an empirical study of the evolution of eclipse third-party plug-ins

An Empirical Study of the Evolution of Eclipse Third-party Plug-ins

IWPSE-EVOL 2010, ANTWEP, BELGIUM

By: John Businge, PhD Student

Mbarara University of Science and Technology

Co-Authors: Prof. Mark van den Brand &

Dr. Alexander Serebrenik

Outline

• Introduction• Goal• Approach• Analysis & Results• Summary & Future work

Software Engineering and Technology (SET) PAGE 212-04-2023

Introduction


Plug-ins

Framework

Frameworks evolve from one release to another to improve qualityPlug-ins have two evolution processes: general and framework-

based

Component frameworks simplify the work of Software Developers

Third-party plug-in: Extend capabilities of a framework and reuse the functionality of a framework

Goal

• Applicability of traditional results on software evolution to constrained evolution of Eclipse plug-ins

• Specifically, we take the first step and investigate Lehman’s laws of software evolution on the constrained evolution of the Eclipse third-party plug-ins.


Approach (1) – Selected Plug-ins

• More than 1,000 Eclipse plug-ins on the advertising website• Collected 21 plug-ins

• More


Approach (2) – 15 metrics Used


• Two categories of metrics:• Eclipse-based evolution - Deps• General Evolution - Tot

Lehman’s Laws of Software Evolution

• Law 1: Continuing change: Software system must be continually adapted else it becomes less satisfactory

• Law 3: Self-regulation: System will adjust its size throughout its lifetime

• Law 5: Conservation of Familiarity: Incremental growth/change tends to remain constant or to decline over time.

• Law 6: Continuing Growth: Systems usually grow over time to accommodate pressure for change.

• Law 7: Declining quality: Quality declines over time


Results…Continuing Change law (Deps)• Software system must be continually adapted else it

becomes less satisfactory


Continuing Change law (NOC-Deps)

• Confirmed


Self-Regulation law (Deps-Tot)

• System will adjust its size throughout its lifetime


Self-Regulation law (Deps-Uniq)

• Confirmed


Continuing growth law (Deps-Uniq)


• Systems usually grow over time to accommodate pressure for change.

Continuing growth law (NOC-Deps)

• Confirmed


Conservation of familiarity law (CFL)

• Incremental growth/change tends to remain constant or to decline over time.

• Statistically test this law.• We used 2 metrics to verify this law: • 1. change-rate = % of handled files (additions, deletions and

modifications), in the previous version of the plug-in as the dependent variable.

• 2. growth-rate = % of added Deps and % of added NOC in the previous version of the plug-in as the dependent variable.

• We test these two metrics as time series on the following models and state hypothesis


CFL - Hypothesis

• Change Rate:• (Handled NOC-Tot) H10: β ＞ 0, H1a: β≦0

• (Handled NOC-Deps) H20: β ＞ 0, H2a: β≦0

• Growth Rate:• (Deps) H30: β ＞ 0, H3a: β≦0

• (Handled NOC-Tot) H40: β ＞ 0, H4a: β≦0

• (Handled NOC-Deps) H50: β ＞ 0, H5a: β≦0


CFL – Results NOC change rate


CFL – Summary Results – NOC change rate

• H1-Tot - 9/15 and H2-Deps- 8/15 supporting the law.

• 2 plug-ins have increasing change rate – further analysis found that growth trend for the 2 metrics used is super-linear. Corresponds to Koch’2007 – Active revisions

• NOT CONFIRMED


CFL – Results Deps growth rate


CFL – Summary Results – Deps Growth Rate

• H3-Deps – 2/15, H4-Tot – 5/15 and H5-Deps – 6/15 supporting the law

• One plug-in had and increasing growth rate – further analysis showed that the growth trend is super-linear. This corresponds to Godfrey and Tu’2000 – Study of Linux

• NOT CONFIRMED


Declining Quality Law (DQL)

• Like CFL, we also statistically test this law.• Dn - Metric was used as the dependent variable to verify

this law.• Dn – normalized distance from the main sequence: is the

is an indicator of the package's balance between abstractness and stability

• A low value (closer to zero) of MEAN and STD of package’s Dn is an indicator of high quality.

• To obtain Dn-values, we follow Serebrenik et al. (2009).

• Plug-ins having at least 30 packages (excl. 3rd party packages) were selected. 8/21 plug-ins satisfied the requirement

• Hypothesis were stated.•


DCL – Hypotheses

• (MEANs of different packages in different plug-in versions) H60: β ≦ 0, H6a: β ＞ 0

• (STDEVs of different packages in different plug-in versions) H70: β ≦ 0, H7a: β ＞ 0


DCL - Results


Dn – SQL - Exceptional


Mar/05 Nov/05 Jul/06 Mar/07 Nov/07 Jul/08 Mar/09 Nov/090.100

0.120

0.140

0.160

0.180

Dn-SQL

MEANSTDV

DCL – Summary

• 5 / 8 plug-ins show support of the law.• 1 plug-in has both MEAN and STD decreasing.• Exceptional cases decrease in MEAN and increase in

STD - SQL

• Inconclusive


Summary and Future Work

• First step to study fine grained evolution of software systems built on component frameworks using Lehman’s laws of software evolution.

• Overall, observed trends compare to earlier research trends

• Broader study of the laws is required• Additional direction- distinguish “Good API” and

“Bad API” of the framework


Thank you for Listening


an empirical study of the evolution of eclipse third-party plug-ins

Engineering

technology set page

lifetime software engineering

continuing growth law

continuing change law

lifetime law

satisfactory law

added deps

selfregulation law depsuniq