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.
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.
June 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.
June update: Somewhat delayed as a new name disambiguation was required. DBLP also modified a journal abbreviation. Minor changes, but some new co-authored SCI-listed papers.
| Affiliation | #SSS scholars | #SCI publications | Research topics | |
|---|---|---|---|---|
| Blekinge Institute of Technology | 18 | 94 | Topic 1: requirements effort decision company cost practice improve; Topic 2: testing estimation industrial empirical test process projects; Topic 3: web quality model project agile bayesian uml; Topic 4: development systematic value applications industry scale literature; Topic 5: models knowledge product management framework data defect | |
| Chalmers / Gothenburg University | 21 | 57 | Topic 1: model industrial sustainability evolution challenges practice automated; Topic 2: systems test design variability models data process; Topic 3: component empirical agile large patterns testing components; Topic 4: requirements development product analysis architecture ecosystems lines; Topic 5: modeling quality management open goal embedded measurement | |
| Lund University | 7 | 25 | Topic 1: regression open programming support academia source cases; Topic 2: line analysis model selection method methods supporting; Topic 3: testing product development attribute risk processes improving; Topic 4: test grammars practices quality scale device process; Topic 5: requirements management systematic large project distances language | |
| RISE Research Institutes of Sweden AB | 10 | 20 | Topic 1: models networks making model industrial hardware neural; Topic 2: service cyber framework systematic mapping reports fuzzy; Topic 3: estimation enterprise embedded traceability impact artificial tools; Topic 4: systems architecture automotive real availability selection method; Topic 5: cost analysis decision development time architecting insurance | |
| Mälardalen University | 6 | 16 | Topic 1: distributed development safety models process network controller; Topic 2: component messages industrial reuse evolution web vehicle; Topic 3: modeling vehicular uml applications test supporting semantics; Topic 4: systems analysis embedded end mixed systematic framework; Topic 5: model time response timing area complex modelling | |
| KTH Royal Institute of Technology | 6 | 14 | Topic 1: analysis automatic checking theory networked method empirical; Topic 2: architecture efficient security attack measurement testability applications; Topic 3: model test testing modeling probabilistic java business; Topic 4: enterprise automated critical static network verification general; Topic 5: systems vulnerability attacks design models application techniques | |
| Skövde University | 3 | 6 | Topic 1: standards model tool perceptions strong digital; Topic 2: open systems method swedish long projects; Topic 3: experiences organisations evolutionary fork lock sector; Topic 4: term companies development gene action pdf; Topic 5: source time mutants mutation involvement models | |
| Linköping University | 3 | 5 | Topic 1: modelica environment parallel simulation objectmath; Topic 2: slicing language incremental algorithmic 2010; Topic 3: dynamic modeling equation physical testing; Topic 4: debugging object interprocedural development openmodelica | |
| Linneaus Univerity | 5 | 5 | Topic 1: adaptive self modeling physical control soa component; Topic 2: systems antipatterns specification optimization graphs model points; Topic 3: analysis security programs logp patterns formal modelling; Topic 4: design resilience machines response task architecture machine; Topic 5: detection critical surveillance scheduling management web verification | |
| Karlstad University | 2 | 5 | Topic 1: kanban development agile mapping; Topic 2: testing interaction combinatorial swarm; Topic 3: systematic literature generation variable | |
| Malmö University | 2 | 3 | Topic 1: ecosystem data; Topic 2: data ecosystem | |
| Örebro University | 1 | 2 | Topic 1: data compositional prioritization; Topic 2: analysis requirements effort; Topic 3: framework statistical distribution | |
| Stockholm University | 1 | 1 | Topic 1: processes requirements flexible management; Topic 2: business capability service organizations; Topic 3: modeling process services lines | |
| Jönköping University | 1 | 1 | Topic 1: license user agreements; Topic 2: learning spyware agreements; Topic 3: end agreements user |
| Scholar | Affiliation | SSS rating | Apparent research interests | |
|---|---|---|---|---|
| Claes Wohlin | Blekinge Institute of Technology | 62.84 | empirical, project, success, factors, analysis, reliability, methods, journals, subjective, systematic | |
| Jan Bosch | Chalmers / Gothenburg University | 53.03 | product, architecture, lines, ecosystems, object, families, variability, development, component, design | |
| Emilia Mendes | Blekinge Institute of Technology | 37.01 | web, effort, estimation, company, value, applications, cost, hypermedia, improve, development | |
| Per Runeson | Lund University | 36.54 | testing, test, unit, academia, product, open, collaboration, detection, industry, inspection | |
| Benoit Baudry | KTH Royal Institute of Technology | 29.01 | test, model, testability, design, genetic, optimization, testing, automatic, validation, analysis | |
| Tony Gorschek | Blekinge Institute of Technology | 26.69 | requirements, empirical, model, process, product, abstraction, development, management, transfer, practice | |
| Robert Feldt | Chalmers / Gothenburg University | 25.43 | test, search, programming, genetic, diverse, empirical, versions, diversity, generating, testing | |
| Björn Regnell | Lund University | 23.34 | requirements, quality, model, scenario, large, org, scale, mobile, domain, testing | |
| Krzysztof Wnuk | Blekinge Institute of Technology | 22.21 | requirements, decision, management, scoping, large, open, industrial, scale, innovation, development | |
| Miroslaw Staron | Chalmers / Gothenburg University | 22.15 | industrial, measurement, development, systems, large, projects, model, code, measures, method | |
| Michael Felderer | Blekinge Institute of Technology | 21.44 | testing, risk, security, test, industrial, defect, system, requirements, quality, systems | |
| Martin Monperrus | KTH Royal Institute of Technology | 20.15 | model, measurement, system, automatic, les, automated, repair, method, calls, missing | |
| Jürgen Börstler | Blekinge Institute of Technology | 18.4 | teaching, object, role, play, learning, concepts, programmieren, quality, projects, tools | |
| Martin Höst | Lund University | 17.82 | product, source, development, processes, project, commercial, management, open, students, systematic | |
| Mikael Svahnberg | Blekinge Institute of Technology | 16.86 | quality, architecture, product, method, requirements, attributes, architectures, lines, consensus, assessment | |
| Ivica Crnkovic | Chalmers / Gothenburg University | 16.75 | component, systems, development, embedded, process, scm, components, challenges, predictability, management | |
| Daniel Méndez Fernández | Blekinge Institute of Technology | 15.94 | requirements, artefact, naming, pain, results, practice, artefacts, improvement, design, first | |
| Darja Smite | Blekinge Institute of Technology | 15.26 | global, development, learned, offshoring, lessons, agile, teams, cost, distributed, project | |
| Eric Knauss | Chalmers / Gothenburg University | 13.8 | requirements, continuous, supporting, von, agile, quality, anforderungen, ecosystems, heuristic, clarification | |
| Efi Papatheocharous | RISE Research Institutes of Sweden AB | 12.79 | cost, estimation, decision, artificial, neural, networks, development, fuzzy, agile, systems | |
| Patrizio Pelliccione | Chalmers / Gothenburg University | 12.7 | systems, cars, specifications, framework, architectural, ecosystems, evolution, automatic, chairs, designing | |
| Markus Borg | RISE Research Institutes of Sweden AB | 12.35 | traceability, analysis, reports, impact, bug, tools, time, safety, issue, information | |
| Richard Torkar | Chalmers / Gothenburg University | 12.03 | testing, libre, source, partition, combining, free, component, unit, industry, applicable | |
| Wasif Afzal | Mälardalen University | 11.04 | runtime, systematic, fault, testing, megam, prediction, megamodelling, model, project, development | |
| Gregory Gay | Chalmers / Gothenburg University | 11.03 | test, generation, search, coverage, real, model, steering, automated, faults, fitness | |
| Richard Berntsson-Svensson | Chalmers / Gothenburg University | 10.94 | requirements, quality, quper, practice, industrial, companies, model, creativity, techniques, making | |
| Emelie Engström | Lund University | 10.55 | test, regression, testing, selection, product, line, systematic, taxonomy, mapping, empirical | |
| Federico Ciccozzi | Mälardalen University | 10.32 | systems, model, uml, embedded, models, code, execution, modelling, generation, support | |
| Michael Unterkalmsteiner | Blekinge Institute of Technology | 10.15 | requirements, alignment, improvement, test, process, next, information, startups, report, spi | |
| Nauman Bin Ali | Blekinge Institute of Technology | 10.08 | systematic, search, simulation, process, literature, industrial, assisted, mapping, stream, development | |
| Regina Hebig | Chalmers / Gothenburg University | 10.05 | model, evolution, development, mde, processes, languages, combined, glass, transformation, complex | |
| Riccardo Scandariato | Chalmers / Gothenburg University | 9.29 | security, design, internet, penetration, defense, detection, threat, networks, technique, components | |
| Jennifer Horkoff | Chalmers / Gothenburg University | 9.25 | goal, modeling, requirements, analysis, interactive, models, systematic, model, creative, experiences | |
| Björn Lundell | Skövde University | 9.17 | open, source, perceptions, tool, swedish, method, standards, companies, openness, experiences | |
| Elizabeth Bjarnason | Lund University | 8.89 | requirements, development, distances, evidence, large, gaps, method, project, practices, timelines | |
| Davide Fucci | Blekinge Institute of Technology | 8.75 | test, development, replication, effects, skills, external, conformance, requirements, process, impact | |
| Fabian Fagerholm | Blekinge Institute of Technology | 8.58 | agile, education, projects, source, performance, onboarding, developers, patterns, lean, experience | |
| Pontus Johnson | KTH Royal Institute of Technology | 8.33 | architecture, analysis, modeling, theory, enterprise, probabilistic, business, general, vulnerability, diagrams | |
| Antonio Cicchetti | Mälardalen University | 8.08 | model, evolution, web, systems, applications, development, view, models, managing, weaving | |
| Thorsten Berger | Chalmers / Gothenburg University | 7.92 | variability, modeling, feature, management, systems, large, industry, projectional, und, models | |
| Philipp Leitner | Chalmers / Gothenburg University | 7.57 | service, services, cloud, web, violations, level, compositions, testing, practice, performance | |
| Welf Löwe | Linneaus Univerity | 7.26 | logp, programs, machines, scheduling, optimization, graphs, task, communication, machine, pram | |
| Birgit Penzenstadler | Chalmers / Gothenburg University | 7.22 | sustainability, requirements, systems, model, design, domain, green, systematic, automotive, system | |
| Robert Lagerström | KTH Royal Institute of Technology | 7.09 | architecture, enterprise, systems, analysis, modifiability, cost, management, models, metamodel, probabilistic | |
| Panagiota Chatzipetrou | Örebro University | 7.01 | analysis, statistical, requirements, framework, data, goals, quality, effort, phase, prioritization | |
| Jakob Axelsson | RISE Research Institutes of Sweden AB | 6.84 | systems, system, time, embedded, real, analysis, architecting, automotive, hardware, platooning | |
| Peter Fritzson | Linköping University | 6.73 | object, modelica, language, modeling, environment, equation, debugging, openmodelica, incremental, system | |
| Ulrik Franke | RISE Research Institutes of Sweden AB | 6.71 | enterprise, architecture, insurance, service, analysis, cyber, availability, framework, trade, models | |
| Jan-Philipp Steghöfer | Chalmers / Gothenburg University | 6.51 | systems, self, agile, open, organising, organic, scrum, computing, die, organizing | |
| Emil Alégroth | Blekinge Institute of Technology | 6.3 | testing, gui, visual, industrial, empirical, test, practice, system, technical, testware | |
| Bestoun S. Ahmed | Karlstad University | 6.04 | interaction, testing, combinatorial, particle, swarm, strength, variable, applications, systematic, model | |
| Hannes Holm | KTH Royal Institute of Technology | 5.5 | attacks, vulnerability, expert, system, investigation, application, web, scanning, security, empirical | |
| Helena Holmström Olsson | Malmö University | 5.25 | ecosystem, data, mind, layer, three, embedded, challenges, chaos, telesm, empowerment | |
| Barbara Gallina | Mälardalen University | 5.1 | safety, process, reuse, lines, model, iso, analysis, product, systems, compliant | |
| Imed Hammouda | Chalmers / Gothenburg University | 4.12 | open, source, design, patterns, concern, pattern, development, learning, uml, tool | |
| Jonas Lundberg | Linneaus Univerity | 4.07 | analysis, response, design, resilience, points, designing, identification, air, management, work | |
| Ludwik Kuzniarz | Blekinge Institute of Technology | 4.06 | uml, models, model, development, teaching, multimedia, object, initial, stereotypes, modeling | |
| Francis Palma | Linneaus Univerity | 4.06 | detection, antipatterns, patterns, specification, soa, service, prioritization, restful, linguistic, test | |
| Mariam Kamkar | Linköping University | 4.05 | slicing, dynamic, interprocedural, debugging, programs, program, testing, applied, algorithmic, three | |
| Gul Calikli | Chalmers / Gothenburg University | 4.04 | confirmation, bias, effects, analysis, factors, defect, human, developers, development, levels | |
| Lars Pareto | Chalmers / Gothenburg University | 4.0 | architectural, base, projects, empirical, station, model, development, concern, design, investigation | |
| Jonas Gamalielsson | Skövde University | 3.96 | open, source, standards, biological, pathways, evolutionary, w3c, model, analysis, alignment | |
| Kenneth Lind | Chalmers / Gothenburg University | 3.84 | size, estimation, components, embedded, time, real, code, automated, model, compsize | |
| Deepika Badampudi | Blekinge Institute of Technology | 3.83 | systematic, translation, knowledge, making, literature, decision, considerations, components, delays, contextualizing | |
| Birgitta Lindström | Skövde University | 3.83 | mutants, time, mutation, subsuming, aspect, real, dynamic, strong, systems, models | |
| Thomas Olsson | RISE Research Institutes of Sweden AB | 3.82 | making, gqm, quality, system, companies, requirements, decision, time, reconfigurable, language | |
| Jelena Zdravkovic | Stockholm University | 3.75 | business, capability, service, requirements, processes, modeling, organizations, governance, frameworks, enterprise | |
| Javier Gonzalez-Huerta | Blekinge Institute of Technology | 3.74 | product, derivation, architecture, validating, improvement, multimodel, model, models, artifacts, automatic | |
| Ana Magazinius | RISE Research Institutes of Sweden AB | 3.57 | estimation, cost, distortional, organizational, mapping, complexity, distortions, inhibitors, behaviors, programs | |
| Kristian Sandahl | Linköping University | 3.53 | extended, methods, systems, assessing, replication, participation, expert, active, requirements, knowledge | |
| Patrik Berander | Malmö University | 3.47 | requirements, voting, prioritization, cumulative, hierarchies, hierarchical, key, students, metric, identification | |
| Pasqualina Potena | RISE Research Institutes of Sweden AB | 3.37 | tradeoff, service, functional, directions, quality, composition, systems, architecture, optimization, attributes | |
| Görel Hedin | Lund University | 3.23 | attribute, grammars, programming, extreme, object, jastadd, preface, language, system, door | |
| Niklas Lavesson | Jönköping University | 2.99 | learning, license, end, user, agreements, spyware, amori, supervised, impact, networks | |
| Saad Mubeen | Mälardalen University | 2.98 | analysis, time, systems, end, response, embedded, component, timing, distributed, vehicular | |
| Narges Khakpour | Linneaus Univerity | 2.93 | systems, self, adaptive, formal, behavioral, adaptation, policies, security, modeling, policy | |
| Muhammad Ovais Ahmad | Karlstad University | 2.6 | kanban, development, agile, systematic, companies, perceptions, attitudes, teams, factory, lean | |
| Christin Lindholm | Lund University | 2.57 | risk, development, medical, device, analysis, management, process, investigated, usability, testing | |
| Michael Mattsson | Blekinge Institute of Technology | 2.57 | framework, industrial, evolution, evolving, stability, solutions, frameworks, causes, experience, paper | |
| Francisco Gomes de Oliveira Neto | Chalmers / Gothenburg University | 2.57 | test, requirements, support, empirical, testing, within, evolution, fault, initiative, coverage | |
| Cyrille Artho | KTH Royal Institute of Technology | 2.5 | model, checking, testing, analysis, java, networked, test, static, systems, dynamic | |
| Niklas Mellegård | RISE Research Institutes of Sweden AB | 1.47 | defect, automotive, impact, scheme, efficiency, initial, improving, development, embedded, process | |
| Daniel Flemström | Mälardalen University | 1.33 | test, guarded, passive, assertions, interactive, toolbox, saga, embedded, integration, mapping | |
| Peter Wallin | RISE Research Institutes of Sweden AB | 1.27 | development, related, issues, system, heavy, architecture, product, vehicles, automotive, architecting | |
| Francesco Flammini | Linneaus Univerity | 1.26 | systems, critical, modelling, surveillance, security, physical, multiformalism, infrastructure, infrastructures, sensor | |
| Stefan Cedergren | RISE Research Institutes of Sweden AB | 1.0 | products, performance, development, evaluating |
| Scholar | Affiliation | SSS rating | Signature SSS works | |
|---|---|---|---|---|
| Claes Wohlin | Blekinge Institute of Technology | 62.84 | 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. (Software Quality Journal) 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. (Software Quality Journal) 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 | 53.03 | 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.) | |
| Emilia Mendes | Blekinge Institute of Technology | 37.01 | 2019: Using Bayesian Network to Estimate the Value of Decisions within the Context of Value-Based Software Engineering: A Multiple Case Study. (International Journal of Software Engineering and Knowledge Engineering) 2018: Towards improving decision making and estimating the value of decisions in value-based software engineering: the VALUE framework. (Software Quality Journal) 2018: Correction to: Towards improving decision making and estimating the value of decisions in value-based software engineering: the VALUE framework. (Software Quality Journal) 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.) | |
| Per Runeson | Lund University | 36.54 | 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) | |
| Benoit Baudry | KTH Royal Institute of Technology | 29.01 | 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 | 26.69 | 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 | 25.43 | 2010: Links between the personalities, views and attitudes of software engineers. (Inf. Softw. Technol.) | |
| Björn Regnell | Lund University | 23.34 | 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.) | |
| Krzysztof Wnuk | Blekinge Institute of Technology | 22.21 | 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) | |
| Miroslaw Staron | Chalmers / Gothenburg University | 22.15 | 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.) | |
| Michael Felderer | Blekinge Institute of Technology | 21.44 | 2019: Comprehensibility of system models during test design: a controlled experiment comparing UML activity diagrams and state machines. (Software Quality Journal) 2016: Risk orientation in software testing processes of small and medium enterprises: an exploratory and comparative study. (Software Quality Journal) 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. (Software Quality Journal) | |
| Martin Monperrus | KTH Royal Institute of Technology | 20.15 | 2013: Automated measurement of models of requirements. (Software Quality Journal) 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) | |
| Jürgen Börstler | Blekinge Institute of Technology | 18.4 | 2016: Beauty and the Beast: on the readability of object-oriented example programs. (Software Quality Journal) 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.) | |
| Martin Höst | Lund University | 17.82 | 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.) | |
| Mikael Svahnberg | Blekinge Institute of Technology | 16.86 | 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.) 2003: A Quality-Driven Decision-Support Method for Identifying Software Architecture Candidates. (International Journal of Software Engineering and Knowledge Engineering) 1999: Evolution in software product lines: two cases. (J. Softw. Maintenance Res. Pract.) | |
| 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) | |
| 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.) | |
| Efi Papatheocharous | RISE Research Institutes of Sweden AB | 12.79 | 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.) 2012: A Hybrid Software Cost Estimation Approach Utilizing Decision Trees and Fuzzy Logic. (International Journal of Software Engineering and Knowledge Engineering) | |
| Patrizio Pelliccione | Chalmers / Gothenburg University | 12.7 | 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.) | |
| Markus Borg | RISE Research Institutes of Sweden AB | 12.35 | 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) | |
| Richard Torkar | Chalmers / Gothenburg University | 12.03 | 2012: Requirements Traceability: a Systematic Review and Industry Case Study. (International Journal of Software Engineering and Knowledge Engineering) | |
| Wasif Afzal | Mälardalen University | 11.04 | 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. (Software Quality Journal) 2012: Resampling Methods in Software Quality Classification. (International Journal of Software Engineering and Knowledge Engineering) 2009: A systematic review of search-based testing for non-functional system properties. (Inf. Softw. Technol.) | |
| Gregory Gay | Chalmers / Gothenburg University | 11.03 | 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.) | |
| Richard Berntsson-Svensson | Chalmers / Gothenburg University | 10.94 | 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.) | |
| Emelie Engström | Lund University | 10.55 | 2017: SERP-test: a taxonomy for supporting industry-academia communication. (Software Quality Journal) 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.) | |
| Federico Ciccozzi | Mälardalen University | 10.32 | 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! (Software Quality Journal) 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.) | |
| 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.) | |
| 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.) | |
| Jennifer Horkoff | Chalmers / Gothenburg University | 9.25 | 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.) | |
| 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) | |
| Fabian Fagerholm | Blekinge Institute of Technology | 8.58 | 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.) | |
| 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) | |
| 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.) | |
| 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.) | |
| Welf Löwe | Linneaus Univerity | 7.26 | 2005: Rapid Construction of Software Comprehension Tools. (International Journal of Software Engineering and Knowledge Engineering) | |
| Birgit Penzenstadler | Chalmers / Gothenburg University | 7.22 | 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.) | |
| Robert Lagerström | KTH Royal Institute of Technology | 7.09 | 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. (Software Quality Journal) 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. (Software Quality Journal) | |
| Panagiota Chatzipetrou | Örebro University | 7.01 | 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. (Software Quality Journal) | |
| Jakob Axelsson | RISE Research Institutes of Sweden AB | 6.84 | 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.) | |
| Peter Fritzson | Linköping University | 6.73 | 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.) | |
| Ulrik Franke | RISE Research Institutes of Sweden AB | 6.71 | 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. (Software Quality Journal) | |
| Jan-Philipp Steghöfer | Chalmers / Gothenburg University | 6.51 | 2017: No silver brick: Opportunities and limitations of teaching Scrum with Lego workshops. (J. Syst. Softw.) | |
| Emil Alégroth | Blekinge Institute of Technology | 6.3 | 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) | |
| Bestoun S. Ahmed | Karlstad University | 6.04 | 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.) | |
| 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) | |
| Helena Holmström Olsson | Malmö University | 5.25 | 2017: From ad hoc to strategic ecosystem management: the “Three-Layer Ecosystem Strategy Model” (TeLESM). (J. Softw. Evol. Process.) | |
| Barbara Gallina | Mälardalen University | 5.1 | 2020: Quantitative evaluation of tailoring within SPICE-compliant security-informed safety-oriented process lines. (J. Softw. Evol. Process.) | |
| Imed Hammouda | Chalmers / Gothenburg University | 4.12 | 2011: Managing Concern Knowledge in Software Systems. (International Journal of Software Engineering and Knowledge Engineering) 2009: Design profiles: toward unified tool support for design patterns and UML profiles. (Softw. Pract. Exp.) | |
| Jonas Lundberg | Linneaus Univerity | 4.07 | 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. (Software Quality Journal) | |
| 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.) | |
| 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.) | |
| Birgitta Lindström | Skövde University | 3.83 | 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.) | |
| Thomas Olsson | RISE Research Institutes of Sweden AB | 3.82 | 2019: An empirical study on decision making for quality requirements. (J. Syst. Softw.) | |
| Jelena Zdravkovic | Stockholm University | 3.75 | 2015: Capturing consumer preferences as requirements for software product lines. (Requir. Eng.) | |
| 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.) | |
| Ana Magazinius | RISE Research Institutes of Sweden AB | 3.57 | 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.) | |
| Kristian Sandahl | Linköping University | 3.53 | 1998: An Extended Replication of an Experiment for Assessing Methods for Software Requirements Inspections. (Empirical Software Engineering) | |
| Patrik Berander | Malmö University | 3.47 | 2009: Evaluating two ways of calculating priorities in requirements hierarchies – An experiment on hierarchical cumulative voting. (J. Syst. Softw.) 2006: Hierarchical Cumulative Voting (hcv) – Prioritization of Requirements in Hierarchies. (International Journal of Software Engineering and Knowledge Engineering) | |
| Pasqualina Potena | RISE Research Institutes of Sweden AB | 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 | 3.23 | 2005: Teaching extreme programming to large groups of students. (J. Syst. Softw.) | |
| Niklas Lavesson | Jönköping University | 2.99 | 2014: A method for evaluation of learning components. (Autom. Softw. Eng.) | |
| Saad Mubeen | Mälardalen University | 2.98 | 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.) | |
| Narges Khakpour | Linneaus Univerity | 2.93 | 2012: HPobSAM for modeling and analyzing IT Ecosystems – Through a case study. (J. Syst. Softw.) | |
| Muhammad Ovais Ahmad | Karlstad University | 2.6 | 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. (Software Quality Journal) | |
| Michael Mattsson | Blekinge Institute of Technology | 2.57 | 2000: Stability assessment of evolving industrial object-oriented frameworks. (J. Softw. Maintenance Res. Pract.) | |
| Francisco Gomes de Oliveira Neto | Chalmers / Gothenburg University | 2.57 | 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.) | |
| 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 AB | 1.47 | 2016: Impact of Introducing Domain-Specific Modelling in Software Maintenance: An Industrial Case Study. (IEEE Trans. Software Eng.) | |
| Daniel Flemström | Mälardalen University | 1.33 | 2018: Similarity-based prioritization of test case automation. (Software Quality Journal) | |
| Peter Wallin | RISE Research Institutes of Sweden AB | 1.27 | 2012: Problems and their mitigation in system and software architecting. (Inf. Softw. Technol.) | |
| Francesco Flammini | Linneaus Univerity | 1.26 | 2009: Automatic instantiation of abstract tests on specific configurations for large critical control systems. (Softw. Test. Verification Reliab.) | |
| Stefan Cedergren | RISE Research Institutes of Sweden AB | 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 | 175 | 0.39 | 0.31 | 25.06 | 62.84 | |
| Jan Bosch | Chalmers / Gothenburg University | 329 | 0.13 | 0.31 | 12.56 | 53.03 | |
| Emilia Mendes | Blekinge Institute of Technology | 176 | 0.17 | 0.4 | 12.56 | 37.01 | |
| Per Runeson | Lund University | 142 | 0.29 | 0.21 | 8.71 | 36.54 | |
| Benoit Baudry | KTH Royal Institute of Technology | 188 | 0.18 | 0.12 | 6.65 | 29.01 | |
| Tony Gorschek | Blekinge Institute of Technology | 112 | 0.47 | 0.12 | 11.29 | 26.69 | |
| Robert Feldt | Chalmers / Gothenburg University | 119 | 0.29 | 0.14 | 5.24 | 25.43 | |
| Björn Regnell | Lund University | 89 | 0.34 | 0.18 | 6.29 | 23.34 | |
| Krzysztof Wnuk | Blekinge Institute of Technology | 92 | 0.22 | 0.3 | 7.22 | 22.21 | |
| Miroslaw Staron | Chalmers / Gothenburg University | 126 | 0.14 | 0.36 | 10.08 | 22.15 | |
| Michael Felderer | Blekinge Institute of Technology | 166 | 0.1 | 0.31 | 7.6 | 21.44 | |
| Martin Monperrus | KTH Royal Institute of Technology | 89 | 0.26 | 0.18 | 6.56 | 20.15 | |
| Jürgen Börstler | Blekinge Institute of Technology | 75 | 0.21 | 0.37 | 4.89 | 18.4 | |
| Martin Höst | Lund University | 93 | 0.18 | 0.22 | 6.96 | 17.82 | |
| Mikael Svahnberg | Blekinge Institute of Technology | 32 | 0.5 | 0.59 | 10.76 | 16.86 | |
| 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 | |
| Eric Knauss | Chalmers / Gothenburg University | 98 | 0.11 | 0.32 | 3.77 | 13.8 | |
| Efi Papatheocharous | RISE Research Institutes of Sweden AB | 51 | 0.2 | 0.51 | 5.01 | 12.79 | |
| Patrizio Pelliccione | Chalmers / Gothenburg University | 131 | 0.14 | 0.06 | 4.73 | 12.7 | |
| Markus Borg | RISE Research Institutes of Sweden AB | 58 | 0.17 | 0.43 | 5.08 | 12.35 | |
| Richard Torkar | Chalmers / Gothenburg University | 63 | 0.35 | 0.1 | 3.51 | 12.03 | |
| Wasif Afzal | Mälardalen University | 60 | 0.17 | 0.22 | 6.0 | 11.04 | |
| Gregory Gay | Chalmers / Gothenburg University | 30 | 0.3 | 0.67 | 6.51 | 11.03 | |
| Richard Berntsson-Svensson | Chalmers / Gothenburg University | 43 | 0.21 | 0.44 | 4.84 | 10.94 | |
| Emelie Engström | Lund University | 31 | 0.32 | 0.39 | 4.81 | 10.55 | |
| Federico Ciccozzi | Mälardalen University | 65 | 0.12 | 0.45 | 5.87 | 10.32 | |
| 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 | |
| Riccardo Scandariato | Chalmers / Gothenburg University | 67 | 0.13 | 0.16 | 3.28 | 9.29 | |
| Jennifer Horkoff | Chalmers / Gothenburg University | 96 | 0.07 | 0.39 | 6.09 | 9.25 | |
| 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 | |
| Fabian Fagerholm | Blekinge Institute of Technology | 41 | 0.17 | 0.39 | 3.74 | 8.58 | |
| 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 | |
| Thorsten Berger | Chalmers / Gothenburg University | 78 | 0.08 | 0.22 | 4.02 | 7.92 | |
| Philipp Leitner | Chalmers / Gothenburg University | 113 | 0.05 | 0.21 | 2.57 | 7.57 | |
| Welf Löwe | Linneaus Univerity | 112 | 0.05 | 0.16 | 2.56 | 7.26 | |
| Birgit Penzenstadler | Chalmers / Gothenburg University | 102 | 0.05 | 0.42 | 2.37 | 7.22 | |
| Robert Lagerström | KTH Royal Institute of Technology | 76 | 0.07 | 0.28 | 4.81 | 7.09 | |
| Panagiota Chatzipetrou | Örebro University | 19 | 0.32 | 0.53 | 2.53 | 7.01 | |
| Jakob Axelsson | RISE Research Institutes of Sweden AB | 61 | 0.08 | 0.57 | 2.86 | 6.84 | |
| Peter Fritzson | Linköping University | 124 | 0.04 | 0.19 | 3.49 | 6.73 | |
| Ulrik Franke | RISE Research Institutes of Sweden AB | 70 | 0.07 | 0.37 | 3.85 | 6.71 | |
| Jan-Philipp Steghöfer | Chalmers / Gothenburg University | 70 | 0.07 | 0.27 | 2.05 | 6.51 | |
| Emil Alégroth | Blekinge Institute of Technology | 26 | 0.19 | 0.54 | 3.41 | 6.3 | |
| Bestoun S. Ahmed | Karlstad University | 23 | 0.22 | 0.43 | 3.38 | 6.04 | |
| Hannes Holm | KTH Royal Institute of Technology | 40 | 0.1 | 0.55 | 2.56 | 5.5 | |
| Helena Holmström Olsson | Malmö University | 93 | 0.04 | 0.32 | 2.19 | 5.25 | |
| Barbara Gallina | Mälardalen University | 73 | 0.05 | 0.34 | 1.99 | 5.1 | |
| Imed Hammouda | Chalmers / Gothenburg University | 73 | 0.04 | 0.32 | 2.8 | 4.12 | |
| Jonas Lundberg | Linneaus Univerity | 59 | 0.05 | 0.29 | 1.76 | 4.07 | |
| 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 | |
| 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 | |
| Birgitta Lindström | Skövde University | 19 | 0.16 | 0.42 | 2.26 | 3.83 | |
| Thomas Olsson | RISE Research Institutes of Sweden AB | 40 | 0.07 | 0.35 | 1.57 | 3.82 | |
| Jelena Zdravkovic | Stockholm University | 88 | 0.03 | 0.27 | 2.05 | 3.75 | |
| Javier Gonzalez-Huerta | Blekinge Institute of Technology | 35 | 0.09 | 0.17 | 1.52 | 3.74 | |
| Ana Magazinius | RISE Research Institutes of Sweden AB | 9 | 0.33 | 0.67 | 2.16 | 3.57 | |
| Kristian Sandahl | Linköping University | 28 | 0.21 | 0.07 | 1.72 | 3.53 | |
| Patrik Berander | Malmö University | 7 | 0.43 | 0.71 | 2.14 | 3.47 | |
| Pasqualina Potena | RISE Research Institutes of Sweden AB | 32 | 0.09 | 0.16 | 1.49 | 3.37 | |
| Görel Hedin | Lund University | 76 | 0.03 | 0.26 | 1.84 | 3.23 | |
| Niklas Lavesson | Jönköping University | 54 | 0.04 | 0.24 | 1.62 | 2.99 | |
| Saad Mubeen | Mälardalen University | 68 | 0.03 | 0.59 | 2.66 | 2.98 | |
| Narges Khakpour | Linneaus Univerity | 19 | 0.11 | 0.79 | 1.27 | 2.93 | |
| Muhammad Ovais Ahmad | Karlstad University | 16 | 0.12 | 0.56 | 2.14 | 2.6 | |
| Christin Lindholm | Lund University | 8 | 0.25 | 0.75 | 2.06 | 2.57 | |
| Michael Mattsson | Blekinge Institute of Technology | 13 | 0.15 | 0.54 | 1.21 | 2.57 | |
| Francisco Gomes de Oliveira Neto | Chalmers / Gothenburg University | 13 | 0.15 | 0.54 | 2.11 | 2.57 | |
| Cyrille Artho | KTH Royal Institute of Technology | 85 | 0.02 | 0.55 | 1.93 | 2.5 | |
| Niklas Mellegård | RISE Research Institutes of Sweden AB | 13 | 0.08 | 0.69 | 1.12 | 1.47 | |
| Daniel Flemström | Mälardalen University | 8 | 0.12 | 0.75 | 1.07 | 1.33 | |
| Peter Wallin | RISE Research Institutes of Sweden AB | 11 | 0.09 | 0.27 | 1.1 | 1.27 | |
| Francesco Flammini | Linneaus Univerity | 43 | 0.02 | 0.44 | 1.42 | 1.26 | |
| Stefan Cedergren | RISE Research Institutes of Sweden AB | 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”.