| Project/Area Number |
26330077
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Software
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|---|
| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
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| Project Period (FY) |
2014-04-01 – 2019-03-31
|
| Project Status |
Completed (Fiscal Year 2018)
|
| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2014: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | ソフトウェア保守 / ソフトウェア追跡性 / 追跡子 / ハッシュ値 |
|---|
| Outline of Final Research Achievements |
In software development, it is crucially important to effectively capture, record and maintain traceability links in a lightweight way. Most of previous work are retrospective approaches based on information retrieval techniques, but they are likely to generate many false positive traceability links. Unlike retrospective approaches, this work proposes a novel lightweight prospective approach, which we call TCC (tracer-carrying code). TCC uses a hash value as a tracer (global ID), widely used in distributed version control systems like Git. TCC automatically embeds a TCC tracer into source code as a side-effect of users' copy&paste operation, so users have no need to explicitly handle tracers (e.g., users have no need to copy&pastes URLs). TCC also caches the referred original text into Git repository. Thus, users can always view the original text later by simply clicking the tracer, even after its URL or file path is changed, or the original text is modified or removed.
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| Academic Significance and Societal Importance of the Research Achievements |
現代社会は多くの場面でソフトウェア技術に支えられているが，しばしばソフトウェア障害による数十億円規模の莫大な損害が出たり，場合によっては人命が危機にさらされる．本研究が提案した追跡性の技術は「ソフトウェアのある部分がなぜこうなっているのか」を辿りやすくし，ソフトウェアが正しいことを確認したり，誤りの発見を支援する技術である．莫大な損害や開発費の大幅な削減に貢献する．
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