NDLI: Empirical studies on software evolution: should we (try to) claim causation?

Please wait, while we are loading the content...

Software is data too: how should we deal with it?

Do metrics help to identify refactoring?

Identifying cross-cutting concerns using software repository mining

A framework for analysing and visualising open source software ecosystems

An exercise in iterative domain-specific language design

An empirical study of the evolution of Eclipse third-party plug-ins

Multi-tenant SaaS applications: maintenance dream or nightmare?

Empirical studies on software evolution: should we (try to) claim causation?

Recording finer-grained software evolution with IDE: an annotation-based approach

Redocumentation of a legacy banking system: an experience report

An automated hint generation approach for supporting the evolution of requirements specifications

Is duplicate code more frequently modified than non-duplicate code in software evolution?: an empirical study on open source software

Feature oriented evolutions for context-aware adaptive systems

Replaying past changes in multi-developer projects

Evolutional analysis of licenses in FOSS

Empirical studies on software evolution: should we (try to) claim causation?

Content Provider	ACM Digital Library
Author	Di Penta, Massimiliano
Abstract	In recent and past years, there have been hundreds of studies aimed at characterizing the evolution of a software system. Many of these studies analyze the behavior of a variable over a given period of observation. How does the size of a software system evolve? What about its complexity? Does the number of defects increase over time or does it remain stable? In some cases, studies also attempt to correlate variables, and, possibly, to build predictors upon them. This is to say, one could estimate the likelihood that a fault occurs in a class, based on some metrics the class exhibits, on the kinds of changes the class underwent. Similarly, change couplings can be inferred by observing how artifacts tend to co-change. Although in many cases we are able to obtain models ensuring good prediction performances, we are not able to claim any causal-effect relationship between our independent and dependent variables. We could easily correlate the presence of some design constructs with the change-proneness of a software component, however the same correlation could be found with the amount of good Belgian beer our developers drink. As a matter of fact, the component could undergo changes for other, external reasons. Recent software evolution studies rely on fine-grained information mined by integrating several kinds of repositories, such as versioning systems, bug tracking systems, or mailing lists. Nowadays, many other precious sources of information, ranging from code search repositories, vulnerability databases, informal communications, and legal documents are also being considered. This would possibly aid to capture the rationale of some events occurring in a software project, and link them to statistical relations we observed. The road towards shifting from solid empirical models towards "principles of software evolution" will likely be long and difficult, therefore we should prepare ourselves to traverse it and go as far as possible with limited damages. To do this, we need to carefully prepare our traveling equipment by paying attention at: (i) combining quantitative studies with qualitative studies, surveys, and informal interviews, (ii) relating social relations among developers with variables observed on the project, (iii) using proper statistical and machine learning techniques able to capture the temporal relation among different events, and (iv) making a massive use of natural language processing and text mining among the various sources of information available.
Starting Page	2
Ending Page	2
Page Count	1
ISBN	9781450301282
DOI	10.1145/1862372.1862375
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-09-20
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Qualitative research Software evolution Empirical studies
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

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