@article{
 title = {QATCH - An adaptive framework for software product quality assessment},
 type = {article},
 year = {2017},
 identifiers = {[object Object]},
 keywords = {Fuzzy analytic hierarchy process,Multi-criteria decision making,Quality metrics,Software engineering,Software quality assessment,Software static analysis},
 volume = {86},
 id = {60d13b03-cfbf-3a26-8856-e54e00c2a807},
 created = {2017-06-23T07:58:43.937Z},
 file_attached = {false},
 profile_id = {ed131701-35e7-34ba-9595-c6cd765a711d},
 last_modified = {2017-07-01T12:40:55.307Z},
 read = {true},
 starred = {true},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 abstract = {© 2017 Elsevier LtdThe subjectivity that underlies the notion of quality does not allow the design and development of a universally accepted mechanism for software quality assessment. This is why contemporary research is now focused on seeking mechanisms able to produce software quality models that can be easily adjusted to custom user needs. In this context, we introduce QATCH, an integrated framework that applies static analysis to benchmark repositories in order to generate software quality models tailored to stakeholder specifications. Fuzzy multi-criteria decision-making is employed in order to model the uncertainty imposed by experts’ judgments. These judgments can be expressed into linguistic values, which makes the process more intuitive. Furthermore, a robust software quality model, the base model, is generated by the system, which is used in the experiments for QATCH system verification. The paper provides an extensive analysis of QATCH and thoroughly discusses its validity and added value in the field of software quality through a number of individual experiments.},
 bibtype = {article},
 author = {Siavvas, M.G. and Chatzidimitriou, K.C. and Symeonidis, A.L.},
 journal = {Expert Systems with Applications}
}

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