Dependency-Based Extraction of Conditional Statements for Understanding Business Rules

Tomomi HATANO; Takashi ISHIO; Joji OKADA; Yuji SAKATA; Katsuro INOUE

doi:10.1587/transinf.2015EDP7202

Dependency-Based Extraction of Conditional Statements for Understanding Business Rules

Tomomi HATANO, Takashi ISHIO, Joji OKADA, Yuji SAKATA, Katsuro INOUE

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For the maintenance of a business system, developers must understand the business rules implemented in the system. One type of business rules defines computational business rules; they represent how an output value of a feature is computed from the valid inputs. Unfortunately, understanding business rules is a tedious and error-prone activity. We propose a program-dependence analysis technique tailored to understanding computational business rules. Given a variable representing an output, the proposed technique extracts the conditional statements that may affect the computation of the output. To evaluate the usefulness of the technique, we conducted an experiment with eight developers in one company. The results confirm that the proposed technique enables developers to accurately identify conditional statements corresponding to computational business rules. Furthermore, we compare the number of conditional statements extracted by the proposed technique and program slicing. We conclude that the proposed technique, in general, is more effective than program slicing.

Publication: IEICE TRANSACTIONS on Information Vol.E99-D No.4 pp.1117-1126

Publication Date: 2016/04/01

Publicized: 2016/01/08

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2015EDP7202

Type of Manuscript: PAPER

Category: Software Engineering

Authors

Tomomi HATANO
  Osaka University
Takashi ISHIO
  Osaka University
Joji OKADA
  NTT DATA Corporation
Yuji SAKATA
  NTT DATA Corporation
Katsuro INOUE
  Osaka University

Keyword

static analysis, control-flow analysis, data-dependence analysis, reverse engineering, Java

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Tomomi HATANO, Takashi ISHIO, Joji OKADA, Yuji SAKATA, Katsuro INOUE, "Dependency-Based Extraction of Conditional Statements for Understanding Business Rules" in IEICE TRANSACTIONS on Information, vol. E99-D, no. 4, pp. 1117-1126, April 2016, doi: 10.1587/transinf.2015EDP7202.
Abstract: For the maintenance of a business system, developers must understand the business rules implemented in the system. One type of business rules defines computational business rules; they represent how an output value of a feature is computed from the valid inputs. Unfortunately, understanding business rules is a tedious and error-prone activity. We propose a program-dependence analysis technique tailored to understanding computational business rules. Given a variable representing an output, the proposed technique extracts the conditional statements that may affect the computation of the output. To evaluate the usefulness of the technique, we conducted an experiment with eight developers in one company. The results confirm that the proposed technique enables developers to accurately identify conditional statements corresponding to computational business rules. Furthermore, we compare the number of conditional statements extracted by the proposed technique and program slicing. We conclude that the proposed technique, in general, is more effective than program slicing.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015EDP7202/_p

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@ARTICLE{e99-d_4_1117,
author={Tomomi HATANO, Takashi ISHIO, Joji OKADA, Yuji SAKATA, Katsuro INOUE, },
journal={IEICE TRANSACTIONS on Information},
title={Dependency-Based Extraction of Conditional Statements for Understanding Business Rules},
year={2016},
volume={E99-D},
number={4},
pages={1117-1126},
abstract={For the maintenance of a business system, developers must understand the business rules implemented in the system. One type of business rules defines computational business rules; they represent how an output value of a feature is computed from the valid inputs. Unfortunately, understanding business rules is a tedious and error-prone activity. We propose a program-dependence analysis technique tailored to understanding computational business rules. Given a variable representing an output, the proposed technique extracts the conditional statements that may affect the computation of the output. To evaluate the usefulness of the technique, we conducted an experiment with eight developers in one company. The results confirm that the proposed technique enables developers to accurately identify conditional statements corresponding to computational business rules. Furthermore, we compare the number of conditional statements extracted by the proposed technique and program slicing. We conclude that the proposed technique, in general, is more effective than program slicing.},
keywords={},
doi={10.1587/transinf.2015EDP7202},
ISSN={1745-1361},
month={April},}

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TY - JOUR
TI - Dependency-Based Extraction of Conditional Statements for Understanding Business Rules
T2 - IEICE TRANSACTIONS on Information
SP - 1117
EP - 1126
AU - Tomomi HATANO
AU - Takashi ISHIO
AU - Joji OKADA
AU - Yuji SAKATA
AU - Katsuro INOUE
PY - 2016
DO - 10.1587/transinf.2015EDP7202
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2016
AB - For the maintenance of a business system, developers must understand the business rules implemented in the system. One type of business rules defines computational business rules; they represent how an output value of a feature is computed from the valid inputs. Unfortunately, understanding business rules is a tedious and error-prone activity. We propose a program-dependence analysis technique tailored to understanding computational business rules. Given a variable representing an output, the proposed technique extracts the conditional statements that may affect the computation of the output. To evaluate the usefulness of the technique, we conducted an experiment with eight developers in one company. The results confirm that the proposed technique enables developers to accurately identify conditional statements corresponding to computational business rules. Furthermore, we compare the number of conditional statements extracted by the proposed technique and program slicing. We conclude that the proposed technique, in general, is more effective than program slicing.
ER -