NDLI: Automated training-set creation for software architecture traceability problem

Content Provider	Springer Nature Link
Author	Zogaan, Waleed Mujhid, Ibrahim S. Santos, Joanna C. Gonzalez, Danielle Mirakhorli, Mehdi
Copyright Year	2016
Abstract	Automated trace retrieval methods based on machine-learning algorithms can significantly reduce the cost and effort needed to create and maintain traceability links between requirements, architecture and source code. However, there is always an upfront cost to train such algorithms to detect relevant architectural information for each quality attribute in the code. In practice, training supervised or semi-supervised algorithms requires the expert to collect several files of architectural tactics that implement a quality requirement and train a learning method. Establishing such a training set can take weeks to months to complete. Furthermore, the effectiveness of this approach is largely dependent upon the knowledge of the expert. In this paper, we present three baseline approaches for the creation of training data. These approaches are (i) Manual Expert-Based, (ii) Automated Web-Mining, which generates training sets by automatically mining tactic’s APIs from technical programming websites, and lastly (iii) Automated Big-Data Analysis, which mines ultra-large scale code repositories to generate training sets. We compare the trace-link creation accuracy achieved using each of these three baseline approaches and discuss the costs and benefits associated with them. Additionally, in a separate study, we investigate the impact of training set size on the accuracy of recovering trace links. The results indicate that automated techniques can create a reliable training set for the problem of tracing architectural tactics.
Starting Page	1028
Ending Page	1062
Page Count	35
File Format	PDF
ISSN	13823256
Journal	Empirical Software Engineering
Volume Number	22
Issue Number	3
e-ISSN	15737616
Language	English
Publisher	Springer US
Publisher Date	2016-11-10
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Architecture traceability Dataset generation Architecturally significant requirements Automation Software Engineering/Programming and Operating Systems Programming Languages, Compilers, Interpreters
Content Type	Text
Resource Type	Article
Subject	Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Tackling the term-mismatch problem in automated trace retrieval

Improving automated requirements trace retrieval: a study of term-based enhancement methods

An industrial case study in reconstructing requirements views

Empirical studies in software and systems traceability

A streamlined, cost-effective database approach to manage requirements traceability

An empirical study on the importance of source code entities for requirements traceability

Do developers benefit from requirements traceability when evolving and maintaining a software system?

Knowledge Requirements for Software Quality Measurement

Requirements-Based Estimation of Change Costs

Automated training-set creation for software architecture traceability problem

Similar Documents

Tackling the term-mismatch problem in automated trace retrieval

Improving automated requirements trace retrieval: a study of term-based enhancement methods

An industrial case study in reconstructing requirements views

Empirical studies in software and systems traceability

A streamlined, cost-effective database approach to manage requirements traceability

An empirical study on the importance of source code entities for requirements traceability

Do developers benefit from requirements traceability when evolving and maintaining a software system?

Knowledge Requirements for Software Quality Measurement

Requirements-Based Estimation of Change Costs

Automated training-set creation for software architecture traceability problem