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logseq/pages/hls__managingDataIntensiveEcosystems-chapter_1668416249546_0.md
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file:: [managingDataIntensiveEcosystems-chapter_1668416249546_0.pdf](../assets/managingDataIntensiveEcosystems-chapter_1668416249546_0.pdf)
file-path:: ../assets/managingDataIntensiveEcosystems-chapter_1668416249546_0.pdf
- the side effects on database design, querying, and maintenance are not well-known.
ls-type:: annotation
hl-page:: 1
hl-color:: purple
id:: 63720458-b3d7-4755-85dd-f269baa9a5f2
- We cover different processes, including automatic database query extraction, bad smell detection, self-admitted technical debt analysis, and evolution history visualization.
ls-type:: annotation
hl-page:: 1
hl-color:: purple
id:: 6372046c-787f-4b27-b745-7500ae97a37d
- If the query is not well-formed or not handled correctly in the program code, it generates extra load on the database side that affects the applications performance [1] [2].
ls-type:: annotation
hl-page:: 2
hl-color:: green
id:: 63720515-20a3-424e-96ea-dca34bfecbb9
hl-stamp:: 1668416793160
- discuss mining techniques
ls-type:: annotation
hl-page:: 2
hl-color:: green
id:: 63720569-687e-4ca8-a1cc-ae12e194c16c
- static analysis and visualization techniques that exploit the mined information on the storage and manipulation of the ecosystem data
ls-type:: annotation
hl-page:: 2
hl-color:: green
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- findings
ls-type:: annotation
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- concluding remarks
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