Table 4: Relation between types of technical debt and
decision criteria.
Types of TD Criteria Studies
Defect Debt
- Severity of the Debt
- Existence of workaround
- Debt impact on customer
- Debt impact on the project
- Scope of tests
- Cost-Benefit
-Effort to implement the
proposed correction
S1,
S16, S6
Design Debt
- Debt impact on the project
- Analysis when the refactored
part will be used
- Cost-Benefit
S2, S4,
S25
6 THREATS TO VALIDITY
Our study has some threats to validity. We present
them below with the strategies for its mitigation.
Selection Bias: we selected each study based on
the judgment of the inclusion and exclusion criteria.
Thus, we cannot guarantee that all relevant primary
studies were selected. With the intention of mitigate
this threat, we discussed the study protocol among
the researchers to guarantee a common
understanding and searched the studies into the main
digital libraries in our field.
Data Extraction: bias or problems on data
extraction from selected studies can affect their
classification. In order to reduce this bias, we
discussed deeply the definitions of data items and
the classification scheme.
External Validity:
we carried out a systematic
mapping study over studies published up 2014 that
focused on TD management. This implies that we
might have missed some relevant studies. Thus, we
cannot generalize our conclusions for whole TD
management approaches. However, our outcomes
allow us to draw insights to guide further
investigations.
7 CONCLUSIONS
The goal of this work was to conduct a systematic
mapping study of the literature in order to identify
criteria to support the decision on the payment of
existent TD items in software systems. We focused
on studies published up 2014 and selected 38 primary
works that discuss TD management strategies.
The main contribution of this work was the
identification of 14 decision criteria that can be used
by development team to decide and/or prioritize the
payment of TD items. In addition, we identified that
only two types of TD were related to decision-
making criteria. In this sense, we cannot recognize
whether: (i) decision criteria are independent of
types of TD, or (ii) there is some kind of influence
between decision criteria and types of TD.
Considering evaluation methods, we identified
that none of analyzed studies has performed any kind
of empirical evaluation. This may indicate a low
level of maturity of the decision-making criteria for
payment of TD.
In general, the results provide some evidence and
motivation for continuing to study decision criteria
for TD payment. As future work, we will investigate
the gaps identified in this mapping study. In
particular, continuing to explore decision criteria in
order to answer the following question: Are criteria
independent of types of TD or there is some kind of
influence between them?. We also intend to work on
the development of a TD management strategy based
on the identified criteria and their combinations.
ACKNOWLEDGEMENTS
This work was partially supported by CNPq
Universal 2014 grant 458261/2014-9.
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