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2017 IEEE 24th International Conference on Software Analysis, Evolution, and Reengineering (SANER),
February 20-24, 2017,
Klagenfurt, Austria
Industrial Research
Fri, Feb 24, 11:00 - 12:30
Bringing Back-in-Time Debugging Down to the Database
Arian Treffer,
Michael Perscheid, and Matthias Uflacker
(HPI, Germany; SAP, Germany)
With back-in-time debuggers, developers
can explore what happened before observable failures
by following infection chains back to their root causes.
While there are several such debuggers for object-
oriented programming languages, we do not know
of any back-in-time capabilities at the database-level.
Thus, if failures are caused by SQL scripts or stored
procedures, developers have difficulties in understand-
ing their unexpected behavior.
In this paper, we present an approach for bringing
back-in-time debugging down to the SAP HANA in-
memory database. Our TARDISP debugger allows de-
velopers to step queries backwards and inspecting the
database at previous and arbitrary points in time. With
the help of a SQL extension, we can express queries
covering a period of execution time within a debugging
session and handle large amounts of data with low over-
head on performance and memory. The entire approach
has been evaluated within a development project at
SAP and shows promising results with respect to the
gathered developer feedback.
@InProceedings{SANER17p521,
author = {Arian Treffer and Michael Perscheid and Matthias Uflacker},
title = {Bringing Back-in-Time Debugging Down to the Database},
booktitle = {Proc.\ SANER},
publisher = {IEEE},
pages = {521--525},
doi = {},
year = {2017},
}
Performance Tuning for Automotive Software Fault Prediction
Harald Altinger, Steffen Herbold, Friederike Schneemann,
Jens Grabowski, and Franz Wotawa
(Audi Electronics Venture, Germany; University of Göttingen, Germany; Graz University of Technology, Austria)
Fault prediction on high quality industry grade software often suffers from strong imbalanced class distribution due to a low bug rate. Previous work reports on low predictive performance, thus tuning parameters is required. As the State of the Art recommends sampling methods for imbalanced learning, we analyse effects when under- and oversampling the training data evaluated on seven different classification algorithms. Our results demonstrate settings to achieve higher performance values but the various classifiers are influenced in different ways. Furthermore, not all performance reports can be tuned at the same time.
@InProceedings{SANER17p526,
author = {Harald Altinger and Steffen Herbold and Friederike Schneemann and Jens Grabowski and Franz Wotawa},
title = {Performance Tuning for Automotive Software Fault Prediction},
booktitle = {Proc.\ SANER},
publisher = {IEEE},
pages = {526--530},
doi = {},
year = {2017},
}
Business Process Recovery Based on System Log and Information of Organizational Structure
Ryota Mibe, Tadashi Tanaka,
Takashi Kobayashi, and Shingo Kobayashi
(Hitachi, Japan; Tokyo Institute of Technology, Japan; Japan EXpert Clone, Japan)
In most current cases of enterprise system development, the requirement specifications should follow those of an existing legacy system. However, it is difficult to identify high-level specifications, such as business process steps, from legacy and undocumented systems. In this paper, we propose a method to recover an abstract business process by using system logs and the organizational information of the operators using an existing legacy system. Our method provides a hierarchical view based on a clustering technique to find abstract activities that consist of a series of operations. We also propose a method to extract the main operation in a cluster. We evaluated the effectiveness of our method through experiments on a real system.
@InProceedings{SANER17p531,
author = {Ryota Mibe and Tadashi Tanaka and Takashi Kobayashi and Shingo Kobayashi},
title = {Business Process Recovery Based on System Log and Information of Organizational Structure},
booktitle = {Proc.\ SANER},
publisher = {IEEE},
pages = {531--535},
doi = {},
year = {2017},
}
Multi-language Re-documentation to Support a COBOL to Java Migration Project
Bernhard Dorninger, Michael Moser, and
Josef Pichler
(Software Competence Center Hagenberg, Austria)
Software migration projects need precise and up-to-date documentation of the software system to be migrated. Missing or outdated documentation hampers the migration process and compromises the overall quality of the resulting new software system. Moreover, if documentation is missing in the first place and no additional effort is undertaken to document the new software system, future maintenance and evolution tasks are burdened right from the beginning. Therefore, we apply an automatic re-documentation approach that uses a single tool chain to generate documentation for the software to be migrated and the transformed software system. By this, we not only support an ongoing COBOL to Java migration project at one of our industry partners but as well create the foundations to continuously generate up-to-date documentation for the new software system.
@InProceedings{SANER17p536,
author = {Bernhard Dorninger and Michael Moser and Josef Pichler},
title = {Multi-language Re-documentation to Support a COBOL to Java Migration Project},
booktitle = {Proc.\ SANER},
publisher = {IEEE},
pages = {536--540},
doi = {},
year = {2017},
}
Proactive Reviews of Textual Requirements
Vard Antinyan and Miroslaw Staron
(University of Gothenburg, Sweden)
In large software development products the number of textual requirements can reach tens of thousands. When such a large number of requirements is delivered to software developers, there is a risk that vague or complex requirements remain undetected until late in the design process. In order to detect such requirements, companies conduct manual reviews of requirements. Manual reviews, however, take substantial amount of effort, and the efficiency is low. The goal of this paper is to present the application of a method for proactive requirements reviews. The method, that was developed and evaluated in a previous study, is now used in three companies. We show how the method evolved from an isolated scripted use to a fully integrated use in the three companies. The results showed that software engineers in the three companies use the method as a help in their job for continuous improvements of requirements.
@InProceedings{SANER17p541,
author = {Vard Antinyan and Miroslaw Staron},
title = {Proactive Reviews of Textual Requirements},
booktitle = {Proc.\ SANER},
publisher = {IEEE},
pages = {541--545},
doi = {},
year = {2017},
}
Data Access Visualization for Legacy Application Maintenance
Keisuke Yano and Akihiko Matsuo
(Fujitsu Labs, Japan)
Software clustering techniques have been studied and applied to
analyze and visualize the actual structure of legacy applications,
which have used program information, e.g., dependencies, as
input. However, business data also play an important role in a business
system. Revealing which programs actually use data in the current
system can give us a key insight when analyzing a long-lived
complicated system. In this paper, we calculate indexes indicating how
a data entity is used, making use of software clustering, which can be
used to detect problematic or characteristic parts of the system. The
developed technique can reveal the characteristics of a data entity;
i.e., it is used like master data. We applied this technique to
two business systems used for many years and found that our technique can help
us understand the systems in terms of business data
usage. Through case studies, we evaluated the validity of the
indexes and showed that software visualization with the indexes
can be used to investigate a system in an exploratory way.
@InProceedings{SANER17p546,
author = {Keisuke Yano and Akihiko Matsuo},
title = {Data Access Visualization for Legacy Application Maintenance},
booktitle = {Proc.\ SANER},
publisher = {IEEE},
pages = {546--550},
doi = {},
year = {2017},
}
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