Zur Hauptnavigation wechseln Zur Suche wechseln Zum Hauptinhalt wechseln

Analyzing closeness of code dependencies for improving IR-based Traceability Recovery

  • Hongyu Kuang
  • , Jia Nie
  • , Hao Hu
  • , Patrick Rempel
  • , Jian Lu
  • , Alexander Egyed
  • , Patrick Mäder

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

Information Retrieval (IR) identifies trace links based on textual similarities among software artifacts. However, the vocabulary mismatch problem between different artifacts hinders the performance of IR-based approaches. A growing body of work addresses this issue by combining IR techniques with code dependency analysis such as method calls. However, so far the performance of combined approaches is highly dependent to the correctness of IR techniques and does not take full advantage of the code dependency analysis. In this paper, we combine IR techniques with closeness analysis to improve IR-based traceability recovery. Specifically, we quantify and utilize the “closeness” for each call and data dependency between two classes to improve rankings of traceability candidate lists. An empirical evaluation based on three real-world systems suggests that our approach outperforms three baseline approaches.
OriginalspracheEnglisch
TitelInternational Conference on Software Analysis, Evolution and Reengineering
Herausgeber*innenGabriele Bavota, Martin Pinzger, Andrian Marcus
Seiten68-78
Seitenumfang11
ISBN (elektronisch)9781509055012
DOIs
PublikationsstatusVeröffentlicht - 21 März 2017

Wissenschaftszweige

  • 102 Informatik
  • 102022 Softwareentwicklung

JKU-Schwerpunkte

  • Computation in Informatics and Mathematics
  • TNF Allgemein

Dieses zitieren