Combining Single-Version and Evolutionary Dependencies for Software-Change Prediction

Kagdi, Huzefa; Maletic, Jonathan I.

doi:10.1109/msr.2007.2

Cited by 15 publications

(12 citation statements)

References 16 publications

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“…Using the achieved results to cross validate each other is a potential technique to further improve impact analysis. In [104], Kagdi and Maletic further refine the idea by proposing to convert the source code into an XML representation using srcML to enable source code dependency analysis. The authors plan to use the mining tool sqminer and the diff-tool codeDiff to mine fine-grained co-changes at code level.…”

Section: ) Execution Tracesmentioning

confidence: 99%

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A taxonomy for software change impact analysis

Lehnert

2011

Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th Annual ERCIM Workshop on Softwar

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Abstract-Change impact analysis is required for constantly evolving systems to support the comprehension, implementation, and evaluation of changes. A lot of research effort has been spent on this subject over the last twenty years, and many approaches were published likewise. However, there has not been an extensive attempt made to summarize and review published approaches as a base for further research in the area. Therefore, we present the results of a comprehensive investigation of software change impact analysis, which is based on a literature review and a taxonomy for impact analysis. The contribution of this review is threefold. First, approaches proposed for impact analysis are explained regarding their motivation and methodology. They are further classified according to the criteria of the taxonomy to enable the comparison and evaluation of approaches proposed in literature. We perform an evaluation of our taxonomy regarding the coverage of its classification criteria in studied literature, which is the second contribution. Last, we address and discuss yet unsolved problems, research areas, and challenges of impact analysis, which were discovered by our review to illustrate possible directions for further research.

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Section: ) Execution Tracesmentioning

confidence: 99%

“…In a final step, both coupling information are combined to predict the impact. However, it still remains an open question whether to use the intersection or union of both as shown in earlier work of Kagdi and Maletic [104].…”

Section: ) Execution Tracesmentioning

confidence: 99%

A taxonomy for software change impact analysis

Lehnert

2011

Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th Annual ERCIM Workshop on Softwar

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“…First, some solutions are presented to support change impact analysis on specific type of systems, e.g., aspect-oriented (Zhao 2002), component-based (Mao et al 2007), and object oriented (Huang and Song 2007;Xing and Stroulia 2006). Second, many solutions are for supporting activities that facilitate change impact analysis, e.g., change prediction (Hassan and Holt 2004;Kagdi and Maletic 2007;Law and Rothermel 2003b), identification of dependence clusters and dependence pollution (Binkley and Harman 2005), dynamic impact analysis in object-oriented programs (Huang and Song 2007), identification of class change profiles (Xing and Stroulia 2006), impact of database schema change (Maule et al 2008), and efficient source code navigation (Robillard 2008). Third, a number of other solutions are presented to support change impact on development aspects such as the relation between evolvability and modularity (Breivold et al 2008), independent development (Glorie et al 2009), and requirement change impact on architectural elements (Khan et al 2008).…”

Section: Change Impact Analysismentioning

confidence: 99%

“…Change patterns are the relationships that solutions in this group characterize as dependencies. The identified historical analysis techniques include the analysis of modification requests (Cataldo et al 2008), co-change mining (Kagdi and Maletic 2007), and analysis of churn metrics (Nagappan and Ball 2007). Table 4 illustrates the application areas supported by these various techniques.…”

Section: Historical Analysismentioning

confidence: 99%

A practice-driven systematic review of dependency analysis solutions

2011

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When following architecture-driven strategies to develop large softwareintensive systems, the analysis of the dependencies is not an easy task. In this paper, we report a systematic literature review on dependency analysis solutions. Dependency analysis concerns making dependencies due to interconnections between programs or system components explicit. The review is practice-driven because its research questions, execution, and reporting were influenced by the practice of a group of software architects at Philips Healthcare MRI. The review results in an overview and assessment of the state-of-the-art and applicability of dependency analysis. The overview provides insights about definitions related to dependency analysis, the sort of development activities that need dependency analysis, and the classification and description of a number of dependency analysis solutions. The contribution of this paper is for both practitioners and researchers. They can take it as a reference to learn about dependency analysis, match their own practice to the presented results, and to build similar overviews of other techniques and methods for other domains or types of systems.

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“…Predicting future changes is one of the primary applications of such transactions [12], [16]. Kagdi and Maletic [9] combine the evolutionary dependencies derived from transactions with static dependency couplings to further improve the prediction of future changes. Shiraban et al [17] predict changes by using artificial intelligence techniques on the transactions, whereas in [16] and in [18] rule mining is applied on the same type of input.…”

Section: Using Transactionsmentioning

confidence: 99%

Approximating Change Sets at Philips Healthcare: A Case Study

Vanya¹,

Premraj²,

Vliet³

2011

2011 15th European Conference on Software Maintenance and Reengineering

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Abstract-A single development task such as solving a bug or implementing a new feature often involves changing a number of entities, also known together as a change set. Change sets can be approximated from the version control system. They are then used by the architects and developers to take important decisions. So change sets need to be approximated carefully. It is common to assume that two entities checked-in less than a small time interval from each other, and having the same meta-data associated with them, belong to the same transaction. Transactions may be good approximations of change sets if developers commit change sets in one go and if the required meta-data is available. This is however not the case in the industrial environment (Philips Healthcare) we study. Our paper presents a case study in which we investigated how change sets can be approximated in an environment with a complex workflow and limited meta-data in the version repositories. We found that, dependent on the commit practices used, a suitable time intervals between check-in timestamps of files has to be determined and leveraged to reliably approximate change sets.

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Combining Single-Version and Evolutionary Dependencies for Software-Change Prediction

Abstract: Abstract

Cited by 15 publications

References 16 publications

A taxonomy for software change impact analysis

A taxonomy for software change impact analysis

A practice-driven systematic review of dependency analysis solutions

Approximating Change Sets at Philips Healthcare: A Case Study

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