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CESI '16: Proceedings of the 4th International Workshop on Conducting Empirical Studies in Industry
ACM2016 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
ICSE '16: 38th International Conference on Software Engineering Austin Texas May 14 - 22, 2016
ISBN:
978-1-4503-4154-7
Published:
14 May 2016
Sponsors:
ACM, SIGSOFT, IEEE-CS\DATC, TCSE
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Abstract

The CESI series of workshops was born out of the need to shift the focus away from simply conducting empirical studies (be them case studies, experiments, surveys, etc.), and reporting their results, to putting them firmly in the context of the software industry. In other words, the aim was to better understand the challenges and opportunities brought about by the organisational context in the conduct of empirical studies.

There were several reasons for this shift. Simply knowing empirical procedures (from the literature or by conducting studies in, often tamed, academic environments) did not seem to prepare one for how to plan and conduct empirical studies in industry. There are just too many hurdles in the way of conducting successful studies in industry. Examples are: (i) understanding specific problems in practice such that conducting relevant studies would give some insight into solving observed problems; (ii) ploughing through organisational politics to zero down to key investigative questions and associated measurable variables; (iii) balancing between scientific purity in empirical procedures and being practical enough to yield usable results for making business decisions within short cycle-times; (iv) taking the results of studies and putting them into practice, in retrospect, to validate the conduct and the outcome of the studies; and more.

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SESSION: Keynote
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Experiences conducting experiments in industry: the ESEIL FiDiPro project

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SESSION: Industry perspective
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SESSION: Research perspective
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Defect prediction on a legacy industrial software: a case study on software with few defects

Context: Building defect prediction models for software projects is helpful for reducing the effort in locating defects. In this paper, we share our experiences in building a defect prediction model for a large industrial software project. We extract ...

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SESSION: Studies in industry
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Case studies in industry: what we have learnt

Case study research has become an important research methodology for exploring phenomena in their natural contexts. Case studies have earned a distinct role in the empirical analysis of software engineering phenomena which are difficult to capture in ...

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Evaluating the benefits of systematic project management in large public sector projects

After an external audit of top-priority projects, the Federal Office for Equipment, Information Technology, and In-Support of the German Armed Forces decided to implement a new project management (PM) system. The new PM system implies major changes in ...

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