Per Runeson

Per Runeson
Lund University | LU · Department of Computer Science

PhD

About

243
Publications
113,018
Reads
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16,706
Citations
Additional affiliations
August 2011 - June 2012
North Carolina State University
Position
  • Professor
January 2004 - present
Lund University
Position
  • Professor (Full)
Education
January 1995 - January 1998
Lund University
Field of study
  • Software Engineering

Publications

Publications (243)
Article
Context In large software organizations with a product line development approach, system test planning and scope selection is a complex task. Due to repeated testing: across different testing levels, over time (test for regression) as well as of different variants, the risk of redundant testing is large as well as the risk of overlooking important...
Article
Full-text available
Weak alignment of requirements engineering (RE) with verification and validation (VV) may lead to problems in delivering the required products in time with the right quality. For example, weak communication of requirements changes to testers may result in lack of verification of new requirements and incorrect verification of old invalid requirement...
Article
Full-text available
Abstract,Case study is a suitable research methodology,for software engineering,research since it studies contemporary phenomena in its natural context. However, the understanding of what constitutes a case study varies, and hence the quality of the resulting studies. This paper aims,at providing,an introduction to case study methodology,and,guidel...
Preprint
Full-text available
Motivation. Digital commons is an emerging phenomenon and of increasing importance, as we enter a digital society. Open data is one example that makes up a pivotal input and foundation for many of today's digital services and applications. Ensuring sustainable provisioning and maintenance of the data, therefore, becomes even more important. Aim. We...
Preprint
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High-quality data has become increasingly important to software engineers in designing and implementing today's software, for example, as an input to machine-learning algorithms and visualisation- and analytics-based features. Open data - i.e., data shared under a licence that gives users the right to study, process, and distribute the data to anyo...
Preprint
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Background: By creating ecosystems around platforms of Open Source Software (OSS) and Open Data (OD), and adopting open collaborative development practices, platform providers may exploit open innovation benefits. However, adopting such practices in a traditionally closed organization is a maturity process that we hypothesize cannot be undergone wi...
Preprint
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Background: Open innovation highlights the potential benefits of external collaboration and knowledge-sharing, often exemplified through Open Source Software (OSS). The public sector has thus far mainly focused on the sharing of Open Government Data (OGD), often with a supply-driven approach with limited feedback-loops. We hypothesize that public s...
Preprint
Full-text available
Context. Innovation is promoted in companies to help them stay competitive. Four types of innovation are defined: product, process, business, and organizational. Objective. We want to understand the perception of the innovation concept in industry, and particularly how the innovation types relate to each other. Method. We launched a survey at a bra...
Preprint
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Objective: Our objective is to explore how public entities in the role of platform providers can address this issue by enabling collaboration within their OGD ecosystems, both in terms of the OGD published on the underpinning platform, as well as any related Open Source Software (OSS) and standards. Method: We conducted an exploratory multiple-case...
Preprint
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Autonomous driving has become an important research area for road traffic, whereas testing of autonomous driving systems to ensure a safe and reliable operation, remains an open challenge. Substantial real-world testing or massive driving data collection does not scale, as the potential test scenarios in real-world traffic are infinite and covering...
Article
Engineers require high-quality data for the design and implementation of today’s software, especially in the context of machine learning (ML). This puts an emphasis on the need for the publication and sharing of data from and between organizations, public as well as private. Following the paradigm of open innovation, open data provide a mechanism t...
Article
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DevOps represent the tight connection between development and operations. To address challenges that arise on the borderline between development and operations, we conducted a study in collaboration with a Swedish company responsible for ticket management and sales in public transportation. The aim of our study was to explore and describe the exist...
Preprint
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Software systems are increasingly depending on data, particularly with the rising use of machine learning, and developers are looking for new sources of data. Open Data Ecosystems (ODE) is an emerging concept for data sharing under public licenses in software ecosystems, similar to Open Source Software (OSS). It has certain similarities to Open Gov...
Article
Software systems are increasingly depending on data, particularly with the rising use of machine learning, and developers are looking for new sources of data. Open Data Ecosystems (ODE) is an emerging concept for data sharing under public licenses in software ecosystems, similar to Open Source Software (OSS). It has certain similarities to Open Gov...
Article
Full-text available
Open Government Data (OGD) is an important driver for open innovation among public entities. However, extant research highlights a need for improved feedback loops, collaboration, and a more demand-driven publication of OGD. In this study, we explore how public platform providers can address this issue by enabling collaboration within OGD ecosystem...
Conference Paper
Testing of autonomous vehicles involves enormous challenges for the automotive industry. The number of real-world driving scenarios is extremely large, and choosing effective test scenarios is essential, as well as combining simulated and real world testing. We present an industrial workbench of tools and workflows to generate efficient and effecti...
Preprint
Full-text available
Objective: The purpose of this paper is to identify the largest cognitive challenges faced by novices developing software in teams. Method: Using grounded theory, we conducted an ethnographic study for two months following four ten person novice teams, consisting of computer science students, developing software systems. Result: This paper identifi...
Article
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Background The literature concerning research methodologies and methods has increased in software engineering in the last decade. However, there is limited guidance on selecting an appropriate research methodology for a given research study or project. Objective Based on a selection of research methodologies suitable for software engineering resea...
Article
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Empirical software engineering research relies on good communication with industrial partners. Conducting joint research both requires and contributes to bridging the communication gap between industry and academia (IA) in software engineering. This study aims to explore communication between the two parties in such a setting. To better understand...
Preprint
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Testing of autonomous systems is extremely important as many of them are both safety-critical and security-critical. The architecture and mechanism of such systems are fundamentally different from traditional control software, which appears to operate in more structured environments and are explicitly instructed according to the system design and i...
Preprint
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Context: Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective: We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we we...
Article
Full-text available
Context Continuous experimentation and A/B testing is an established industry practice that has been researched for more than 10 years. Our aim is to synthesize the conducted research. Objective We wanted to find the core constituents of a framework for continuous experimentation and the solutions that are applied within the field. Finally, we wer...
Article
Context The changes that are taking place with respect to environmental sensitivity are forcing organizations to adopt a new approach to this problem. Implementing sustainability initiatives has become a priority for the social and environmental awareness of organizations that want to stay ahead of the curve. One of the business areas that has, mor...
Chapter
Software engineering research aims to help improve real-world practice. With the adoption of empirical software engineering research methods, the understanding of real-world needs and validation of solution proposals have evolved. However, the philosophical perspective on what constitutes theoretical knowledge and research contributions in software...
Chapter
Background: Open innovation highlights the potential benefits of external collaboration and knowledge-sharing, often exemplified through Open Source Software (OSS). The public sector has thus far mainly focused on the sharing of Open Government Data (OGD), often with a supply-driven approach with limited feedback-loops. We hypothesize that public s...
Article
Full-text available
Background Assessing and communicating software engineering research can be challenging. Design science is recognized as an appropriate research paradigm for applied research, but is rarely explicitly used as a way to present planned or achieved research contributions in software engineering. Applying the design science lens to software engineering...
Article
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Moving toward the open innovation (OI) model requires multifaceted transformations within companies. It often involves giving away the tools for product development or sharing future product directions with open tools ecosystems. Moving from the traditional closed innovation model toward an OI model for software development tools shows the potentia...
Conference Paper
Data defined software is becoming more and more prevalent, especially with the advent of machine learning and artificial intelligence. With data defined systems come both challenges - to continue to collect and maintain quality data - and opportunities - open innovation by sharing with others. We propose Open Data Collaboration (ODC) to describe pe...
Preprint
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Background: Communicating software engineering research to industry practitioners and to other researchers can be challenging due to its context dependent nature. Design science is recognized as a pragmatic research paradigm, addressing this and other characteristics of applied and prescriptive research. Applying the design science lens to software...
Conference Paper
Full-text available
Context: Open tools (e.g., Jenkins, Gerrit and Git) offer a lucrative alternative to commercial tools. Many companies and developers from OSS communities make a collaborative effort to improve the tools. Prior to this study, we developed an empirically based theory for companies' strategic choices on the development of these tools, based on empiric...
Conference Paper
Background. Continuous experimentation (CE) has recently emerged as an established industry practice and as a research subject. Our aim is to study the application of CE and A/B testing in various industrial contexts. Objective. We wanted to investigate whether CE is used in different sectors of industry, by how it is reported in academic studies....
Article
Full-text available
Exploratory testing (ET) is a powerful and efficient way of testing software by integrating design, execution, and analysis of tests during a testing session. ET is often contrasted with scripted testing, and seen as a choice of either exploratory testing or not. In contrast, we pose that exploratory testing can be of varying degrees of exploration...
Article
Full-text available
Background. Despite growing interest of Open Innovation (OI) in Software Engineering (SE), little is known about what triggers software organizations to adopt it and how this affects SE practices. OI can be realized in numerous of ways, including Open Source Software (OSS) involvement. Outcomes from OI are not restricted to product innovation but a...
Article
The relative pros and cons of using students or practitioners in experiments in empirical software engineering have been discussed for a long time and continue to be an important topic. Following the recent publication of “Empirical software engineering experts on the use of students and professionals in experiments” by Falessi, Juristo, Wohlin, Tu...
Article
Context The increased use of Open Source Software (OSS) affects how software-intensive product development organizations (SIPDO) innovate and compete, moving them towards Open Innovation (OI). Specifically, software engineering tools have the potential for OI, but require better understanding regarding what to develop internally and what to acquire...
Conference Paper
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Much empirical software engineering research aims at producing prescriptive knowledge that helps software engineers improve their work or solve their problems. But deriving general knowledge from real world problem solving instances can be challenging. In this paper, we promote design science as a paradigm to support producing and communicating pre...
Conference Paper
Controlled experiments, also called A/B tests or split tests, are used in software engineering to improve products by evaluating variants with user data. By parameterizing software systems, multivariate experiments can be performed automatically and in large scale, in this way, controlled experimentation is formulated as an optimization problem. Us...
Conference Paper
Background. Search and selection of primary studies in Systematic Literature Reviews (SLR) is labour intensive, and hard to replicate and update. Aims. We explore a machine learning approach to support semi-automated search and selection in SLRs to address these weaknesses. Method. We 1) train a classifier on an initial set of papers, 2) extend thi...
Article
Full-text available
Despite growing interest of Open Innovation (OI) in Software Engineering (SE), little is known about what triggers software organizations to adopt it and how this affects SE practices. OI can be realized in numerous of ways, including Open Source Software (OSS) involvement. Outcomes from OI are not restricted to product innovation but also include...
Article
Full-text available
Exploratory testing (ET) is a powerful and efficient way of testing software by integrating design, execution, and analysis of tests during a testing session. ET is often contrasted with scripted testing, and seen as a choice between black and white. We pose that there are different levels of exploratory testing from fully exploratory to fully scri...
Conference Paper
Full-text available
Software engineers working in large projects must navigate complex information landscapes. Change Impact Analysis (CIA) is a task that relies on engineers' successful information seeking in databases storing, e.g., source code, requirements, design descriptions, and test case specifications. Several previous approaches to support information seekin...
Article
This issue's letter discusses the proper use of sampling in software engineering research surveys.
Article
Change Impact Analysis (CIA) during software evolution of safety-critical systems is a labor-intensive task. Several authors have proposed tool support for CIA, but very few tools were evaluated in industry. We present a case study on ImpRec, a recommendation System for Software Engineering (RSSE), tailored for CIA at a process automation company....
Chapter
Quantitative data comes with enormous possibilities for presenting key characteristics of the data in a very compressed form. Basic descriptive statistics, like mean and standard deviation, comprise thousands or millions of data points into single numbers. In contrast, qualitative data, with its focus on descriptions, words, and phrases does not co...
Article
Full-text available
Change Impact Analysis (CIA) during software evolution of safety-critical systems is a labor-intensive task. Several authors have proposed tool support for CIA, but very few tools were evaluated in industry. We present a case study on ImpRec, a recommendation System for Software Engineering (RSSE), tailored for CIA at a process automation company....
Conference Paper
Full-text available
Empirical software engineering is a growing research area. Industrial experience gathered by systematic empirical case studies is extremely important for further evolution of the software engineering discipline. Scientific theory cannot provide effective means for software industry without fundamental understanding of the evolutionary development o...
Article
Context: Open innovation (OI) is considered a main driver for inventions in general, and its challenges are touching software producing organizations (SPO) when they are moving from a closed innovation model to more open approaches, to accelerate their internal innovation process. Objective: This study aims to identify the OI state of the art in so...
Article
Full-text available
Case studies are largely used for investigating software engineering practices. They are characterized by their flexible nature, multiple forms of data collection, and are mostly informed by qualitative data. Synthesis of case studies is necessary to build a body of knowledge from individual cases. There are many methods for such synthe- sis, but t...
Article
Full-text available
Context: Bug report assignment is an important part of software maintenance. In particular, incorrect assignments of bug reports to development teams can be very expensive in large software development projects. Several studies propose automating bug assignment techniques using machine learning in open source software contexts, but no study exists...
Conference Paper
Open Innovation (OI) has gained significant attention since the term was introduced in 2003. However, little is known whether general software testing processes are well suited for OI. An exploratory case study on the Acceptance Test Harness (ATH) is conducted to investigate OI testing activities of Jenkins. As far as the research methodology is co...
Conference Paper
Context. Innovation is promoted in companies to help them stay competitive. Four types of innovation are defined: product, process, business, and organizational. Objective. We want to understand the perception of the innovation concept in industry, and particularly how the innovation types relate to each other. Method. We launched a survey at a bra...
Article
Full-text available
Coordinating a software project across distances is challenging. Even without geographical and time zone distances, other distances within a project can cause communication gaps. For example, organisational and cognitive distances between product owners and development-near roles such as developers and testers can lead to differences in understandi...
Conference Paper
Full-text available
Background. Test automation is a widely used technique to increase the efficiency of software testing. However, executing more test cases increases the effort required to analyze test results. At Qlik, automated tests run nightly for up to 20 development branches, each containing thousands of test cases, resulting in information overload. Aim. We t...
Article
Unit verification, including software inspections and unit tests, is usually the first code verification phase in the software development process. However, principles of unit verification are weakly explored, mostly due to the lack of data, since unit verification data are rarely systematically collected and only a few studies have been published...
Article
System of systems are of high complexity, and for each system, many different requirements are implemented in parallel. Systems are developed with some degree of managerial independence but later on have to work together. In this situation, many requirements are written, implemented, and tested in parallel for different systems that are to be integ...
Article
Full-text available
This issue of the Software Quality Journal contains a special section on Regression testing. Regression testing used to be considered as a special type of testing activity that is performed to prevent regression faults, i.e. damages to existing features, introduced by recent modifications to the software. This was a gigantic task involving an infea...
Article
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In formal experiments on software engineering, the number of factors that may impact an outcome is very high. Some factors are controlled and change by design, while others are are either unforeseen or due to chance. This paper aims to explore how context factors change in a series of formal experiments and to identify implications for experimentat...
Chapter
Full-text available
Changes in evolving software systems are often managed using an issue repository. This repository may contribute to information overload in an organization, but it may also help in navigating the software system. Software developers spend much effort on issue triage, a task in which the mere number of issue reports becomes a significant challenge....
Conference Paper
Full-text available
Context: Duplicate detection is a fundamental part of issue management. Systems able to predict whether a new defect report will be closed as a duplicate, may decrease costs by limiting rework and collecting related pieces of information. Previous work relies on the textual content of the defect reports, often assuming that better results are obtai...