Sun 4 Nov 2018 14:15 - 14:30 at Rock Lake - NL4SE Workshop III

In the domain of software engineering NLP techniques are needed
to use and find duplicate or similar development knowledge which
are stored in development documentation as development tasks. To
understand duplicate and similar development documentations we
will discuss different NLP techniques as descriptive statistics, topic
analysis and similarity algorithms as N-grams, the Jaccard or LSI algorithm
as well as machine learning algorithms as Decision trees or
support vector machines (SVM). Those techniques are used to reach
a better understanding of the characteristics, the lexical relations
(syntactical and semantical) and the classification and prediction of
duplicate development tasks. We found that duplicate tasks share
conceptual information and are rather created by inexperienced developers.
By tuning different features to predict development tasks
with a gradient or a Fidelity loss function a system can identify a
duplicate tasks with a 100% accuracy.

Passionate Software Engineer, Architect and Researcher!

Sun 4 Nov
Times are displayed in time zone: (GMT-05:00) Guadalajara, Mexico City, Monterrey change

13:30 - 15:00: NL4SE - NL4SE Workshop III at Rock Lake
fse-2018-NL4SE13:30 - 13:45
Umme Ayda MannanOregon State University, USA, Iftekhar AhmedUniversity of California at Irvine, USA, Anita SarmaOregon State University
fse-2018-NL4SE13:45 - 14:00
fse-2018-NL4SE14:00 - 14:15
Xueqing LiuUniversity of Illinois at Urbana-Champaign, USA, Chi WangMicrosoft, USA, Yue LengUniversity of Illinois at Urbana-Champaign, USA, ChengXiang ZhaiUniversity of Illinois at Urbana-Champaign, USA
fse-2018-NL4SE14:15 - 14:30
Mathias EllmannUniversity of Hamburg and LegalTechTeam
fse-2018-NL4SE14:30 - 14:45
Grigoreta Sofia CojocarDepartment of Computer Science, Babes-Bolyai University, Adriana-Mihaela GuranDepartment of Computer Science, Babes-Bolyai University
fse-2018-NL4SE14:45 - 15:00
Mathias EllmannUniversity of Hamburg and LegalTechTeam, Marko Schnecken.n., n.n.