Dynamic filtering and prioritization of static code analysis alerts

Name: Dynamic filtering and prioritization of static code analysis alerts
Author: Yüksel, U., Sözer, Hasan

İsim	Dynamic filtering and prioritization of static code analysis alerts
Yazar	Yüksel, U., Sözer, Hasan
Basım Tarihi:	2021
Basım Yeri	- IEEE
Konu	Code reviews, Processing alarms/warnings/alerts, Program analysis, Prolog, Static code analysis
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-1-6654-2604-6
Kayıt Numarası	71fa9abc-7c2a-4549-bbe2-2289ab50c500
Lokasyon	Computer Science
Tarih	2021
Örnek Metin	We propose an approach for filtering and prioritizing static code analysis alerts while these alerts are being reviewed by the developer. We construct a Prolog knowledge base that captures the data flow information in the source code as well as the reported alerts, their properties and associations with the data flow. The knowledge base is updated as the developer reviews the listed alerts and decides whether they point at an actual fault or not. These updates provide useful information since some of the alerts of the same type can be related in terms of their root cause. Hence, dynamically updated knowledge base can be queried to eliminate or prioritize the remaining alerts in the review list. We present a motivating example to illustrate the approach and its automation by integrating a set of tools.
DOI	10.1109/ISSREW53611.2021.00086

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Dynamic filtering and prioritization of static code analysis alerts

Yazar Yüksel, U., Sözer, Hasan

Basım Tarihi 2021

Basım Yeri - IEEE

Konu Code reviews, Processing alarms/warnings/alerts, Program analysis, Prolog, Static code analysis

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-1-6654-2604-6

Kayıt Numarası 71fa9abc-7c2a-4549-bbe2-2289ab50c500

Lokasyon Computer Science

Tarih 2021

Örnek Metin We propose an approach for filtering and prioritizing static code analysis alerts while these alerts are being reviewed by the developer. We construct a Prolog knowledge base that captures the data flow information in the source code as well as the reported alerts, their properties and associations with the data flow. The knowledge base is updated as the developer reviews the listed alerts and decides whether they point at an actual fault or not. These updates provide useful information since some of the alerts of the same type can be related in terms of their root cause. Hence, dynamically updated knowledge base can be queried to eliminate or prioritize the remaining alerts in the review list. We present a motivating example to illustrate the approach and its automation by integrating a set of tools.

DOI 10.1109/ISSREW53611.2021.00086