Reporting Experiments in Software Engineering

Jedlitschka, Andreas; Ciolkowski, Marcus; Pfahl, Dietmar

doi:10.1007/978-1-84800-044-5_8

Cited by 245 publications

(184 citation statements)

References 24 publications

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“…In IS research, there have been diverse propositions to ensure common standards of scientific rigor in empirical research such as field experiments or case studies [50,51]. Hevner et al [52] summarized empirical "design evaluation methods" for information systems research.…”

Section: Additional Aspectsmentioning

confidence: 99%

Effective application of process improvement patterns to business processes

Lohrmann

Reichert

2014

Softw Syst Model

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Improving the operational effectiveness and efficiency of processes is a fundamental task of business process management (BPM). There exist many proposals of process improvement patterns (PIPs) as practices that aim at supporting this goal. Selecting and implementing relevant PIPs are therefore an important prerequisite for establishing processaware information systems in enterprises. Nevertheless, there is still a gap regarding the validation of PIPs with respect to their actual business value for a specific application scenario before implementation investments are incurred. Based on empirical research as well as experiences from BPM projects, this paper proposes a method to tackle this challenge. Our approach toward the assessment of process improvement patterns considers real-world constraints such as the role of senior stakeholders or the cost of adapting available IT systems. In addition, it outlines process improvement potentials that arise from the information technology infrastructure available to organizations, particularly regarding the combination of enterprise resource planning with business process intelligence. Our approach is illustrated along a real-world business process from human resource management. The latter covers a transactional volume of about 29,000 process instances over a period of 1 year. Overall, our approach enables both practitioners and researchers to reasonably assess PIPs before taking any process implementation decision.

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Section: Additional Aspectsmentioning

confidence: 99%

Effective application of process improvement patterns to business processes

Lohrmann

Reichert

2014

Softw Syst Model

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“…To present our experiment, we use the guidelines suggested by Jedlitschka and Ciolkowski [27]. For brevity, we describe only necessary details to understand our experiment.…”

Section: Empirical Validationmentioning

confidence: 99%

“…Participants came from the University of Passau (27), Philipps University Marburg (31), and University of Magdeburg (70), so we had 128 participants in total. All universities are located in Germany.…”

Section: Participantsmentioning

confidence: 99%

Measuring and modeling programming experience

et al. 2013

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Programming experience is an important confounding parameter in controlled experiments regarding program comprehension. In literature, ways to measure or control programming experience vary. Often, researchers neglect it or do not specify how they controlled for it. We set out to find a well-defined understanding of programming experience and a way to measure it. From published comprehension experiments, we extracted questions that assess programming experience. In a controlled experiment, we compare the answers of computer-science students to these questions with their performance in solving program-comprehension tasks. We found that self estimation seems to be a reliable way to measure programming experience. Furthermore, we applied exploratory and confirmatory factor analyses to extract and evaluate a model of programming experience. With our analysis, we initiate a path toward validly and reliably measuring and describing programming experience to better understand and control its influence in program-comprehension experiments.

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“…As discussed in other empirical software engineering studies [16], it is necessary to identify possible threats to validity that could bring into question the experiment and its results.…”

Section: Threats To Validitymentioning

confidence: 99%