Software Requirements Retrieval Using Use Case Terms and Structure Similarity Computation

Author(s):  
Akadej Udomchaiporn ◽  
Nakornthip Prompoon ◽  
Pizzanu Kanongchaiyos
Author(s):  
Ferdika Bagus Permana ◽  
Daniel Oranova Siahaan

Abstrak— Di dalam pengembangan perangkat lunak berskala besar, terdapat jumlah dokumen kebutuhan perangkat lunak yang sangat banyak dalam sekali proses elisitasi yang mungkin dihasilkan untuk domain yang berbeda dari setiap tim pengembang. Dokumen-dokumen ini mungkin digunakan kembali untuk mengurangi biaya dan waktu guna pengembangan perangkat lunak berikutnya. Oleh karena itu dibutuhkan suatu mekanisme untuk mendapatkan dokumen tersebut kembali yang sesuai dengan kebutuhan pengguna secara efektif dan efisien.Makalah ini mengusulkan suatu pendekatan kesamaan semantik dan struktur dalam deskripsi kasus penggunaaan guna mendapatkan kembali dokumen spesifikasi kebutuhan perangkat lunak. Dari kasus penggunaan yang didapatkan kembali tersebut kemudian dibuat suatu urutan atau ranking kesamaan kasus penggunaan berdasar suatu threshold yang telah didapatkan berdasar nilai kesepakatan tertinggi dengan pakar pada proses pengujian.Pendekatan menggunakan kesamaan semantik pada kata dan kalimat ini merupakan pendekatan yang diajukan sebagai pengganti dari pendekatan sebelumnya yaitu menggunakan term frequency dan keyword atau kata kunci. Metode ini diujicobakan pada percobaan dengan menggunakan 20 kueri deskripsi kasus penggunaan. Tiga skenario yang berbeda disusun untuk menginvestigasi nilai threshold yang ideal, mengetahui perbedaan hasil atau result set dengan pendekatan sebelumnya dan untuk mengetahui efek kombinasi struktur deskripsi kasus penggunaan pada masukan kueri terhadap hasil kueri yang didapatkan. Kata Kunci—Temu Kembali Kasus Penggunaan, Kesamaan Semantik, Sistem Temu Kembali InformasiAbstract— In software industry, there are tremendous number of software requirements documents in effect of large scale of software development. These collections of software requirements documents can be reused in order to cut off the development time and reduce the cost. There is a need to retrieve one or more of those documents which is suitable with the user’s specifications for the new software development. So, if we can retrieve many similar software requirements to a new project, development process will be less costly and less error because the retrieved software requirements can be tailored to the new case with fewer modifications. This paper presents a methodology to retrieve software requirements documents using structured base of use case description semantic similarity computation. Each element of query use case description will be calculated with the use case description in the collections or repository. The semantic similarity score is used to rank the use case in the collections and to retrieve the requirement documents to be used in the new software project development. We introduce a semantic similarity computation approach as a substitute of term frequency and keyword approach. We validate the usefulness of our method through the experiment using 20 cases. Three experiment scenarios are presented to investigate the ideal threshold value, the retrieval result differences with previous approach and to find out the effect of various combinations of structural query to the retrieval result.Keywords— Use Case Retrieval, Semantic Similarity, Information Retrieval 


2008 ◽  
Vol 14 (1) ◽  
pp. 1-14 ◽  
Author(s):  
John Mathenge Kanyaru ◽  
Keith Phalp

Author(s):  
Dušan Savić ◽  
Siniša Vlajić ◽  
Marijana Despotović-Zrakić

Applications are often multi-tier and require application servers, workflow engines, and database management systems. Cloud computing is a computing paradigm wherein the resources such as processors, storage, and software applications are provided as services via the Internet. Moving an enterprise application to the cloud can be a challenge. This application needs to be split into the components that then automatically deploy on the cloud. In this chapter, the authors introduce a way to automatically derivate the main architecture components from the software requirements that can serve as a basis for an architecture diagram in the MOCCA method. The proposed approach is model and use case driven.


Author(s):  
Deokyoon Ko ◽  
Sooyong Park ◽  
Yourim Kim ◽  
Soojin Park ◽  
Suntae Kim

Completeness in software requirements specification is one of the key factors for successful software development. For specifying software requirements, scenario-based approach is broadly used, comprising a basic flow regarding the successful use of the system, and alternative flows describing abnormal or less frequent interactions of the system. However, alternative flows tend to be frequently missed in many cases, because of the relative lower significance rather than the basic flow, which eventually have an influence on achieving the completeness of software requirements. In order to address the issue, we propose an approach for automatically recommending alternative flows from a basic flow by extracting the essential use case patterns based on the occurrence patterns of the agents and measuring the verb similarity between the main verbs of each scenario. In order to validate our approach, we apply it to three industrial case studies, and show comprehensiveness of the suggested alternative flows and synergic effectiveness for inexperienced developers.


Author(s):  
Timofejs Murenecs ◽  
Erika Asnina

Automated Derivation of Use Case Model from Topological Functioning ModelThe first important step in Model Driven Architecture software development is qualitative analysis and specification of structure and behavior of business and its supporting information system as well as software requirements. We continue the research on achieving a qualitative software requirements model, Use Case Model (UCM), based on a formal business model, Topological Functioning Model (TFM), by using formal model transformations. This paper discusses the results of implementation of the transformation from TFM to UCM by using Query/View/Transformation Relations supported by mediniQvt.


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