developers | |
| Lars Pareto | Chalmers / Gothenburg University | 4.0 | architectural, empirical, design, base, development, concern, projects, concerns, model, investigation | |
| Jonas Gamalielsson | Skövde University | 3.96 | open, source, standards, biological, beyond, evolutionary, communities, digital, w3c, gene | |
| Francisco Gomes de Oliveira Neto | Chalmers / Gothenburg University | 3.91 | test, support, testing, requirements, empirical, distributed, scale, tasks, evaluate, aligning | |
| Kenneth Lind | Chalmers / Gothenburg University | 3.84 | size, estimation, components, embedded, automated, code, time, real, compsize, model | |
| Deepika Badampudi | Blekinge Institute of Technology | 3.83 | systematic, knowledge, translation, decision, making, literature, oss, scale, synthesis, perspectives | |
| Thomas Olsson | RISE Research Institutes of Sweden | 3.82 | decision, gqm, making, system, language, time, quality, companies, requirements, reconfigurable | |
| Jelena Zdravkovic | Stockholm University | 3.79 | business, capability, service, processes, requirements, modeling, governance, enterprise, services, frameworks | |
| Birgitta Lindström | Skövde University | 3.79 | mutants, mutation, time, real, strong, systems, dynamic, aspect, subsuming, testability | |
| Javier Gonzalez-Huerta | Blekinge Institute of Technology | 3.74 | product, architecture, derivation, multimodel, validating, model, improvement, models, quality, integrating | |
| Kristian Sandahl | Linköping University | 3.53 | participation, inspections, replication, expert, knowledge, active, assessing, systems, developing, methods | |
| Pasqualina Potena | RISE Research Institutes of Sweden | 3.37 | tradeoff, functional, attributes, optimization, service, directions, architecture, quality, composition, systems | |
| Görel Hedin | Lund University | 3.33 | attribute, grammars, programming, preface, extreme, jastadd, object, languages, incremental, design | |
| Imed Hammouda | Chalmers / Gothenburg University | 3.14 | open, source, patterns, design, concern, pattern, development, communities, systems, sustainable | |
| Saad Mubeen | Mälardalen University | 3.03 | analysis, time, systems, end, embedded, response, timing, component, distributed, vehicular | |
| Niklas Lavesson | Jönköping University | 2.99 | learning, end, user, agreements, license, spyware, approve, online, rule, inducer | |
| Narges Khakpour | Linneaus Univerity | 2.81 | systems, self, adaptive, formal, behavioral, synthesis, control, modeling, structural, analysis | |
| Muhammad Ovais Ahmad | Karlstad University | 2.75 | kanban, development, agile, systematic, companies, lean, empirical, transition, practices, management | |
| Christin Lindholm | Lund University | 2.57 | risk, development, medical, device, analysis, process, management, perspective, identification, testing | |
| Ana Magazinius | RISE Research Institutes of Sweden | 2.55 | estimation, cost, distortional, distortions, organizational, effects, bounty, complexity, confirming, exploring | |
| Patrik Berander | Malmö University | 2.53 | requirements, prioritization, cumulative, hierarchies, hierarchical, voting, two, efficient, measurement, management | |
| Cyrille Artho | KTH Royal Institute of Technology | 2.5 | model, checking, testing, analysis, networked, java, static, test, applications, programs | |
| Niklas Mellegård | RISE Research Institutes of Sweden | 1.47 | defect, automotive, weight, improving, impact, efficiency, reports, initial, scheme, classification | |
| Michael Mattsson | Blekinge Institute of Technology | 1.45 | framework, industrial, solutions, experience, application, frameworks, causes, evolving, evolution, paper | |
| Daniel Flemström | Mälardalen University | 1.33 | test, guarded, passive, assertions, interactive, saga, natural, prioritization, reuse, cases | |
| Francesco Flammini | Linneaus Univerity | 1.32 | systems, critical, security, surveillance, modelling, infrastructure, infrastructures, multiformalism, physical, repairable | |
| Peter Wallin | RISE Research Institutes of Sweden | 1.27 | development, related, system, issues, vehicles, architecting, architectures, architecture, heavy, automotive | |
| Stefan Cedergren | RISE Research Institutes of Sweden | 1.0 | products, performance, development, evaluating |
| Scholar | Affiliation | SSS rating | Signature SSS works | |
|---|---|---|---|---|
| Claes Wohlin | Blekinge Institute of Technology | 63.2 | 2015: Towards a decision-making structure for selecting a research design in empirical software engineering. (Empirical Software Engineering) 2015: A general theory of software engineering: Balancing human, social and organizational capitals. (J. Syst. Softw.) 2013: Systematic literature reviews in software engineering. (Inf. Softw. Technol.) 2013: On the reliability of mapping studies in software engineering. (J. Syst. Softw.) 2011: Taking novelty to a new level. (Inf. Softw. Technol.) 2009: An analysis of the most cited articles in software engineering journals – 2002. (Inf. Softw. Technol.) 2008: An analysis of the most cited articles in software engineering journals – 2001. (Inf. Softw. Technol.) 2007: Most cited journal articles in software engineering. (Inf. Softw. Technol.) 2007: An analysis of the most cited articles in software engineering journals – 2000. (Inf. Softw. Technol.) 2005: Most cited journal articles in software engineering. (Inf. Softw. Technol.) 2005: An analysis of the most cited articles in software engineering journals – 1999. (Inf. Softw. Technol.) 2004: Are Individual Differences in Software Development Performance Possible to Capture Using a Quantitative Survey?. (Empirical Software Engineering) 2003: Prioritizing and Assessing Software Project Success Factors and Project Characteristics using Subjective Data. (Empirical Software Engineering) 2001: Assessing Project Success Using Subjective Evaluation Factors. (Softw. Qual. J.) 2000: Subjective evaluation as a tool for learning from software project success. (Inf. Softw. Technol.) 1999: Strategies for industrial relevance in software engineering education. (J. Syst. Softw.) 1995: Soft factors and their impact on time to market. (Softw. Qual. J.) 1995: An Experimental Evaluation of Capture-Recapture in Software Inspections. (Softw. Test. Verification Reliab.) 1994: Certification of Software Components. (IEEE Trans. Software Eng.) | |
| Jan Bosch | Chalmers / Gothenburg University | 53.52 | 2018: Ecosystem traps and where to find them. (J. Softw. Evol. Process.) 2012: Software ecosystems: Taking software development beyond the boundaries of the organization. (J. Syst. Softw.) 2011: Introducing agile customer-centered development in a legacy software product line. (Softw. Pract. Exp.) 2010: From integration to composition: On the impact of software product lines, global development and ecosystems. (J. Syst. Softw.) 2003: Software architecture – Engineering quality attributes. (J. Syst. Softw.) 1999: Superimposition: a component adaptation technique. (Inf. Softw. Technol.) | |
| Per Runeson | Lund University | 36.8 | 2014: Variation factors in the design and analysis of replicated controlled experiments – Three (dis)similar studies on inspections versus unit testing. (Empirical Software Engineering) 2009: Guidelines for conducting and reporting case study research in software engineering. (Empirical Software Engineering) 2003: Test processes in software product evolution – a qualitative survey on the state of practice. (J. Softw. Maintenance Res. Pract.) 1998: An Experimental Evaluation of an Experience-Based Capture-Recapture Method in Software Code Inspections. (Empirical Software Engineering) | |
| Emilia Mendes | Blekinge Institute of Technology | 33.35 | 2020: When to update systematic literature reviews in software engineering. (J. Syst. Softw.) 2018: Towards improving decision making and estimating the value of decisions in value-based software engineering: the VALUE framework. (Softw. Qual. J.) 2008: Replicating studies on cross- vs single-company effort models using the ISBSG Database. (Empirical Software Engineering) 2008: Cross-company vs. single-company web effort models using the Tukutuku database: An extended study. (J. Syst. Softw.) 2008: Bayesian Network Models for Web Effort Prediction: A Comparative Study. (IEEE Trans. Software Eng.) 2005: Investigating Web size metrics for early Web cost estimation. (J. Syst. Softw.) 2003: A Comparative Study of Cost Estimation Models for Web Hypermedia Applications. (Empirical Software Engineering) 1998: Reusability and maintainability in hypermedia applications for education. (Inf. Softw. Technol.) | |
| Benoit Baudry | KTH Royal Institute of Technology | 29.31 | 2005: Measuring design testability of a UML class diagram. (Inf. Softw. Technol.) 2005: From genetic to bacteriological algorithms for mutation-based testing. (Softw. Test. Verification Reliab.) | |
| Tony Gorschek | Blekinge Institute of Technology | 26.56 | 2014: On the use of software design models in software development practice: An empirical investigation. (J. Syst. Softw.) 2012: Introduction of a process maturity model for market-driven product management and requirements engineering. (J. Softw. Maintenance Res. Pract.) 2008: Requirements engineering: In search of the dependent variables. (Inf. Softw. Technol.) 2007: A controlled empirical evaluation of a requirements abstraction model. (Inf. Softw. Technol.) 2006: Requirements Abstraction Model. (Requir. Eng.) 2004: Packaging software process improvement issues: a method and a case study. (Softw. Pract. Exp.) | |
| Robert Feldt | Chalmers / Gothenburg University | 24.74 | 2010: Links between the personalities, views and attitudes of software engineers. (Inf. Softw. Technol.) | |
| Miroslaw Staron | Chalmers / Gothenburg University | 23.53 | 2018: Industrial experiences from evolving measurement systems into self-healing systems for improved availability. (Softw. Pract. Exp.) 2016: MeSRAM – A method for assessing robustness of measurement programs in large software development organizations and its industrial evaluation. (J. Syst. Softw.) 2012: Critical role of measures in decision processes: Managerial and technical measures in the context of large software development organizations. (Inf. Softw. Technol.) 2011: Developing measurement systems: an industrial case study. (J. Softw. Maintenance Res. Pract.) 2010: A method for forecasting defect backlog in large streamline software development projects and its industrial evaluation. (Inf. Softw. Technol.) 2009: A framework for developing measurement systems and its industrial evaluation. (Inf. Softw. Technol.) 2008: Predicting weekly defect inflow in large software projects based on project planning and test status. (Inf. Softw. Technol.) 2006: Empirical assessment of using stereotypes to improve comprehension of UML models: A set of experiments. (J. Syst. Softw.) | |
| Björn Regnell | Lund University | 22.99 | 2001: An Industrial Case Study on Distributed Prioritisation in Market-Driven Requirements Engineering for Packaged Software. (Requir. Eng.) 2000: Are the Perspectives Really Different? – Further Experimentation on Scenario-Based Reading of Requirements. (Empirical Software Engineering) 2000: Towards integration of use case modelling and usage-based testing. (J. Syst. Softw.) | |
| Michael Felderer | Blekinge Institute of Technology | 21.57 | 2019: Comprehensibility of system models during test design: a controlled experiment comparing UML activity diagrams and state machines. (Softw. Qual. J.) 2016: Risk orientation in software testing processes of small and medium enterprises: an exploratory and comparative study. (Softw. Qual. J.) 2016: Model-based security testing: a taxonomy and systematic classification. (Softw. Test. Verification Reliab.) 2015: Manual test case derivation from UML activity diagrams and state machines: A controlled experiment. (Inf. Softw. Technol.) 2014: Integrating risk-based testing in industrial test processes. (Softw. Qual. J.) | |
| Krzysztof Wnuk | Blekinge Institute of Technology | 20.92 | 2016: Supporting Scope Tracking and Visualization for Very Large-Scale Requirements Engineering-Utilizing FSC+, Decision Patterns, and Atomic Decision Visualizations. (IEEE Trans. Software Eng.) 2015: Exploring factors affecting decision outcome and lead time in large-scale requirements engineering. (J. Softw. Evol. Process.) 2014: Bridges and barriers to hardware-dependent software ecosystem participation – A case study. (Inf. Softw. Technol.) 2013: Obsolete software requirements. (Inf. Softw. Technol.) 2012: Replication of an experiment on linguistic tool support for consolidation of requirements from multiple sources. (Empirical Software Engineering) | |
| Martin Monperrus | KTH Royal Institute of Technology | 20.83 | 2013: Automated measurement of models of requirements. (Softw. Qual. J.) 2013: Detecting missing method calls as violations of the majority rule. (ACM Trans. Softw. Eng. Methodol.) 2012: What should developers be aware of? An empirical study on the directives of API documentation. (Empirical Software Engineering) 2011: Model-driven generative development of measurement software. (Software and Systems Modeling) | |
| Martin Höst | Lund University | 18.45 | 2011: A systematic review of research on open source software in commercial software product development. (Inf. Softw. Technol.) 2001: Exploring bottlenecks in market-driven requirements management processes with discrete event simulation. (J. Syst. Softw.) 2000: Using Students as Subjects-A Comparative Study of Students and Professionals in Lead-Time Impact Assessment. (Empirical Software Engineering) 2000: Evaluation of code review methods through interviews and experimentation. (J. Syst. Softw.) 1997: A subjective effort estimation experiment. (Inf. Softw. Technol.) | |
| Jürgen Börstler | Blekinge Institute of Technology | 17.71 | 2016: Beauty and the Beast: on the readability of object-oriented example programs. (Softw. Qual. J.) 2016: The Role of Method Chains and Comments in Software Readability and Comprehension – An Experiment. (IEEE Trans. Software Eng.) 1995: Integrated software reuse: Management and techniques : Paul Walton and Neil Maiden (eds) Ashgate Publishing, Hants, UK (1993) 178 pp 49.50 hardcover ISBN 1 85742 146 9. (Inf. Softw. Technol.) | |
| Ivica Crnkovic | Chalmers / Gothenburg University | 16.75 | 2011: A Classification Framework for Software Component Models. (IEEE Trans. Software Eng.) 2005: Automated Component-Based Software Engineering. (J. Syst. Softw.) 2002: Challenges of component-based development. (J. Syst. Softw.) | |
| Daniel Méndez Fernández | Blekinge Institute of Technology | 15.94 | 2019: Empirical software engineering: From discipline to interdiscipline. (J. Syst. Softw.) 2019: Artefacts in software engineering: a fundamental positioning. (Software and Systems Modeling) 2017: Naming the pain in requirements engineering – Contemporary problems, causes, and effects in practice. (Empirical Software Engineering) 2015: Naming the pain in requirements engineering: A design for a global family of surveys and first results from Germany. (Inf. Softw. Technol.) 2015: Artefact-based requirements engineering: the AMDiRE approach. (Requir. Eng.) 2012: Field study on requirements engineering: Investigation of artefacts, project parameters, and execution strategies. (Inf. Softw. Technol.) | |
| Darja Smite | Blekinge Institute of Technology | 15.26 | 2017: Software teams and their knowledge networks in large-scale software development. (Inf. Softw. Technol.) 2014: An empirically based terminology and taxonomy for global software engineering. (Empirical Software Engineering) 2013: Offshore insourcing in software development: Structuring the decision-making process. (J. Syst. Softw.) 2012: Lessons learned from transferring software products to India. (J. Softw. Evol. Process.) 2010: Empirical evidence in global software engineering: a systematic review. (Empirical Software Engineering) | |
| Mikael Svahnberg | Blekinge Institute of Technology | 14.61 | 2017: A model for assessing and re-assessing the value of software reuse. (J. Softw. Evol. Process.) 2015: Uni-REPM: a framework for requirements engineering process assessment. (Requir. Eng.) 2013: Uni-REPM: validated and improved. (Requir. Eng.) 2010: A systematic review on strategic release planning models. (Inf. Softw. Technol.) 2007: Six years of evaluating software architectures in student projects. (J. Syst. Softw.) 2005: An Investigation of a Method for Identifying a Software Architecture Candidate with Respect to Quality Attributes. (Empirical Software Engineering) 2005: A taxonomy of variability realization techniques. (Softw. Pract. Exp.) 2004: An industrial study on building consensus around software architectures and quality attributes. (Inf. Softw. Technol.) 1999: Evolution in software product lines: two cases. (J. Softw. Maintenance Res. Pract.) | |
| Eric Knauss | Chalmers / Gothenburg University | 13.8 | 2018: Continuous clarification and emergent requirements flows in open-commercial software ecosystems. (Requir. Eng.) 2015: Patterns of continuous requirements clarification. (Requir. Eng.) | |
| Markus Borg | RISE Research Institutes of Sweden | 13.71 | 2019: Selecting component sourcing options: A survey of software engineering’s broader make-or-buy decisions. (Inf. Softw. Technol.) 2017: Supporting Change Impact Analysis Using a Recommendation System: An Industrial Case Study in a Safety-Critical Context. (IEEE Trans. Software Eng.) 2016: TuneR: a framework for tuning software engineering tools with hands-on instructions in R. (J. Softw. Evol. Process.) 2014: Recovering from a decade: a systematic mapping of information retrieval approaches to software traceability. (Empirical Software Engineering) | |
| Patrizio Pelliccione | Chalmers / Gothenburg University | 12.79 | 2009: CHARMY: A Framework for Designing and Verifying Architectural Specifications. (IEEE Trans. Software Eng.) 2008: An architectural approach to the correct and automatic assembly of evolving component-based systems. (J. Syst. Softw.) | |
| Efi Papatheocharous | RISE Research Institutes of Sweden | 12.65 | 2018: The GRADE taxonomy for supporting decision-making of asset selection in software-intensive system development. (Inf. Softw. Technol.) 2017: An investigation of effort distribution among development phases: A four-stage progressive software cost estimation model. (J. Softw. Evol. Process.) 2014: Empirical evidence and state of practice of software agile teams. (J. Softw. Evol. Process.) | |
| Federico Ciccozzi | Mälardalen University | 11.96 | 2019: Execution of UML models: a systematic review of research and practice. (Software and Systems Modeling) 2018: On the automated translational execution of the action language for foundational UML. (Software and Systems Modeling) 2018: Architecture optimization: speed or accuracy? both! (Softw. Qual. J.) 2016: Explicit connection patterns (ECP) profile and semantics for modelling and generating explicit connections in complex UML composite structures. (J. Syst. Softw.) 2013: Round-trip support for extra-functional property management in model-driven engineering of embedded systems. (Inf. Softw. Technol.) | |
| Gregory Gay | Chalmers / Gothenburg University | 11.94 | 2017: Automated Steering of Model-Based Test Oracles to Admit Real Program Behaviors. (IEEE Trans. Software Eng.) 2016: The Effect of Program and Model Structure on the Effectiveness of MC/DC Test Adequacy Coverage. (ACM Trans. Softw. Eng. Methodol.) 2015: The Risks of Coverage-Directed Test Case Generation. (IEEE Trans. Software Eng.) 2015: Automated Oracle Data Selection Support. (IEEE Trans. Software Eng.) 2010: Finding robust solutions in requirements models. (Autom. Softw. Eng.) 2010: Automatically finding the control variables for complex system behavior. (Autom. Softw. Eng.) | |
| Emelie Engström | Lund University | 11.54 | 2020: How software engineering research aligns with design science: a review. (Empirical Software Engineering) 2017: SERP-test: a taxonomy for supporting industry-academia communication. (Softw. Qual. J.) 2013: Test overlay in an emerging software product line – An industrial case study. (Inf. Softw. Technol.) 2011: Software product line testing – A systematic mapping study. (Inf. Softw. Technol.) 2010: A systematic review on regression test selection techniques. (Inf. Softw. Technol.) | |
| Wasif Afzal | Mälardalen University | 10.28 | 2016: Software test process improvement approaches: A systematic literature review and an industrial case study. (J. Syst. Softw.) 2015: An experiment on the effectiveness and efficiency of exploratory testing. (Empirical Software Engineering) 2014: Prediction of faults-slip-through in large software projects: an empirical evaluation. (Softw. Qual. J.) 2009: A systematic review of search-based testing for non-functional system properties. (Inf. Softw. Technol.) | |
| Michael Unterkalmsteiner | Blekinge Institute of Technology | 10.15 | 2016: Large-scale information retrieval in software engineering – an experience report from industrial application. (Empirical Software Engineering) 2015: Assessing requirements engineering and software test alignment – Five case studies. (J. Syst. Softw.) 2014: A conceptual framework for SPI evaluation. (J. Softw. Evol. Process.) 2014: A taxonomy for requirements engineering and software test alignment. (ACM Trans. Softw. Eng. Methodol.) 2012: Evaluation and Measurement of Software Process Improvement – A Systematic Literature Review. (IEEE Trans. Software Eng.) | |
| Nauman Bin Ali | Blekinge Institute of Technology | 10.08 | 2019: On the search for industry-relevant regression testing research. (Empirical Software Engineering) 2019: A critical appraisal tool for systematic literature reviews in software engineering. (Inf. Softw. Technol.) 2018: Reliability of search in systematic reviews: Towards a quality assessment framework for the automated-search strategy. (Inf. Softw. Technol.) 2016: FLOW-assisted value stream mapping in the early phases of large-scale software development. (J. Syst. Softw.) 2015: Evaluation of simulation-assisted value stream mapping for software product development: Two industrial cases. (Inf. Softw. Technol.) 2014: A systematic literature review on the industrial use of software process simulation. (J. Syst. Softw.) | |
| Regina Hebig | Chalmers / Gothenburg University | 10.05 | 2017: The changing balance of technology and process: A case study on a combined setting of model-driven development and classical C coding. (J. Softw. Evol. Process.) 2017: On the complex nature of MDE evolution and its impact on changeability. (Software and Systems Modeling) 2017: Approaches to Co-Evolution of Metamodels and Models: A Survey. (IEEE Trans. Software Eng.) | |
| Richard Berntsson-Svensson | Chalmers / Gothenburg University | 9.9 | 2017: Is role playing in Requirements Engineering Education increasing learning outcome? (Requir. Eng.) 2013: An investigation of how quality requirements are specified in industrial practice. (Inf. Softw. Technol.) 2012: Setting quality targets for coming releases with QUPER: an industrial case study. (Requir. Eng.) 2012: Quality Requirements in Industrial Practice – An Extended Interview Study at Eleven Companies. (IEEE Trans. Software Eng.) | |
| Jennifer Horkoff | Chalmers / Gothenburg University | 9.35 | 2019: Creative goal modeling for innovative requirements. (Inf. Softw. Technol.) 2019: Goal-oriented requirements engineering: an extended systematic mapping study. (Requir. Eng.) 2016: Interactive goal model analysis for early requirements engineering. (Requir. Eng.) 2014: Strategic business modeling: representation and reasoning. (Software and Systems Modeling) 2013: Comparison and evaluation of goal-oriented satisfaction analysis techniques. (Requir. Eng.) | |
| Riccardo Scandariato | Chalmers / Gothenburg University | 9.29 | 2015: A descriptive study of Microsoft’s threat modeling technique. (Requir. Eng.) 2014: Predicting Vulnerable Software Components via Text Mining. (IEEE Trans. Software Eng.) | |
| Björn Lundell | Skövde University | 9.17 | 2011: Practitioner perceptions of Open Source software in the embedded systems area. (J. Syst. Softw.) 2004: Changing perceptions of CASE technology. (J. Syst. Softw.) | |
| Elizabeth Bjarnason | Lund University | 8.89 | 2019: Improving requirements-test alignment by prescribing practices that mitigate communication gaps. (Empirical Software Engineering) 2017: The role of distances in requirements communication: a case study. (Requir. Eng.) 2016: A theory of distances in software engineering. (Inf. Softw. Technol.) 2016: A multi-case study of agile requirements engineering and the use of test cases as requirements. (Inf. Softw. Technol.) 2014: Challenges and practices in aligning requirements with verification and validation: a case study of six companies. (Empirical Software Engineering) 2012: Are you biting off more than you can chew? A case study on causes and effects of overscoping in large-scale software engineering. (Inf. Softw. Technol.) | |
| Davide Fucci | Blekinge Institute of Technology | 8.75 | 2020: Need for Sleep: The Impact of a Night of Sleep Deprivation on Novice Developers’ Performance. (IEEE Trans. Software Eng.) 2017: A Dissection of the Test-Driven Development Process: Does It Really Matter to Test-First or to Test-Last? (IEEE Trans. Software Eng.) 2015: Towards an operationalization of test-driven development skills: An industrial empirical study. (Inf. Softw. Technol.) 2014: On the role of tests in test-driven development: a differentiated and partial replication. (Empirical Software Engineering) | |
| Mauro Caporuscio | Linneaus Univerity | 8.34 | 2017: Building design-time and run-time knowledge for QoS-based component assembly. (Softw. Pract. Exp.) 2016: GoPrime: A Fully Decentralized Middleware for Utility-Aware Service Assembly. (IEEE Trans. Software Eng.) 2015: Engineering Future Internet applications: The Prime approach. (J. Syst. Softw.) 2007: Model-based system reconfiguration for dynamic performance management. (J. Syst. Softw.) 2003: Design and Evaluation of a Support Service for Mobile, Wireless Publish/Subscribe Applications. (IEEE Trans. Software Eng.) | |
| Pontus Johnson | KTH Royal Institute of Technology | 8.33 | 2016: The Tarpit – A general theory of software engineering. (Inf. Softw. Technol.) | |
| Antonio Cicchetti | Mälardalen University | 8.08 | 2019: Multi-view approaches for software and system modelling: a systematic literature review. (Software and Systems Modeling) 2013: Managing the evolution of data-intensive Web applications by model-driven techniques. (Software and Systems Modeling) | |
| Panagiota Chatzipetrou | Örebro University | 7.97 | 2020: Component attributes and their importance in decisions and component selection. (Softw. Qual. J.) 2015: A multivariate statistical framework for the analysis of software effort phase distribution. (Inf. Softw. Technol.) 2015: An experience-based framework for evaluating alignment of software quality goals. (Softw. Qual. J.) | |
| Thorsten Berger | Chalmers / Gothenburg University | 7.92 | 2020: The state of adoption and the challenges of systematic variability management in industry. (Empirical Software Engineering) 2014: Variability mechanisms in software ecosystems. (Inf. Softw. Technol.) 2013: A Study of Variability Models and Languages in the Systems Software Domain. (IEEE Trans. Software Eng.) | |
| Fabian Fagerholm | Blekinge Institute of Technology | 7.74 | 2018: Designing and implementing an environment for software start-up education: Patterns and anti-patterns. (J. Syst. Softw.) 2017: The RIGHT model for Continuous Experimentation. (J. Syst. Softw.) 2015: Performance Alignment Work: How software developers experience the continuous adaptation of team performance in Lean and Agile environments. (Inf. Softw. Technol.) | |
| Mira Kajko-Mattsson | KTH Royal Institute of Technology | 7.61 | 2005: A Survey of Documentation Practice within Corrective Maintenance. (Empirical Software Engineering) 2004: Problems within front-end support. (J. Softw. Maintenance Res. Pract.) 2002: Problem management maturity within corrective maintenance. (J. Softw. Maintenance Res. Pract.) 2000: Software problem reporting and resolution process at ABB Robotics AB: state of practice. (J. Softw. Maintenance Res. Pract.) | |
| Philipp Leitner | Chalmers / Gothenburg University | 7.57 | 2019: A mixed-method empirical study of Function-as-a-Service software development in industrial practice. (J. Syst. Softw.) | |
| Emil Alégroth | Blekinge Institute of Technology | 7.35 | 2017: On the long-term use of visual gui testing in industrial practice: a case study. (Empirical Software Engineering) 2016: Maintenance of automated test suites in industry: An empirical study on Visual GUI Testing. (Inf. Softw. Technol.) 2015: Visual GUI testing in practice: challenges, problemsand limitations. (Empirical Software Engineering) | |
| Birgit Penzenstadler | Chalmers / Gothenburg University | 7.29 | 2018: Sustainability analysis and ease of learning in artifact-based requirements engineering: The newest member of the family of studies (It’s a girl!). (Inf. Softw. Technol.) | |
| Jakob Axelsson | RISE Research Institutes of Sweden | 7.18 | 2016: Quality assurance in software ecosystems: A systematic literature mapping and research agenda. (J. Syst. Softw.) 2014: Characteristics of software ecosystems for Federated Embedded Systems: A case study. (Inf. Softw. Technol.) | |
| Ulrik Franke | RISE Research Institutes of Sweden | 6.92 | 2018: What can we learn from enterprise architecture models? An experiment comparing models and documents for capability development. (Software and Systems Modeling) 2014: An architecture framework for enterprise IT service availability analysis. (Software and Systems Modeling) 2012: Availability of enterprise IT systems: an expert-based Bayesian framework. (Softw. Qual. J.) | |
| Helena Holmström Olsson | Malmö University | 6.62 | 2020: Going digital: Disruption and transformation in software-intensive embedded systems ecosystems. (J. Softw. Evol. Process.) 2017: From ad hoc to strategic ecosystem management: the “Three-Layer Ecosystem Strategy Model” (TeLESM). (J. Softw. Evol. Process.) | |
| Jan-Philipp Steghöfer | Chalmers / Gothenburg University | 6.51 | 2017: No silver brick: Opportunities and limitations of teaching Scrum with Lego workshops. (J. Syst. Softw.) | |
| Robert Lagerström | KTH Royal Institute of Technology | 6.32 | 2013: Increasing software development efficiency and maintainability for complex industrial systems – A case study. (J. Softw. Evol. Process.) 2012: Identifying factors affecting software development cost and productivity. (Softw. Qual. J.) 2010: Architecture analysis of enterprise systems modifiability – Models, analysis, and validation. (J. Syst. Softw.) 2010: Architecture analysis of enterprise systems modifiability: a metamodel for software change cost estimation. (Softw. Qual. J.) | |
| Hannes Holm | KTH Royal Institute of Technology | 5.5 | 2015: A Bayesian network model for likelihood estimations of acquirement of critical software vulnerabilities and exploits. (Inf. Softw. Technol.) 2014: Automatic data collection for enterprise architecture models. (Software and Systems Modeling) | |
| Peter Fritzson | Linköping University | 5.17 | 1994: Using assertions in declarative and operational models for automated debugging. (J. Syst. Softw.) 1983: Symbolic debugging through incremental compilation in an integrated environment. (J. Syst. Softw.) | |
| Barbara Gallina | Mälardalen University | 5.17 | 2020: Quantitative evaluation of tailoring within SPICE-compliant security-informed safety-oriented process lines. (J. Softw. Evol. Process.) | |
| Bestoun S. Ahmed | Karlstad University | 4.9 | 2017: Handling constraints in combinatorial interaction testing in the presence of multi objective particle swarm and multithreading. (Inf. Softw. Technol.) 2015: Achievement of minimized combinatorial test suite for configuration-aware software functional testing using the Cuckoo Search algorithm. (Inf. Softw. Technol.) 2011: A variable strength interaction test suites generation strategy using Particle Swarm Optimization. (J. Syst. Softw.) | |
| Jonas Lundberg | Linneaus Univerity | 4.2 | 2009: Fast and precise points-to analysis. (Inf. Softw. Technol.) | |
| Ludwik Kuzniarz | Blekinge Institute of Technology | 4.06 | 2011: Empirical extension of a classification framework for addressing consistency in model based development. (Inf. Softw. Technol.) | |
| Francis Palma | Linneaus Univerity | 4.06 | 2019: UniDoSA: The Unified Specification and Detection of Service Antipatterns. (IEEE Trans. Software Eng.) | |
| Mariam Kamkar | Linköping University | 4.05 | 1998: Application of program slicing in algorithmic debugging. (Inf. Softw. Technol.) 1995: An overview and comparative classification of program slicing techniques. (J. Syst. Softw.) | |
| Gul Calikli | Chalmers / Gothenburg University | 4.04 | 2015: Empirical analysis of factors affecting confirmation bias levels of software engineers. (Softw. Qual. J.) | |
| Lars Pareto | Chalmers / Gothenburg University | 4.0 | 2012: Collaborative prioritization of architectural concerns. (J. Syst. Softw.) 2012: Concern coverage in base station development: an empirical investigation. (Software and Systems Modeling) | |
| Jonas Gamalielsson | Skövde University | 3.96 | 2015: On organisational influences in software standards and their open source implementations. (Inf. Softw. Technol.) 2014: Sustainability of Open Source software communities beyond a fork: How and why has the LibreOffice project evolved? (J. Syst. Softw.) | |
| Francisco Gomes de Oliveira Neto | Chalmers / Gothenburg University | 3.91 | 2019: Evolution of statistical analysis in empirical software engineering research: Current state and steps forward. (J. Syst. Softw.) 2016: Full modification coverage through automatic similarity-based test case selection. (Inf. Softw. Technol.) | |
| Kenneth Lind | Chalmers / Gothenburg University | 3.84 | 2012: A Practical Approach to Size Estimation of Embedded Software Components. (IEEE Trans. Software Eng.) | |
| Deepika Badampudi | Blekinge Institute of Technology | 3.83 | 2018: A decision-making process-line for selection of software asset origins and components. (J. Syst. Softw.) 2016: Software component decision-making: In-house, OSS, COTS or outsourcing – A systematic literature review. (J. Syst. Softw.) | |
| Thomas Olsson | RISE Research Institutes of Sweden | 3.82 | 2019: An empirical study on decision making for quality requirements. (J. Syst. Softw.) | |
| Jelena Zdravkovic | Stockholm University | 3.79 | 2015: Capturing consumer preferences as requirements for software product lines. (Requir. Eng.) | |
| Birgitta Lindström | Skövde University | 3.79 | 2019: On strong mutation and the theory of subsuming logic-based mutants. (Softw. Test. Verification Reliab.) 2017: Using mutation to design tests for aspect-oriented models. (Inf. Softw. Technol.) | |
| Javier Gonzalez-Huerta | Blekinge Institute of Technology | 3.74 | 2015: Validating a model-driven software architecture evaluation and improvement method: A family of experiments. (Inf. Softw. Technol.) | |
| Kristian Sandahl | Linköping University | 3.53 | 1998: An Extended Replication of an Experiment for Assessing Methods for Software Requirements Inspections. (Empirical Software Engineering) | |
| Pasqualina Potena | RISE Research Institutes of Sweden | 3.37 | 2013: Optimization of adaptation plans for a service-oriented architecture with cost, reliability, availability and performance tradeoff. (J. Syst. Softw.) | |
| Görel Hedin | Lund University | 3.33 | 2005: Teaching extreme programming to large groups of students. (J. Syst. Softw.) | |
| Imed Hammouda | Chalmers / Gothenburg University | 3.14 | 2009: Design profiles: toward unified tool support for design patterns and UML profiles. (Softw. Pract. Exp.) | |
| Saad Mubeen | Mälardalen University | 3.03 | 2019: Supporting timing analysis of vehicular embedded systems through the refinement of timing constraints. (Software and Systems Modeling) 2015: Integrating mixed transmission and practical limitations with the worst-case response-time analysis for Controller Area Network. (J. Syst. Softw.) | |
| Niklas Lavesson | Jönköping University | 2.99 | 2014: A method for evaluation of learning components. (Autom. Softw. Eng.) | |
| Narges Khakpour | Linneaus Univerity | 2.81 | 2012: HPobSAM for modeling and analyzing IT Ecosystems – Through a case study. (J. Syst. Softw.) | |
| Muhammad Ovais Ahmad | Karlstad University | 2.75 | 2018: Kanban in software engineering: A systematic mapping study. (J. Syst. Softw.) 2017: An empirical study of portfolio management and Kanban in agile and lean software companies. (J. Softw. Evol. Process.) | |
| Christin Lindholm | Lund University | 2.57 | 2015: Involving user perspective in a software risk management process. (J. Softw. Evol. Process.) 2014: A case study on software risk analysis and planning in medical device development. (Softw. Qual. J.) | |
| Ana Magazinius | RISE Research Institutes of Sweden | 2.55 | 2012: Investigating intentional distortions in software cost estimation – An exploratory study. (J. Syst. Softw.) 2010: Software cost estimation inhibitors – a case study in automotive context. (J. Softw. Maintenance Res. Pract.) | |
| Patrik Berander | Malmö University | 2.53 | 2009: Evaluating two ways of calculating priorities in requirements hierarchies – An experiment on hierarchical cumulative voting. (J. Syst. Softw.) | |
| Cyrille Artho | KTH Royal Institute of Technology | 2.5 | 2003: High-level data races. (Softw. Test. Verification Reliab.) | |
| Niklas Mellegård | RISE Research Institutes of Sweden | 1.47 | 2016: Impact of Introducing Domain-Specific Modelling in Software Maintenance: An Industrial Case Study. (IEEE Trans. Software Eng.) | |
| Michael Mattsson | Blekinge Institute of Technology | 1.45 | 2000: Stability assessment of evolving industrial object-oriented frameworks. (J. Softw. Maintenance Res. Pract.) | |
| Daniel Flemström | Mälardalen University | 1.33 | 2018: Similarity-based prioritization of test case automation. (Softw. Qual. J.) | |
| Francesco Flammini | Linneaus Univerity | 1.32 | 2009: Automatic instantiation of abstract tests on specific configurations for large critical control systems. (Softw. Test. Verification Reliab.) | |
| Peter Wallin | RISE Research Institutes of Sweden | 1.27 | 2012: Problems and their mitigation in system and software architecting. (Inf. Softw. Technol.) | |
| Stefan Cedergren | RISE Research Institutes of Sweden | 1.0 | 2014: Evaluating performance in the development of software-intensive products. (Inf. Softw. Technol.) |
| Scholar | Affiliation | #Publ. | SCI ratio | 1st ratio | SSS contrib. | SSS rating | |
|---|---|---|---|---|---|---|---|
| Claes Wohlin | Blekinge Institute of Technology | 176 | 0.39 | 0.31 | 24.98 | 63.2 | |
| Jan Bosch | Chalmers / Gothenburg University | 332 | 0.13 | 0.31 | 12.59 | 53.52 | |
| Per Runeson | Lund University | 143 | 0.29 | 0.21 | 8.72 | 36.8 | |
| Emilia Mendes | Blekinge Institute of Technology | 176 | 0.15 | 0.4 | 11.39 | 33.35 | |
| Benoit Baudry | KTH Royal Institute of Technology | 190 | 0.18 | 0.12 | 6.76 | 29.31 | |
| Tony Gorschek | Blekinge Institute of Technology | 114 | 0.44 | 0.12 | 11.04 | 26.56 | |
| Robert Feldt | Chalmers / Gothenburg University | 120 | 0.27 | 0.14 | 4.98 | 24.74 | |
| Miroslaw Staron | Chalmers / Gothenburg University | 127 | 0.15 | 0.35 | 10.18 | 23.53 | |
| Björn Regnell | Lund University | 89 | 0.33 | 0.18 | 6.2 | 22.99 | |
| Michael Felderer | Blekinge Institute of Technology | 167 | 0.1 | 0.31 | 7.61 | 21.57 | |
| Krzysztof Wnuk | Blekinge Institute of Technology | 93 | 0.2 | 0.3 | 7.14 | 20.92 | |
| Martin Monperrus | KTH Royal Institute of Technology | 90 | 0.27 | 0.18 | 6.66 | 20.83 | |
| Martin Höst | Lund University | 94 | 0.19 | 0.21 | 7.06 | 18.45 | |
| Jürgen Börstler | Blekinge Institute of Technology | 75 | 0.2 | 0.37 | 4.8 | 17.71 | |
| Ivica Crnkovic | Chalmers / Gothenburg University | 144 | 0.09 | 0.28 | 5.31 | 16.75 | |
| Daniel Méndez Fernández | Blekinge Institute of Technology | 78 | 0.18 | 0.28 | 7.44 | 15.94 | |
| Darja Smite | Blekinge Institute of Technology | 70 | 0.17 | 0.5 | 6.28 | 15.26 | |
| Mikael Svahnberg | Blekinge Institute of Technology | 32 | 0.41 | 0.59 | 9.59 | 14.61 | |
| Eric Knauss | Chalmers / Gothenburg University | 98 | 0.11 | 0.32 | 3.77 | 13.8 | |
| Markus Borg | RISE Research Institutes of Sweden | 59 | 0.19 | 0.42 | 5.18 | 13.71 | |
| Patrizio Pelliccione | Chalmers / Gothenburg University | 132 | 0.14 | 0.06 | 4.74 | 12.79 | |
| Efi Papatheocharous | RISE Research Institutes of Sweden | 53 | 0.19 | 0.49 | 4.13 | 12.65 | |
| Federico Ciccozzi | Mälardalen University | 66 | 0.14 | 0.44 | 5.97 | 11.96 | |
| Gregory Gay | Chalmers / Gothenburg University | 31 | 0.32 | 0.65 | 6.61 | 11.94 | |
| Emelie Engström | Lund University | 32 | 0.34 | 0.41 | 5.81 | 11.54 | |
| Wasif Afzal | Mälardalen University | 62 | 0.15 | 0.21 | 5.03 | 10.28 | |
| Michael Unterkalmsteiner | Blekinge Institute of Technology | 32 | 0.34 | 0.28 | 5.81 | 10.15 | |
| Nauman Bin Ali | Blekinge Institute of Technology | 21 | 0.48 | 0.48 | 6.51 | 10.08 | |
| Regina Hebig | Chalmers / Gothenburg University | 58 | 0.14 | 0.33 | 4.0 | 10.05 | |
| Richard Berntsson-Svensson | Chalmers / Gothenburg University | 44 | 0.18 | 0.45 | 4.76 | 9.9 | |
| Jennifer Horkoff | Chalmers / Gothenburg University | 97 | 0.07 | 0.39 | 6.1 | 9.35 | |
| Riccardo Scandariato | Chalmers / Gothenburg University | 67 | 0.13 | 0.16 | 3.28 | 9.29 | |
| Björn Lundell | Skövde University | 71 | 0.1 | 0.31 | 3.14 | 9.17 | |
| Elizabeth Bjarnason | Lund University | 30 | 0.23 | 0.7 | 6.33 | 8.89 | |
| Davide Fucci | Blekinge Institute of Technology | 42 | 0.17 | 0.38 | 4.65 | 8.75 | |
| Mauro Caporuscio | Linneaus Univerity | 47 | 0.13 | 0.66 | 5.51 | 8.34 | |
| Pontus Johnson | KTH Royal Institute of Technology | 90 | 0.07 | 0.26 | 2.34 | 8.33 | |
| Antonio Cicchetti | Mälardalen University | 75 | 0.08 | 0.35 | 3.09 | 8.08 | |
| Panagiota Chatzipetrou | Örebro University | 20 | 0.35 | 0.55 | 3.53 | 7.97 | |
| Thorsten Berger | Chalmers / Gothenburg University | 78 | 0.08 | 0.22 | 4.02 | 7.92 | |
| Fabian Fagerholm | Blekinge Institute of Technology | 41 | 0.15 | 0.39 | 3.65 | 7.74 | |
| Mira Kajko-Mattsson | KTH Royal Institute of Technology | 105 | 0.05 | 0.72 | 5.1 | 7.61 | |
| Philipp Leitner | Chalmers / Gothenburg University | 113 | 0.05 | 0.21 | 2.57 | 7.57 | |
| Emil Alégroth | Blekinge Institute of Technology | 27 | 0.22 | 0.52 | 3.51 | 7.35 | |
| Birgit Penzenstadler | Chalmers / Gothenburg University | 103 | 0.05 | 0.42 | 2.38 | 7.29 | |
| Jakob Axelsson | RISE Research Institutes of Sweden | 64 | 0.08 | 0.58 | 2.89 | 7.18 | |
| Ulrik Franke | RISE Research Institutes of Sweden | 72 | 0.07 | 0.38 | 3.87 | 6.92 | |
| Helena Holmström Olsson | Malmö University | 95 | 0.05 | 0.33 | 3.2 | 6.62 | |
| Jan-Philipp Steghöfer | Chalmers / Gothenburg University | 70 | 0.07 | 0.27 | 2.05 | 6.51 | |
| Robert Lagerström | KTH Royal Institute of Technology | 78 | 0.06 | 0.27 | 4.83 | 6.32 | |
| Hannes Holm | KTH Royal Institute of Technology | 40 | 0.1 | 0.55 | 2.56 | 5.5 | |
| Peter Fritzson | Linköping University | 124 | 0.03 | 0.19 | 3.4 | 5.17 | |
| Barbara Gallina | Mälardalen University | 74 | 0.05 | 0.34 | 2.0 | 5.17 | |
| Bestoun S. Ahmed | Karlstad University | 23 | 0.17 | 0.43 | 3.29 | 4.9 | |
| Jonas Lundberg | Linneaus Univerity | 61 | 0.05 | 0.28 | 1.78 | 4.2 | |
| Ludwik Kuzniarz | Blekinge Institute of Technology | 27 | 0.11 | 0.56 | 1.44 | 4.06 | |
| Francis Palma | Linneaus Univerity | 20 | 0.15 | 0.7 | 1.37 | 4.06 | |
| Mariam Kamkar | Linköping University | 28 | 0.11 | 0.39 | 2.35 | 4.05 | |
| Gul Calikli | Chalmers / Gothenburg University | 26 | 0.12 | 0.38 | 1.43 | 4.04 | |
| Lars Pareto | Chalmers / Gothenburg University | 26 | 0.12 | 0.35 | 2.33 | 4.0 | |
| Jonas Gamalielsson | Skövde University | 32 | 0.09 | 0.5 | 2.39 | 3.96 | |
| Francisco Gomes de Oliveira Neto | Chalmers / Gothenburg University | 20 | 0.15 | 0.5 | 2.27 | 3.91 | |
| Kenneth Lind | Chalmers / Gothenburg University | 13 | 0.23 | 0.69 | 1.3 | 3.84 | |
| Deepika Badampudi | Blekinge Institute of Technology | 11 | 0.27 | 0.82 | 2.18 | 3.83 | |
| Thomas Olsson | RISE Research Institutes of Sweden | 40 | 0.07 | 0.35 | 1.57 | 3.82 | |
| Jelena Zdravkovic | Stockholm University | 89 | 0.03 | 0.27 | 2.06 | 3.79 | |
| Birgitta Lindström | Skövde University | 20 | 0.15 | 0.4 | 2.27 | 3.79 | |
| Javier Gonzalez-Huerta | Blekinge Institute of Technology | 35 | 0.09 | 0.17 | 1.52 | 3.74 | |
| Kristian Sandahl | Linköping University | 28 | 0.21 | 0.07 | 1.72 | 3.53 | |
| Pasqualina Potena | RISE Research Institutes of Sweden | 32 | 0.09 | 0.16 | 1.49 | 3.37 | |
| Görel Hedin | Lund University | 78 | 0.03 | 0.27 | 1.86 | 3.33 | |
| Imed Hammouda | Chalmers / Gothenburg University | 73 | 0.03 | 0.32 | 1.81 | 3.14 | |
| Saad Mubeen | Mälardalen University | 69 | 0.03 | 0.58 | 2.67 | 3.03 | |
| Niklas Lavesson | Jönköping University | 54 | 0.04 | 0.24 | 1.62 | 2.99 | |
| Narges Khakpour | Linneaus Univerity | 20 | 0.1 | 0.75 | 1.28 | 2.81 | |
| Muhammad Ovais Ahmad | Karlstad University | 17 | 0.12 | 0.53 | 2.15 | 2.75 | |
| Christin Lindholm | Lund University | 8 | 0.25 | 0.75 | 2.06 | 2.57 | |
| Ana Magazinius | RISE Research Institutes of Sweden | 9 | 0.22 | 0.67 | 2.07 | 2.55 | |
| Patrik Berander | Malmö University | 7 | 0.29 | 0.71 | 1.15 | 2.53 | |
| Cyrille Artho | KTH Royal Institute of Technology | 85 | 0.02 | 0.55 | 1.93 | 2.5 | |
| Niklas Mellegård | RISE Research Institutes of Sweden | 13 | 0.08 | 0.69 | 1.12 | 1.47 | |
| Michael Mattsson | Blekinge Institute of Technology | 13 | 0.08 | 0.54 | 1.12 | 1.45 | |
| Daniel Flemström | Mälardalen University | 8 | 0.12 | 0.75 | 1.07 | 1.33 | |
| Francesco Flammini | Linneaus Univerity | 45 | 0.02 | 0.42 | 1.44 | 1.32 | |
| Peter Wallin | RISE Research Institutes of Sweden | 11 | 0.09 | 0.27 | 1.1 | 1.27 | |
| Stefan Cedergren | RISE Research Institutes of Sweden | 4 | 0.25 | 0.25 | 1.03 | 1.0 |
Detailed information
The source code used to calculate the data and generate the tables is available as
- Publication data are extracted from the manually curated DBLP. Publications that are not indexed by DBLP are not considered. Also, arXiv publications and Software Engineering Notes are removed.
- Prof. Robert Feldt’s list of SCI-listed SE journals is used to determine the SCI status. This means that the magazines IEEE SW, IEEE Computer, and CACM are excluded.
- SCI ratio is the fraction of a scholar’s papers that are publications in SCI-listed journals. We do not filter out introduction sections to special issues etc.
- 1st ratio is the fraction of a scholar’s first-authorships.
- SSS rating is calculated as the total number of publications multiplied by the weighted harmonic mean between the SCI-ratio and the 1st ratio, where the SCI-ratio is weighted twice as important as the 1st ratio. The SSS ratio can both increase and decrease, thus it is a more interesting metric to follow over time – SCI ratio emphasizes a quality focus (as opposed to paper inflation) and 1st ratio values active research (rather than management and supervision). I like the SSS rating as it indicates how prolific scholars are, but it also deteriorates by unrestrained co-authorships.
- SSS
contrib . is (just like the H-index) a non-decreasing number calculated as 1*SCI-listed first-authorships + 0.1*SCI-listed co-authorships + 0.01*other publications. This metric is useful if you don’t like the ideas of the fluctuating SSS rating. - The apparent research interests of individual SSS scholars
is calculated by listing the most used terms in the titles of all first-authored publications. A manually curated stop-word list is used in the preprocessing. - The research topics of affiliations are calculated using topic modeling (LDA) with the paper titles of first-authored publications of SSS scholars as input. The number of topics and terms per topic are based on the total number of words in the input.
FAQ
Q: Isn’t there enough focus on rankings and lists already?
A. Yes, but let’s do this anyway. The main purpose of the Swe-SE-SCI index is to help navigate the expertise among academic SE scholars in Sweden. The index must be ordered in some way, and it turns into gamification no matter what metric you choose. My original idea was actually to embrace gamification even more by providing achievements in the form of badges.
Q: But there are other prestigious publications venues as well! Feldt’s list doesn’t cover everything. Why don’t you include the SCI-listed journal X?
A. There are indeed other great journals that publish amazing research. However, Feldt’s list is carefully curated for software engineering, I couldn’t do a better job myself.
Q: Shouldn’t you properly acknowledge ICSE publications? Now it’s valued just like a minor research workshop.
A: No. While ICSE is a highly competitive and prestigious venue, it is already recognized enough. I like journal publications and I prefer incentives to redirect paper submissions away from conferences.
Q: Why don’t you include PhD students and postdocs? They also publish great journal papers.
A: True, but I need to select a sustainable scope. As soon as the PhD student gets a permanent position in Sweden I will be happy to add her/him. Also, the main purpose of SWE-SE-SCI is to index expertise in Sweden – scholars with permanent positions are likely to be appropriate contact persons for industry. The SSS scholars can of course, in turn, recommend other internal experts.
Q: Being a co-author to help others is a supportive thing to do. Doesn’t the 1st ratio discourage collaboration? Supervisors get penalized by the SSS ratio.
A: Writing papers together is a great thing to do and what really makes SE research fun. However, the average number of authors on papers is growing – a metric that encourages scholars to think twice before putting her/his name on a paper is a good counter-balance. Supervision is certainly another great thing in research, but it’s not the job for Swe-SE-SCI to highlight.
Q: Software engineering is a multidisciplinary topic, thus considering only a few SCI-listed journals is a problem. Can’t you see that great scholars with plenty of other SCI-listed publications are undervalued?
A: Yes, but Swe-SE-SCI doesn’t try to rank scholars based on their research greatness. Swe-SE-SCI is mainly focusing on contributions in core SE journals. This index is for SE in Sweden, others are welcome to maintain lists for related areas such as computer science, information systems, enterprise architecture, artificial intelligence… the code is available on GitHub. And yes, some senior SSS scholars focusing on other topics might appear surprisingly low on the lists. They might be great researchers, but they
Q: Why don’t you include any open access journals? You support the old broken academic publication system.
A: I include the SCI-listed journals selected by Prof. Feldt. There are open access journals on the SCI “emerging list” such as e-Informatica Software Engineering Journal. I look forward to including such open access journals when they are upgraded to the “extended list”.