Teknik Identifikasi Fitur Berdasarkan Kalimat Pernyataan Kebutuhan dalam Konteks Pengembangan Software Product Line
DOI:
https://doi.org/10.25126/jtiik.2022935732Abstrak
Software product line (SPL) adalah konsep software reuse di bidang industri perangkat lunak yang memiliki fase awal berupa domain engineering untuk mengidentifikasi dan memetakan fitur-fitur dari sekumpulan produk perangkat lunak yang akan dikembangkan. Fitur perangkat lunak sering kali diekspresikan secara eksplisit dalam kalimat pernyataan kebutuhan yang ada pada dokumen spesifikasi kebutuhan perangkat lunak (SRS). Saat ini, penelitian tentang otomatisasi identifikasi fitur perangkat lunak berdasarkan dokumen spesifikasi kebutuhan telah banyak diusulkan dengan berbagai metode, namun hasil yang diperoleh kebanyakan adalah kata benda yang dianggap sebagai kandidat fitur. Representasi fitur dengan kata benda dianggap masih terlalu abstrak dan tidak mewakili konsep fitur sebagai kemampuan atau fungsionalitas suatu perangkat lunak. Dalam penelitian ini, identifikasi fitur yang direpresentasikan dengan frasa gabungan kata kerja dan kata benda diusulkan karena dianggap lebih menjelaskan kemampuan dan fungsionalitas dari suatu perangkat lunak. Pola penulisan kalimat pernyataan kebutuhan dengan requirement boilerplate dimanfaatkan sebagai dasar identifikasi fitur perangkat lunak secara otomatis dengan menggunakan alat bantu pemrosesan bahasa natural atau NLP (natural language processing). Dalam penelitian ini diusulkan 4 (empat) aturan dependency parser, yang merupakan salah satu pipeline dalam NLP. Tingkat keberhasilan metode pada penelitian ini adalah antara 65% sampai dengan 88% untuk 5 kelompok kalimat pernyataan kebutuhan yang diujikan. Hasil tersebut menunjukkan bahwa metode yang diusulkan pada penelitian ini bisa mengautomasi proses identifikasi fitur pada tahapan domain engineering dalam pengembangan software product line khususnya yang menggunakan metode ekstraktif.
Abstract
Software product line (SPL) is a software reuse concept in the software industry that has an initial phase of domain engineering to identify and map the features of a set of software products to be developed. Software features are often expressed explicitly in the requirement sentences contained in the software requirements specification (SRS) document. Currently, research on the automation of software feature identification based on requirements specification documents has been proposed by various methods, but the results obtained are mostly nouns that are considered feature candidates. Representation of features with nouns is considered too abstract and does not represent the concept of features as capabilities or functionality of the software. In this study, the identification of features represented by combined phrases of verbs and nouns is proposed because it is considered to better explain the capabilities and functionality of software. The pattern of writing a requirement sentence with boilerplate requirements is used as the basis for automatically identifying software features using natural language processing (NLP) tools. In this research, 4 (four) dependency parser rules are proposed, which is one of the pipelines in NLP. The success rate of the method in this study is between 65% to 88% for the 5 groups of sentences that were tested. These results indicate that the method proposed in this study can automate the feature identification process at the domain engineering stage in product line software development, especially those using extractive methods.
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