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Comparison of different impact analysis methods and programmer's opinion: an empirical study

Authors:

Gabriella Tóth,

Péter Hegedűs,

Árpád Beszédes,

Tibor Gyimóthy,

Judit JászAuthors Info & Claims

PPPJ '10: Proceedings of the 8th International Conference on the Principles and Practice of Programming in Java

Pages 109 - 118

https://doi.org/10.1145/1852761.1852777

Published: 15 September 2010 Publication History

Abstract

In change impact analysis, obtaining guidance from automatic tools would be highly desirable since this activity is generally seen as a very difficult program comprehension problem. However, since the notion of an 'impact set' (or dependency set) of a specific change is usually very inexact and context dependent, the approaches and algorithms for computing these sets are also very diverse producing quite different results. The question 'which algorithm finds program dependencies in the most efficient way?' has been preoccupying researchers for a long time, but there are still very few results published on the comparison of the different algorithms to what programmers think are real dependencies. In this work, we report on our experiment conducted with this goal in mind using a compact, easily comprehensible Java experimental software system, simulated program changes, and a group of programmers who were asked to perform impact analysis with the help of different tools and on the basis of their programming experience. We show which algorithms turned out to be the closest to the programmers' opinion in this case study. However, the results also certified that most existing algorithms need to be further enhanced and an effective methodology to use automated tools to support impact analysis still needs to be found.

References

[1]

}}The BEFRIEND homepage. http://www.inf.u-szeged.hu/befriend/.

[2]

}}JRipples tool for Incremental Change. http://jripples.sourceforge.net/.

[3]

}}IEEE std 610.12-1990: IEEE standard glossary of software engineering terminology, 1990.

[4]

}}G. Antoniol, V. F. Rollo, and G. Venturi. Detecting groups of co-changing files in cvs repositories. In IWPSE '05: Proceedings of the Eighth International Workshop on Principles of Software Evolution, pages 23--32, Washington, DC, USA, 2005. IEEE Computer Society. ISBN 0-7695-2349-8.

Digital Library

[5]

}}R. S. Arnold and S. A. Bohner. Impact analysis - towards a framework for comparison. In ICSM '93: Proceedings of the Conference on Software Maintenance, pages 292--301, Washington, DC, USA, 1993. IEEE Computer Society. ISBN 0-8186-4600-4.

Digital Library

[6]

}}R. S. Arnold and S. A. Bohner. Software Change Impact Analysis. IEEE Computer Society Press, Los Alamitos, CA, USA, 1996. ISBN 0818673842.

Digital Library

[7]

}}V. R. Basili, G. Caldiera, and H. D. Rombach. The goal question metric approach. In Encyclopedia of Software Engineering. Wiley, 1994.

[8]

}}Á. Beszédes, T. Gergely, J. Jász, G. Tóth, T. Gyimóthy, and V. Rajlich. Computation of static execute after relation with applications to software maintenance. In Proceedings of the 2007 IEEE International Conference on Software Maintenance (ICSM'07), pages 295--304. IEEE Computer Society, Oct. 2007.

[9]

}}J. Bible, G. Rothermel, and D. S. Rosenblum. A comparative study of coarse- and fine-grained safe regression test-selection techniques. ACM Trans. Softw. Eng. Methodol., 10(2):149--183, 2001. ISSN 1049-331X.

Digital Library

[10]

}}S. A. Bohner. Impact analysis in the software change process: a year 2000 perspective. In ICSM '96: Proceedings of the 1996 International Conference on Software Maintenance, pages 42--51, Washington, DC, USA, 1996. IEEE Computer Society. ISBN 0-8186-7677-9.

Digital Library

[11]

}}B. Breech, M. Tegtmeyer, and L. Pollock. A comparison of online and dynamic impact analysis algorithms. In CSMR '05: Proceedings of the Ninth European Conference on Software Maintenance and Reengineering, pages 143--152, Washington, DC, USA, 2005. IEEE Computer Society. ISBN 0-7695-2304-8.

Digital Library

[12]

}}J. Buckner, J. Buchta, M. Petrenko, and V. Rajlich. JRipples: A tool for program comprehension during incremental change. In IWPC, pages 149--152, 2005.

Digital Library

[13]

}}J. Cohen. A coefficient of agreement for nominal scales. Psychological Bulletin, 20:37--46, 1960.

[14]

}}L. J. Fülöp, R. Ferenc, and T. Gyimóthy. Towards a Benchmark for Evaluating Design Pattern Miner Tools. In Proceedings of the 12th European Conference on Software Maintenance and Reengineering (CSMR 2008). IEEE Computer Society, Apr. 2008.

Digital Library

[15]

}}L. J. Fülöp, P. Hegedűs, R. Ferenc, and T. Gyimóthy. Towards a Benchmark for Evaluating Reverse Engineering Tools. In Tool Demonstrations of the 15th Working Conference on Reverse Engineering (WCRE 2008), Oct. 2008.

Digital Library

[16]

}}L. J. Fülöp, P. Hegedűs, and R. Ferenc. BEFRIEND - a Benchmark for Evaluating Reverse Engineering Tools, accepted, to appear. Periodica Polytechnica, 2009.

[17]

}}D. M. German, A. E. Hassan, and G. Robles. Change impact graphs: Determining the impact of prior codechanges. Information and Software Technology, 51(10):1394--1408, 2009. ISSN 0950-5849. Source Code Analysis and Manipulation, SCAM 2008.

Digital Library

[18]

}}A. E. Hassan and R. C. Holt. Predicting change propagation in software systems. In ICSM '04: Proceedings of the 20th IEEE International Conference on Software Maintenance, pages 284--293, Washington, DC, USA, 2004. IEEE Computer Society. ISBN 0-7695-2213-0.

Digital Library

[19]

}}S. Horwitz, T. Reps, and D. Binkley. Interprocedural slicing using dependence graphs. ACM Transactions on Programming Languages and Systems, 12(1):26--61, 1990.

Digital Library

[20]

}}INDUS Homepage. Indus project: Java program slicer and static analyses tools. http://indus.projects.cis.ksu.edu/. URL http://indus.projects.cis.ksu.edu/.

[21]

}}J. Jász, Á. Beszédes, T. Gyimóthy, and V. Rajlich. Static execute after/before as a replacement of traditional software dependencies. In Proceedings of the 2008 IEEE International Conference on Software Maintenance (ICSM'08), pages 137--146. IEEE Computer Society, Oct. 2008.

[22]

}}B. A. Kitchenham, S. L. Pfleeger, L. M. Pickard, P. W. Jones, D. C. Hoaglin, K. E. Emam, and J. Rosenberg. Preliminary guidelines for empirical research in software engineering. IEEE Trans. Softw. Eng., 28(8):721--734, 2002. ISSN 0098-5589.

Digital Library

[23]

}}M. Lindvall and K. Sandahl. How well do experienced software developers predict software change? J. Syst. Softw., 43(1):19--27, 1998. ISSN 0164--1212.

Digital Library

[24]

}}A. Orso, T. Apiwattanapong, J. Law, G. Rothermel, and M. J. Harrold. An empirical comparison of dynamic impact analysis algorithms. In ICSE '04: Proceedings of the 26th International Conference on Software Engineering, pages 491--500, Washington, DC, USA, 2004. IEEE Computer Society. ISBN 0-7695-2163-0.

Digital Library

[25]

}}V. Rajlich. Intensions are a key to program comprehension. In ICPC, pages 1--9, 2009.

[26]

}}V. Rajlich and P. Gosavi. Incremental change in object-oriented programming. IEEE Software, 21:62--69, 2004. ISSN 0740-7459.

Digital Library

[27]

}}B. G. Ryder. Constructing the call graph of a program. IEEE Trans. Softw. Eng., 5(3):216--226, 1979. ISSN 0098-5589.

Digital Library

[28]

}}T. Zimmermann, P. Weißgerber, S. Diehl, and A. Zeller. Mining version histories to guide software changes. IEEE Trans. Software Eng., 31(6):429--445, 2005.

Digital Library

Cited By

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cover image ACM Other conferences

PPPJ '10: Proceedings of the 8th International Conference on the Principles and Practice of Programming in Java

September 2010

173 pages

ISBN:9781450302692

DOI:10.1145/1852761

General Chair:
Andreas Krall
Vienna University of Technology
,
Program Chair:
Hanspeter Mössenböck
Johannes Kepler University Linz

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 September 2010

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PPPJ '10: Principles and Practice of Programming in Java

September 15 - 17, 2010

Vienna, Austria

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Cited By

Eshraghian FHafezieh NFarivar Fde Cesare S(2024)AI in software programming: understanding emotional responses to GitHub CopilotInformation Technology & People10.1108/ITP-01-2023-0084Online publication date: 2-Apr-2024
https://doi.org/10.1108/ITP-01-2023-0084
Dai PWang YJin DGong YYang W(2021)An improving approach to analyzing change impact of C programsComputer Communications10.1016/j.comcom.2021.10.039Online publication date: Nov-2021
https://doi.org/10.1016/j.comcom.2021.10.039
Razzaq ALe Gear AExton CBuckley J(2019)An empirical assessment of baseline feature location techniquesEmpirical Software Engineering10.1007/s10664-019-09734-5Online publication date: 16-Jul-2019
https://doi.org/10.1007/s10664-019-09734-5
Razzaq AWasala AExton CBuckley J(2018)The State of Empirical Evaluation in Static Feature LocationACM Transactions on Software Engineering and Methodology10.1145/328098828:1(1-58)Online publication date: 5-Dec-2018
https://dl.acm.org/doi/10.1145/3280988
Malhotra MChhabra J(2018)Improved Computation of Change Impact Analysis in Software Using All Applicable DependenciesFuturistic Trends in Network and Communication Technologies10.1007/978-981-13-3804-5_27(367-381)Online publication date: 25-Dec-2018
https://doi.org/10.1007/978-981-13-3804-5_27
Steppe KChin STuck W(2017)Improving the Teaching of Software Design with Automated Modelling of Syntactic Dependencies2017 IEEE 30th Conference on Software Engineering Education and Training (CSEE&T)10.1109/CSEET.2017.31(144-151)Online publication date: Nov-2017
https://doi.org/10.1109/CSEET.2017.31
Abi-Antoun MYibin Wang Khalaj EGiang ARajlich V(2015)Impact analysis based on a global hierarchical Object Graph2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)10.1109/SANER.2015.7081832(221-230)Online publication date: Mar-2015
https://doi.org/10.1109/SANER.2015.7081832
Cai HSantelices R(2015)Abstracting Program Dependencies Using the Method Dependence GraphProceedings of the 2015 IEEE International Conference on Software Quality, Reliability and Security10.1109/QRS.2015.18(49-58)Online publication date: 3-Aug-2015
https://dl.acm.org/doi/10.1109/QRS.2015.18
Wetzlmaier TRamler R(2015)Improving Manual Change Impact Analysis with Tool Support: A Study in an Industrial ProjectSoftware Quality. Software and Systems Quality in Distributed and Mobile Environments10.1007/978-3-319-13251-8_4(47-66)Online publication date: 6-Jan-2015
https://doi.org/10.1007/978-3-319-13251-8_4
Hegedus P(2013)Revealing the Effect of Coding Practices on Software MaintainabilityProceedings of the 2013 IEEE International Conference on Software Maintenance10.1109/ICSM.2013.99(578-581)Online publication date: 22-Sep-2013
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