Change Impact Analysis by Concept Propagation

سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 228

فایل این مقاله در 6 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_JCSE-5-1_005

تاریخ نمایه سازی: 21 فروردین 1400

چکیده مقاله:

Software maintenance is an important phase of the software life cycle. An important task in this phase is to locate code fragments affected by user change requests. However, performing this task manually is costly and requires prior knowledge of the software structure. In previous studies, Latent Semantic Indexing (LSI) has been applied to map the user change queries to the relevant code segments automatically. However, due to the lack of domain knowledge embedded in the source code, LSI might be unable to perform this mapping accurately. In this paper, we have proposed a domain knowledge propagation method to obtain more relevant impact set for each change request. This method spreads the user interface originated domain knowledge to the program classes according to the program dependency graph. The proposed method has been applied to ArgoUML case-study which is an open-source project associated with its change requests. It was observed that applying the concept propagation resulted in 5% increase in the accuracy of the plain LSI method.

نویسندگان

Zeinab mahzoon

Shiraz university of technology , Shiraz , Iran

Omid Bushehrian

Shiraz university of Technology Shiraz Iran

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • B. Li, X. Sun, H. Leung, and S. Zhang. A survey of code-based change ...
  • A. Marcus, A. Sergeyev, V. Rajlich, and J.I. Maletic. An Information Retrieval Approach ...
  • G. Canfora and L. Cerulo. Impact Analysis by Mining Software and Change ...
  • M. Torchiano and F. Ricca. Impact analysis by means of unstructured knowledge ...
  • C. D. Manning, P. Raghavan, and H. Schütze. Introduction to information retrieval. Cambridge ...
  • S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman. Indexing ...
  • C. Gupta, S. Yogesh, and D. S. Chauhan. Dependency based process model for ...
  • D. M.German, A. E.Hassan, and G. Robles. Change Impact Graphs: Determining the Impact ...
  • E. Ufuktepe and T. Tuglular. A Program Slicing-Based Bayesian Network Model for ...
  • C. Carrillo and R. Capilla. Ripple effect to evaluate the impact of ...
  • R. Wen, D. Gilbert, M. G. Roche, and S. McIntosh. BLIMP Tracer: Integrating Build ...
  • L. B. Cuong, V. S. Nguyen, D. A. Nguyen, P. N. Hung, and D. H. ...
  • L. Badri, M. Badri, and D. St-Yves. Supporting predictive change impact analysis: a ...
  • D. Poshyvanyk, A. Marcus, R. Ferenc, and T. Gyimóthy. Using information retrieval based coupling ...
  • A.E. Hassan and R.C. Holt. Predicting Change Propagation in Software ...
  • I. S. Wiese, R. Ré, I. Steinmacher, R. T. Kuroda, G. A. Oliva, C. Treude, and ...
  • D. Falessi, J. Roll, J. Guo, and J. Cleland-Huang. Leveraging Historical Associations between Requirements ...
  • J. Novacek, A. Ahari, A. Cornaglia, F. Haxel, A. Viehl, O. Bringmann, and Wo. Rosenstiel. Ontology-Supported ...
  • A. Parashar and J. K. Chhabra. Assessing Impact of Class Change by ...
  • N. Alhindawi, N. Dragan, M. L. Collard, and J. I. Maletic. Improving Feature Location ...
  • B. Dit and M. Revelleand M. Gethersand D. Poshyvanyk. Feature location in source ...
  • نمایش کامل مراجع