1. Gabatarwa & Bayyani

Wannan takarda tana gabatar da bayanai da bincike na tushe don Tsarin Girma na Yankin Mai Da Hatsari na Gudanar da API (API-m-FAMM). An ƙera wannan tsari ne don ba wa ƙungiyoyin da ke bayyana API ga masu haɓaka na ɓangare na uku tsari mai tsari don tantance, inganta, da kuma kimanta girman tsarin ayyukan kasuwancin su na gudanar da API. Ana fassara Gudanar da API a matsayin aikin da ya ƙunshi ƙira, bugawa, turawa, da ci gaba da mulkin API, gami da iyawa kamar sarrafa tsarin rayuwa, gudanar da samun dama, sa ido, ƙuntatawa, bincike, tsaro, da takaddun bayanai.

Babban ƙimar wannan bayanan yana cikin ƙaƙƙarfan hanyar samunsa ta hanyoyi da yawa, yana ba da haɗe-haɗen ra'ayi na ingantattun ayyuka masu mahimmanci don aiwatar da dabarun API mai inganci.

2. Ƙayyadaddun Bayanai & Hanyoyin Bincike

Bayanan samfur ne na ingantacciyar hanyar bincike mai matakai da yawa wacce ke tabbatar da ƙwararrun ilimi da dacewa ta aikace.

2.1 Samun Bayanai & Tushe

Yanki na Bincike: Gudanar da Fasaha da Ƙirƙira, musamman Tsarin Girma na Yankin Mai Da Hatsari don Gudanar da API.

Nau'in Bayanai: Bayanin rubutu, nassoshi na wallafe-wallafe, da teburori masu tsari waɗanda ke cikakken bayanin ayyuka da iyawa.

Tushe na Farko: Bincike na Tsari na Wallafe-wallafe (SLR) [68], wanda aka ƙara da wallafe-wallafen launin toka.

2.2 Tsarin Tattara Bayanai

Tattarawar ta bi tsari mai tsauri, mai maimaitawa:

  1. SLR na Farko & Rarrabawa: An gano ayyuka daga wallafe-wallafe kuma an rarraba su ta hanyar kamanceceniya ta jigo.
  2. Tabbatarwa na Ciki: Taron tattaunawa na masu bincike, binciken yarjejeniya tsakanin masu ƙima, da bincike.
  3. Tabbatarwa na Kwararru (tattaunawa 11): Masu aiki sun kimanta ayyuka da iyawa. An ci gaba da aiki idan aƙalla ƙwararru biyu sun ga yana da dacewa kuma yana da amfani.
  4. Gyara (tattaunawa 6): Masu bincike sun tattauna kuma suka aiwatar da ƙari, cirewa, da ƙaura.
  5. Ƙimar Ƙarshe: Ƙwararru 3 da aka riga aka yi hira da su sun kimanta tsarin da aka gyara.
  6. Tabbatar da Nazarin Lamari: An gudanar da nazarin lamari biyar akan samfuran software daban-daban don ƙimar ƙarshe.

3. Tsarin API-m-FAMM

3.1 Abubuwan Asali: Ayyuka, Iyawa, Yankuna Mai Da Hatsari

An tsara tsarin a matsayi uku na asali:

  • Ayyuka (80): Ƙananan ayyuka masu aiwatarwa da ƙungiya za ta iya aiwatarwa. Kowane aiki ana bayyana shi da lamba ta musamman, suna, bayani, sharuɗɗan aiwatarwa, da tushen wallafe-wallafe.
  • Iyawa (20): Ƙwararrun ƙwarewa na matakin sama waɗanda aka samo ta hanyar haɗa ayyuka masu alaƙa. Ana bayyana su da lamba, bayani, da tushen wallafe-wallafen zaɓi.
  • Yankuna Mai Da Hatsari (6): Yankunan gudanar da API na matakin sama, kowanne yana ƙunshe da saitin iyawa. Suna ba da jagorar dabarun don kimanta girma.

3.2 Tsarin Tsari & Matsayi

Tsarin yana bin tsari mai bayyanawa: Yankin Mai Da Hatsari → Iyawa → Aiki. Wannan tsari yana ba wa ƙungiyoyi damar zurfafa bincike daga yankunan dabarun zuwa takamaiman ayyuka masu aiwatarwa. Yankuna shida masu da hatsari (misali, suna rufe yankuna kamar Dabarun & Ƙira, Haɓakawa & Turawa, Tsaro & Mulki, Saidan & Bincike, Al'umma & Ƙwarewar Mai Haɓakawa, Gudanar da Tsarin Rayuwa) suna ba da cikakken ra'ayi game da yanayin gudanar da API.

4. Muhimman Bayanai & Taƙaitaccen Ƙididdiga

Jimlar Ayyuka

80

Abubuwan da za a iya aiwatarwa

Iyawa na Asali

20

Ƙwarewar da aka haɗa

Yankunan Dabarun Mai Da Hatsari

6

Yankunan gudanarwa na matakin sama

Tabbatar da Tattaunawar Kwararru

11+3

Zagayen tabbatarwa na ƙwararru

Babban Amfanin Aikace-aikace:

  • Masu Bincike: Don kimanta tsari, tabbatarwa, faɗaɗawa, da kafa ƙamus na fage.
  • Masu Aiki/Masu Ba da Shawara: Don kimanta cikar aiwatar da ayyuka da jagorar taswirar hanyoyin inganta girma.

5. Bincike na Asali: Ra'ayi Mai Muhimmanci na Masana'antu

Babban Bayani: API-m-FAMM ba kawai wani nau'in rarrabuwa na ilimi ba ne; tsari ne na musamman, wanda ƙwararru suka tabbatar, wanda ke haɗa gibin da ya shahara tsakanin ka'idar API da gaskiyar aiki. A cikin kasuwa da ke cike da tsare-tsare na musamman na mai siyarwa (kamar na Google's Apigee ko tsarin girma na MuleSoft), wannan aikin yana ba da tushe marar son kai, wanda ya dogara da shaida. Ƙarfinsa—wanda ke daidaitawa da tsarin hanyoyin da ake gani a cikin SLR na tushe a cikin injiniyan software kamar na Kitchenham da sauransu—shine babban kadarsa. Duk da haka, gwajinsa na gaskiya baya cikin ginin sa amma a cikin karɓarsa a kan tsarin ƙungiyoyi masu tsauri, sau da yawa masu keɓancewa.

Tsarin Hankali: Hankalin tsarin yana da ƙarfi sosai: raba babbar matsalar "gudanar da API" zuwa Yankuna Mai Da Hatsari ("abin da"), ayyana Iyawa a cikinsu ("yadda da kyau"), da ƙayyadaddun Ayyuka ("yadda"). Wannan yana kama da hanyar Manufa-Tambaya-Ma'auni (GQM) da ake amfani da ita a cikin injiniyan software mai ma'auni. Tsarin tabbatarwa—daga wallafe-wallafe zuwa yarjejeniyar ƙwararru zuwa nazarin lamari—yana da ƙarfi, kama da matakan tabbatarwa da yawa da ake amfani da su wajen haɓaka tsarin SPICE ko CMMI.

Ƙarfi & Kurakurai: Babban ƙarfinsa shine tushensa na zahiri. Ba kamar yawancin tsarin girma waɗanda ke da ra'ayi ko kuma sun dogara da ƙananan nazarin lamari ba, ayyukan 80 na API-m-FAMM an samo su ne daga faɗaɗaɗɗen wallafe-wallafe kuma ƙwararru 11+3 sun amince da su. Wannan yana ba shi aminci nan take. Babban aibi, duk da haka, yana cikin fahimta: tsarin yana ɗaukan matakin haɗin kai na ƙungiya da dabarun mai da hankali kan API waɗanda yawancin kamfanoni ba su da shi. Yana zana inda za a je amma yana da sauƙi akan kayan aikin sarrafa canji da ake buƙata don tafiya—suka na gama gari na tsarin girma da masu bincike kamar Paulk da Becker suka haskaka. Bugu da ƙari, yayin da aka jera ayyukan, haɗin kai, jerin aiwatarwa, da cinikin albarkatu ba a ƙirƙira su a fili ba, waɗanda ke da mahimmanci don tsara taswirar hanyar aiki.

Bayanai masu Aiwatarwa: Ga shugabanni, babban ƙimar tsarin shine kayan aikin bincike da fifiko. Kada ku yi ƙoƙarin aiwatar da dukkan ayyuka 80 lokaci ɗaya. Yi amfani da Yankuna Mai Da Hatsari 6 don gano mafi girman matsalolin ƙungiyar ku (misali, Tsaro ne ko Ƙwarewar Mai Haɓakawa?). Sa'an nan, ku kimanta girma a cikin wannan yanki ta amfani da takamaiman ayyuka a matsayin lissafin bincike. Wannan hanya mai niyya tana daidaitawa da ra'ayin "ci gaba da matakai" da aka tattauna a cikin ISO/IEC 330xx. Bayanan farko ne don gina tsarin ingantawa na musamman, wanda ke jagorantar ma'auni. Mataki na gaba ga kowace ƙungiya ya kamata su rufe wannan tsarin tare da ma'aunin amfani da API da kansu da manufofin kasuwanci don ƙirƙirar ƙididdigar girma mai nauyi, mai da hankali kan yanayi.

6. Cikakkun Bayanai na Fasaha & Tsarin Bincike

6.1 Ƙididdigar Girma & Tsarin Ƙima

Duk da yake PDF ba ta ƙayyade algorithm na maki ba, ana iya ƙayyade ƙimar tsarin girma na yau da kullun. Ana iya samun matakin girma $M_{FA}$ don Yankin Mai Da Hatsari $FA$ daga matsayin aiwatar da ayyukansa. Hanyar maki mai sauƙi mai nauyi zata iya zama:

$M_{FA} = \frac{\sum_{i=1}^{n} w_i \cdot s_i}{\sum_{i=1}^{n} w_i} \times L_{max}$

Inda:

  • $n$ shine adadin ayyuka a cikin Yankin Mai Da Hatsari.
  • $w_i$ shine nauyin (mahimmanci) na aiki $i$ (za a iya samo shi daga ƙimar ƙwararru).
  • $s_i$ shine makin aiwatarwa don aiki $i$ (misali, 0=Ba a aiwatar ba, 0.5=Wani ɓangare, 1=Cikakke).
  • $L_{max}$ shine matsakaicin matakin girma (misali, 5).
Jimillar girman ƙungiyar $M_{Org}$ zai iya zama tarawa, watakila vector na maki $M_{FA}$ shida don guje wa asarar ƙananan bayanai: $M_{Org} = [M_{FA1}, M_{FA2}, ..., M_{FA6}]$.

6.2 Aiwatar da Tsarin: Misali na Lamari Ba tare da Lamba ba

Yanayi: Kamfanin fasahar kuɗi "PayFast" yana da API na jama'a don sarrafa biyan kuɗi amma yana fuskantar matsaloli game da korafe-korafen masu haɓaka game da dogaro da takaddun bayanai marasa bayyanawa.

Bincike ta amfani da API-m-FAMM:

  1. Gano Yankin Mai Da Hatsari Mai Dacewa: Alamun suna nuni zuwa "Ƙwarewar Mai Haɓakawa & Al'umma" da "Saidan & Bincike".
  2. Kimanta Iyawa & Ayyuka: A cikin Ƙwarewar Mai Haɓakawa, kimanta ayyuka kamar:
    • "Bayar da takaddun bayanai na API mai ma'amala (misali, Swagger UI)"
    • "Kiyaye lissafin canji na jama'a don nau'ikan API."
    • "Bayar da yanayin yashi tare da bayanan gwaji."
    PayFast ya gano ba shi da lissafin canji kuma yanayin yashi mai iyaka.
  3. Fifita Ayyuka: Dangane da tsarin tsarin da mahimmanci da ƙwararru suka tabbatar (wanda aka haɗa da shi), PayFast ya fifita ƙirƙirar lissafin canji da haɓaka yashinsa a matsayin nasarori masu sauri don inganta amincin mai haɓaka, kafin shiga cikin ƙarin iyawa na sa ido.
Wannan ƙimar mai tsari tana motsa ƙungiyar daga "inganta takaddun" maras tabbas zuwa takamaiman ayyuka masu aiwatarwa waɗanda ƙwararru na masana'antu suka tabbatar.

7. Hangen Nesa na Aiwatarwa & Hanyoyin Gaba

Bayanan API-m-FAMM sun buɗe hanyoyi da yawa don aikin gaba da aikace-aikace:

  • Haɗin Kayan Aiki: Bayanan da aka tsara sun dace don haɗawa cikin dandamalin gudanar da API (misali, Kong, Azure API Management) a matsayin ƙa'idar ƙima da aka gina, yana ba da allunan girma ta atomatik.
  • Tsarin Girma Mai Ƙarfi: Bincike na gaba zai iya haɗa aiwatar da ayyuka zuwa ma'auni na aiki (misali, lokacin aiki na API, matsakaicin lokacin warwarewa, lokacin shigar da mai haɓaka) don ƙirƙirar tsarin girma mai tushen bayanai, mai daidaita kansa. Wannan yana daidaitawa da binciken DevOps akan auna da inganta aikin isar da software.
  • Faɗaɗawa na Musamman na Tsaye: Tsarin na gama gari ne. Aikin gaba zai iya ƙirƙirar faɗaɗawa na musamman don masana'antu kamar kiwon lafiya (ayyukan API masu bin HIPAA) ko kuɗi (iyawa na musamman na PSD2/Bude Banki), kamar yadda CMMI ke da bambance-bambancen yanki.
  • Ma'auni na Ƙididdiga: Haɗawa da ɓoye bayanan ƙima daga ƙungiyoyi da yawa zai iya ƙirƙirar ma'auni na masana'antu, yana amsa muhimmin tambaya: "Girma mu yake idan aka kwatanta da takwarorinsu?"
  • Binciken Giba Mai Ƙarfin AI: Amfani da LLM da aka horar da su akan bayanin aiki da tashoshin API na ƙungiyoyi/takaddun bayanai zai iya ba da damar ƙimar girma na farko ta atomatik, yana rage matsalar shiga don amfani da tsarin sosai.

8. Nassoshi

  1. Mathijssen, M., Overeem, M., & Jansen, S. (2020). Identification of Practices and Capabilities in API Management: A Systematic Literature Review. arXiv preprint arXiv:2006.10481.
  2. Kitchenham, B., & Charters, S. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering. EBSE Technical Report, EBSE-2007-01.
  3. Paulk, M. C., Curtis, B., Chrissis, M. B., & Weber, C. V. (1993). Capability Maturity Model for Software, Version 1.1. Software Engineering Institute, CMU/SEI-93-TR-24.
  4. Becker, J., Knackstedt, R., & Pöppelbuß, J. (2009). Developing Maturity Models for IT Management. Business & Information Systems Engineering, 1(3), 213–222.
  5. ISO/IEC 330xx series. Information technology — Process assessment.
  6. Forsgren, N., Humble, J., & Kim, G. (2018). Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations. IT Revolution Press.
  7. [68] Labarin bincike na farko da ke da alaƙa daga Bincike na Tsari na Wallafe-wallafe (wanda aka ambata a cikin PDF).