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What are problem causes of software projects? – Data of root cause analysis at four software companies

Lehtinen, Timo and Mäntylä, Mika LU (2011) Empirical Software Engineering and Measurement (ESEM), 2011 International Symposium on In [Host publication title missing] p.388-391
Abstract (Swedish)
Abstract in Undetermined

Root cause analysis (RCA) is a structured investigation of a problem to detect the causes that need to be prevented. We applied ARCA, an RCA method, to target problems of four medium-sized software companies and collected 648 causes of software engineering problems. Thereafter, we applied grounded theory to the causes to study their types and related process areas. We detected 14 types of causes in 6 process areas. Our results indicate that development work and software testing are the most common process areas, whereas lack of instructions and experiences, insufficient work practices, low quality task output, task difficulty, and challenging existing product are the most common types of the causes.... (More)
Abstract in Undetermined

Root cause analysis (RCA) is a structured investigation of a problem to detect the causes that need to be prevented. We applied ARCA, an RCA method, to target problems of four medium-sized software companies and collected 648 causes of software engineering problems. Thereafter, we applied grounded theory to the causes to study their types and related process areas. We detected 14 types of causes in 6 process areas. Our results indicate that development work and software testing are the most common process areas, whereas lack of instructions and experiences, insufficient work practices, low quality task output, task difficulty, and challenging existing product are the most common types of the causes. As the types of causes are evenly distributed between the cases, we hypothesize that the distributions could be generalizable. Finally, we found that only 2.5% of the causes are related to software development tools that are widely investigated in software engineering research. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
[Host publication title missing]
pages
388 - 391
conference name
Empirical Software Engineering and Measurement (ESEM), 2011 International Symposium on
external identifiers
  • Scopus:84858739754
ISSN
1938-6451
ISBN
978-1-4577-2203-5
DOI
10.1109/ESEM.2011.55
language
English
LU publication?
no
id
b07b086b-c9b0-4434-8cc5-761cba42b1d1 (old id 2225563)
date added to LUP
2011-12-15 14:19:49
date last changed
2016-10-13 04:35:29
@misc{b07b086b-c9b0-4434-8cc5-761cba42b1d1,
  abstract     = {<b>Abstract in Undetermined</b><br/><br>
Root cause analysis (RCA) is a structured investigation of a problem to detect the causes that need to be prevented. We applied ARCA, an RCA method, to target problems of four medium-sized software companies and collected 648 causes of software engineering problems. Thereafter, we applied grounded theory to the causes to study their types and related process areas. We detected 14 types of causes in 6 process areas. Our results indicate that development work and software testing are the most common process areas, whereas lack of instructions and experiences, insufficient work practices, low quality task output, task difficulty, and challenging existing product are the most common types of the causes. As the types of causes are evenly distributed between the cases, we hypothesize that the distributions could be generalizable. Finally, we found that only 2.5% of the causes are related to software development tools that are widely investigated in software engineering research.},
  author       = {Lehtinen, Timo and Mäntylä, Mika},
  isbn         = {978-1-4577-2203-5},
  issn         = {1938-6451},
  language     = {eng},
  pages        = {388--391},
  series       = {[Host publication title missing]},
  title        = {What are problem causes of software projects? – Data of root cause analysis at four software companies},
  url          = {http://dx.doi.org/10.1109/ESEM.2011.55},
  year         = {2011},
}