SEKE 2012 Proceedings - Knowledge Systems Institute

Using FCA-based Change Impact Analysis for Regression Testing ∗
Xiaobing Sun, Bixin Li, Chuanqi Tao, Qiandong Zhang
School of Computer Science and Engineering, Southeast University, Nanjing, China
State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences
{sundomore, bx.li, taocq, zhangqd}@seu.edu.cn
Abstract
Software regression testing is one of the most practical
means to ensure software quality during software evolution.
Test case selection and prioritization are two effective techniques
to maximize the value of the increasing test cases,
and usually studied independently. In this paper, we integrate
these two techniques together, and finish them based
on the impact results predicted by the change impact analysis
(CIA) technique. First, we use formal concept analysis
(FCA) to predict a ranked list of impacted methods from a
set of changed classes. Then, test cases which cover these
impacted methods are included in the new test suite. As
each method predicted by the CIA is assigned with an impact
factor (IF) value corresponding to the probability of
this method to be impacted, test cases are ordered according
to the IF values of the individual methods. Initial empirical
study demonstrates the effectiveness of our regression
testing approach.
1 Introduction
Software change is a fundamental ingredient of software
maintenance. Changes made to software will inevitably
have some unpredicted and undesirable effects on other
parts of the software, thus may induce some faults to the
modified software. And new faults induced during software
maintenance can be identified and isolated by software
change impact analysis and regression testing [2, 12, 15].
Change impact analysis (CIA) is an approach to identify
potential ripple effects caused by changes made to software
[2, 10]. And whether these potential effects inject
∗ This work is supported partially by National Natural Science Foundation
of China under Grant No. 60973149, partially by the Open Funds of
State Key Laboratory of Computer Science of Chinese Academy of Sciences
under Grant No. SYSKF1110, partially by Doctoral Fund of Ministry
of Education of China under Grant No. 20100092110022, partially
by the Scientific Research Foundation of Graduate School of Southeast
University under Grant No. YBJJ1102.
faults into the software is often checked by software regression
testing. Regression testing is one of the most practical
means of ensuring software quality during software evolution.
It is used to provide confidence that: 1) the modified
parts of the program can run consistently with the new
system, and 2) the unmodified parts are not affected by the
modifications and can behave correctly as before. To date,
anumber of different approaches have been studied to regression
testing [15], such as test case selection and test
case prioritization. On the one hand, test case selection is
used to reduce testing cost by selecting a subset of test cases
from original test suite that are necessary to test the modified
software [8, 12]. On the other hand, test case prioritization
is used to identify an ‘ideal’ ordering of test cases to
yield benefits such as earlier feedback to testers and earlier
fault detection [11].
While the research community has made considerable
progress in regression testing areas, one important problem
was overlooked, that is, most current regression testing
techniques are proposed standalone, for example, some focused
on test case selection [13, 8] while some on test case
prioritization [4, 5], and they are usually studied independently.
But in practice, test case selection and prioritization
are performed together to generate a ranked list of test cases
to be directly used. This paper is proposed to address this
lack by combining test case selection and prioritization together.
In our study, we use CIA to support regression testing
activity. The CIA computes a ranked list of impacted
methods from a set of changed classes based on the formal
concept analysis (FCA) technique. And each method in the
impact results is assigned with an impact factor (IF) value,
which corresponds to the probability of this method to be
impacted. On the one hand, test cases are selected based on
the coverage information of these impacted methods; on the
other hand, test cases are ordered based on the probability
of the method to be impacted. And these two procedures are
integrated together and performed through only a round.
This paper is organized as follows: in the next section,
we introduce the FCA-based CIA technique. Section 3
presents our regression testing approach. In Section 4, em-
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