Feature location in COBOL mainframe systems: An experience report

Geet, Joris Van; Demeyer, Serge

doi:10.1109/icsm.2009.5306312

Cited by 7 publications

(5 citation statements)

References 8 publications

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“… compared a number of approaches on industrial software. In addition to these studies, Van Geet and Demeyer report on their experiences of applying Eisenbarth et al . 's formal concept analysis of execution traces FLT in an industrial setting.…”

Section: Feature Location Tools and Studiesmentioning

confidence: 99%

“…As previously discussed, TraceGraph was used in an industrial setting [101], and Wilde et al [4] compared a number of approaches on industrial software. In addition to these studies, Van Geet and Demeyer [129] report on their experiences of applying Eisenbarth et al's [7] formal concept analysis of execution traces FLT in an industrial setting. The context was a pre-study phase for the migration of a banking system written in COBOL.…”

Section: Industrial Case Studiesmentioning

confidence: 99%

See 1 more Smart Citation

Feature location in source code: a taxonomy and survey

Dit¹,

Revelle²,

Gethers³

et al. 2011

J Software Evolu Process

433

395

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________________________________________________________________________Feature location is the activity of identifying an initial location in the source code that implements functionality in a software system. Many feature location techniques have been introduced that automate some or all of this process, and a comprehensive overview of this large body of work would be beneficial to researchers and practitioners. This paper presents a systematic literature survey of feature location techniques. Eighty-nine articles from 25 venues have been reviewed and classified within the taxonomy in order to organize and structure existing work in the field of feature location. The paper also discusses open issues and defines future directions in the field of feature location.

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Section: Feature Location Tools and Studiesmentioning

confidence: 99%

Section: Industrial Case Studiesmentioning

confidence: 99%

Feature location in source code: a taxonomy and survey

Dit¹,

Revelle²,

Gethers³

et al. 2011

J Software Evolu Process

433

395

View full text Add to dashboard Cite

show abstract

“…Additionally, some other approaches were also proposed for specific system models, like for mainframe [14], distributed system [12], SOA [13], etc. However, they are limited by specific applications.…”

Section: Related Workmentioning

confidence: 99%

Feature Location in Source Code by Trace-Based Impact Analysis and Information Retrieval

Cai

Yang

Wang

et al. 2012

IEICE Trans. Inf. & Syst.

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Feature location is to identify source code that implements a given feature. It is essential for software maintenance and evolution. A large amount of research, including static analysis, dynamic analysis and the hybrid approaches, has been done on the feature location problems. The existing approaches either need plenty of scenarios or rely on domain experts heavily. This paper proposes a new approach to locate functional feature in source code by combining the change impact analysis and information retrieval. In this approach, the source code is instrumented and executed using a single scenario to obtain the execution trace. The execution trace is extended according to the control flow to cover all the potentially relevant classes. The classes are ranked by trace-based impact analysis and information retrieval. The ranking analysis takes advantages of the semantics and structural characteristics of source code. The identified results are of higher precision than the individual approaches. Finally, two open source cases have been studied and the efficiency of the proposed approach is verified.

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“…As previously discussed, TraceGraph [133] was used in an industrial setting [133], and Wilde et al [226] compared a number of approaches on industrial software. In addition to these studies, Van Geet and Demeyer [221] report on their experiences of applying Eisenbarth et al's [76] formal concept analysis of execution traces feature location technique in an industrial setting. The context was a pre-study phase for the migration of a banking system written in COBOL.…”

Section: Industrial Case Studiesmentioning

confidence: 99%

Supporting Feature-Level Software Maintenance

Revelle

2009

2009 16th Working Conference on Reverse Engineering

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Software maintenance is the process of modifying a software system to fix defects, improve performance, add new functionality, or adapt the system to a new environment. A maintenance task is often initiated by a bug report or a request for new functionality. Bug reports typically describe problems with incorrect behaviors or functionalities. These behaviors or functionalities are known as features. Even in very well-designed systems, the source code that implements features is often not completely modularized. The delocalized nature of features makes maintaining them challenging. Since maintenance tasks are expressed in terms of features, the goal of this dissertation is to support software maintenance at the feature-level. We focus on two tasks in particular: feature location and impact analysis via feature coupling.Feature location is the process of identifying the source code that implements a feature, and it is an essential first step to any maintenance task. There are many existing techniques for feature location that incorporate various types of analyses such as static, dynamic, and textual. In this dissertation, we recognize the advantages of leveraging several types of analyses and introduce a new approach to feature location based on combining dynamic analysis, textual analysis, and web mining algorithms applied to software. The use of web mining for feature location is a novel contribution, and we show that our new techniques based on web mining are significantly more effective than the current state of the art.After using feature location to identify a feature's source code, maintenance can be completed on that feature. Impact analysis should then be performed to revalidate the system and determine which other features may have been affected by the modifications. We define three feature coupling metrics that capture the relationship between features based on structural information, textual information, and their combination. Our novel feature coupling metrics can be used for impact analysis to quantify the strength of coupling between pairs of features. We performed three empirical studies on open-source software systems to asses the feature coupling metrics and established three major results. First,

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Feature location in COBOL mainframe systems: An experience report

Cited by 7 publications

References 8 publications

Feature location in source code: a taxonomy and survey

Feature location in source code: a taxonomy and survey

Feature Location in Source Code by Trace-Based Impact Analysis and Information Retrieval

Supporting Feature-Level Software Maintenance

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