Challenges and pitfalls on surveying evidence in the software engineering technical literature: an exploratory study with novices

Challenges and pitfalls on surveying evidence in the software engineering technical literature:... The evidence-based software engineering approach advocates the use of evidence from empirical studies to support the decisions on the adoption of software technologies by practitioners in the software industry. To this end, many guidelines have been proposed to contribute to the execution and repeatability of literature reviews, and to the confidence of their results, especially regarding systematic literature reviews (SLR). To investigate similarities and differences, and to characterize the challenges and pitfalls of the planning and generated results of SLR research protocols dealing with the same research question and performed by similar teams of novice researchers in the context of the software engineering field. We qualitatively compared (using Jaccard and Kappa coefficients) and evaluated (using DARE) same goal SLR research protocols and outcomes undertaken by similar research teams. Seven similar SLR protocols regarding quality attributes for use cases executed in 2010 and 2012 enabled us to observe unexpected differences in their planning and execution. Even when the participants reached some agreement in the planning, the outcomes were different. The research protocols and reports allowed us to observe six challenges contributing to the divergences in the results: researchers’ inexperience in the topic, researchers’ inexperience in the method, lack of clearness and completeness of the papers, lack of a common terminology regarding the problem domain, lack of research verification procedures, and lack of commitment to the SLR. According to our findings, it is not possible to rely on results of SLRs performed by novices. Also, similarities at a starting or intermediate step during different SLR executions may not directly translate to the next steps, since non-explicit information might entail differences in the outcomes, hampering the repeatability and confidence of the SLR process and results. Although we do have expectations that the presence and follow-up of a senior researcher can contribute to increasing SLRs’ repeatability, this conclusion can only be drawn upon the existence of additional studies on this topic. Yet, systematic planning, transparency of decisions and verification procedures are key factors to guarantee the reliability of SLRs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Empirical Software Engineering Springer Journals

Challenges and pitfalls on surveying evidence in the software engineering technical literature: an exploratory study with novices

Loading next page...
 
/lp/springer_journal/challenges-and-pitfalls-on-surveying-evidence-in-the-software-FNhOo8jToi
Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Computer Science; Software Engineering/Programming and Operating Systems; Programming Languages, Compilers, Interpreters
ISSN
1382-3256
eISSN
1573-7616
D.O.I.
10.1007/s10664-017-9556-7
Publisher site
See Article on Publisher Site

Abstract

The evidence-based software engineering approach advocates the use of evidence from empirical studies to support the decisions on the adoption of software technologies by practitioners in the software industry. To this end, many guidelines have been proposed to contribute to the execution and repeatability of literature reviews, and to the confidence of their results, especially regarding systematic literature reviews (SLR). To investigate similarities and differences, and to characterize the challenges and pitfalls of the planning and generated results of SLR research protocols dealing with the same research question and performed by similar teams of novice researchers in the context of the software engineering field. We qualitatively compared (using Jaccard and Kappa coefficients) and evaluated (using DARE) same goal SLR research protocols and outcomes undertaken by similar research teams. Seven similar SLR protocols regarding quality attributes for use cases executed in 2010 and 2012 enabled us to observe unexpected differences in their planning and execution. Even when the participants reached some agreement in the planning, the outcomes were different. The research protocols and reports allowed us to observe six challenges contributing to the divergences in the results: researchers’ inexperience in the topic, researchers’ inexperience in the method, lack of clearness and completeness of the papers, lack of a common terminology regarding the problem domain, lack of research verification procedures, and lack of commitment to the SLR. According to our findings, it is not possible to rely on results of SLRs performed by novices. Also, similarities at a starting or intermediate step during different SLR executions may not directly translate to the next steps, since non-explicit information might entail differences in the outcomes, hampering the repeatability and confidence of the SLR process and results. Although we do have expectations that the presence and follow-up of a senior researcher can contribute to increasing SLRs’ repeatability, this conclusion can only be drawn upon the existence of additional studies on this topic. Yet, systematic planning, transparency of decisions and verification procedures are key factors to guarantee the reliability of SLRs.

Journal

Empirical Software EngineeringSpringer Journals

Published: Oct 28, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off