1. Gabatarwa
Tattalin arzikin API ginshiƙi ne na canjin dijital, yana ba da damar haɗa ƙananan ayyuka (microservices) a cikin yanayin girgije gauraye da na gefe. Kamar yadda misalin takarda na kantin sayar da littattafai ya nuna wanda ya ƙunshi kaya, keken siyayya, tabbatar da bashi, da ƙananan ayyukan jigilar kaya, ingancin dukan aikace-aikacen kasuwanci ya dogara da amincin API ɗinsa. Gwajin da aka tsara na gargajiya, wanda ya haɗa da ƙirar yanayi da zaɓin sigogi, yana da wahala kuma yana fama da rufe babban sararin haɗin jerin kiran API da ƙimar sigogi. Wannan takarda ta gabatar da Autotest Assist a matsayin mafita, tana ba da shawarar samar da gwajin bazuwar don ƙarfafa da haɓaka hanyoyin gwaji na gargajiya.
2. Tsarin Samar da Gwajin Bazuwar
2.1 Tsarin Asali
Tsarin ya ƙunshi maimaitawa: 1) Zaɓin aikin API $f()$ bazuwar don aiwatarwa. 2) Samar da sigogi masu shigarwa $p_1, p_2, ..., p_k$ bazuwar waɗanda suka dace da nahawu kuma halal a ma'ana waɗanda suka bi sharuɗɗan farko na $f()$. 3) Aiwatar da $f()$ da lura da sakamako da tasirin tsarin. Wannan yana haifar da jerin hulɗar API na bazuwar, yana binciken sararin yanayin tsarin.
2.2 Manyan Ƙalubale
Takardar ta gano ƙalubale guda biyar masu mahimmanci: tabbatar da gamsuwar sharuɗɗan farko don nasarar kiran API; tantance halin da ake tsammani bayan aiwatarwa; tallafawa gyara gazawar; haɗa gwaje-gwaje masu amfani da aka gano cikin tsarin gwajin komawa da aka tsara; da kuma tantance rufe da aka samu ta hanyar tsarin bazuwar don kimanta isasshensa don komawar tsarin.
3. Autotest Assist: Hanyoyi & Tsarin Gina
3.1 Fassarar Ƙayyadaddun API
Autotest Assist yana magance ƙalubalen farko biyu ta hanyar fassara ƙayyadaddun API na yau da kullun (misali, OpenAPI/Swagger). Wannan ƙayyadaddun dole ne a bayyana ko a ɓoye ya ayyana sharuɗɗan farko (yanayin tsarin da ake buƙata da ƙuntatawa na shigarwa) da sharuɗɗan baya (sakamakon da ake tsammani da canje-canjen yanayi).
3.2 Ƙirƙirar Samfur & Samar da Gwaji
Kayan aikin yana ƙirƙirar samfur mai ɗaukar yanayi daga ƙayyadaddun bayanai. Wannan samfur yana fahimtar dogaro da albarkatu—misali, cewa API "sayi littafi" $g()$ yana buƙatar ingantaccen littafin da aka samu daga API "samun littafi" $f()$ da ya gabata. Mai samar da bazuwar yana amfani da wannan samfurin don samar da ƙimar sigogi da jerin abubuwan da suka mutunta waɗannan dogaro, suna motsawa fiye da nahawu kawai zuwa ingancin ma'ana.
3.3 Bayyana Matsalolin Ƙayyadaddun Bayanai
Babban fa'ida ta biyu ita ce, tsarin fassara ƙayyadaddun bayanai don samar da gwaji zai iya bayyana shubuha, rashin daidaituwa, ko ƙuntatawa da suka ɓace a cikin takaddun API—kurakurai waɗanda za su iya haifar da kurakurai na haɗawa ko amfani mara kyau.
4. Haɗawa da Gwaji da Aka Tsara
4.1 Haɓaka Tsarin Gwajin Komawa
Lokacin da gwajin bazuwar ya gano kuskure, dole ne a kiyaye gyaran daga komawa. Autotest Assist yana tallafawa canza jerin gwajin bazuwar da aka bayyana (ko ƙaramin sigar sa) zuwa gwaji mai ƙarfi, mai maimaitawa da aka tsara. Wannan yana haifar da zagaye mai kyau inda binciken bazuwar ya ƙarfafa tsarin aminci na ƙayyadaddun.
4.2 Ƙididdigar Rufewa
Takardar ta ɗaga tambaya mai mahimmanci na amana: Shin gwajin bazuwar kadai zai iya komawa tsarin? Amsar tana cikin ma'aunin rufe (misali, rufe lamba, rufe ƙarshen API, rufe haɗin ƙimar sigogi). Duk da yake gwajin bazuwar zai iya samun babban rufe, tsarin da aka tsara yana da mahimmanci har yanzu don mahimman dabaru na kasuwanci da yanayi na gefe, yana haifar da dabarar gauraye.
5. Cikakkun Bayanai na Fasaha & Tsarin Lissafi
Matsalar samarwa ta asali za a iya tsara ta azaman samfurin daga sararin duk yiwuwar ingantattun hanyoyin aiwatarwa. Bari $S$ ya zama saitin yanayin tsarin, $A$ saitin kiran API, kuma $P_a$ saitin ingantattun sigogi don API $a \in A$. Ingantacciyar hanyar $T$ jerin abubuwa ne $\langle (a_1, \vec{p_1}), (a_2, \vec{p_2}), ... \rangle$ kamar haka, ga kowane mataki $i$, sharuɗɗan farko $Pre(a_i, \vec{p_i})$ suna riƙe a yanayi $S_{i-1}$, kuma aiwatarwa yana haifar da sabon yanayi $S_i = Post(a_i, \vec{p_i}, S_{i-1})$. Samfurin Autotest Assist yana ƙididdige ayyukan $Pre$ da $Post$ daga ƙayyadaddun bayanai don jagorantar zaɓin bazuwar, da nufin haɓaka yuwuwar $P(T)$ na samar da hanyoyi daban-daban, ingantattu, masu binciken sararin yanayi. Ma'aunin tasiri $E$ ana iya bayyana shi azaman aikin rufe $Cov(T)$ da ƙimar gano kuskure $FDR(T)$ akan lokaci $t$: $E(t) = \int_0^t \alpha \cdot Cov(T(\tau)) + \beta \cdot FDR(T(\tau)) \, d\tau$, inda $\alpha$ da $\beta$ ma'auni ne.
6. Sakamakon Gwaji & Aiki
Duk da yake ɓangaren PDF da aka bayar bai haɗa da takamaiman sakamako na ƙididdiga ba, hanyar da aka bayyana tana nuna sakamako masu aunawa. Sakamakon da ake tsammani daga tura kayan aiki kamar Autotest Assist zai haɗa da: Jadawali 1: Gano Kuskure Akan Lokaci – Zane mai nuna cewa samar da gwajin bazuwar (mai yiwuwa yana bin lanƙwasa kamar $F_d(t) = k \cdot (1 - e^{-\lambda t})$) yana gano kurakurai a ƙimar farko mafi girma fiye da gwaji da aka tsara kadai, ko da yake ƙimar na iya tsayawa. Jadawali 2: Kwatancen Rufe – Jadawali mai kwatanta rufe lamba, rufe reshe, da rufe haɗin ƙimar sigogi da tsarin gwaji da aka tsara ya samu sabanin tsarin gwaji da aka tsara wanda aka ƙarfafa da gwaje-gwaje bazuwar, yana nuna gagarumin riba a cikin na ƙarshe, musamman ga sararin sigogi. Jadawali 3: Gano Laifin Ƙayyadaddun Bayanai – Tsarin lokaci mai nuna adadin shubuha ko kurakurai da aka samu a cikin ƙayyadaddun API a lokacin matakin ƙirƙirar samfur, yana nuna ƙimarsa azaman mai tsaftace ƙayyadaddun bayanai.
7. Tsarin Bincike: Misali Ba na Lamba ba
Yi la'akari da sauƙaƙan "Gudanar da Takardu" microservice tare da API guda biyu: POST /documents (yana ƙirƙirar takarda, yana dawo da ID takarda doc_id) da GET /documents/{doc_id} (yana dawo da takarda). Gwaji da aka tsara zai iya ƙirƙirar takarda a bayyane sannan ya ɗauko ta. Tsarin bazuwar na Autotest Assist zai iya samar da wannan jerin, amma kuma wasu: ƙoƙarin GET doc_id mara wanzuwa (gwada sarrafa kuskure); ko samar da jerin CREATE, CREATE, GET (don ID#1), GET (don ID#2). Hakanan zai iya samar da doc_id mara kyau amma ingantacciyar nahawu (misali, tare da haruffa na musamman) don bincika tsaro ko gefuna na fassara. Ƙimar tsarin tana cikin samar da waɗannan jerin abubuwan da ba a zata ba amma ingantattu waɗanda mai gwaji ɗan adam ba zai iya tunani ba, bisa ga samfurin da aka ƙaddara cewa GET ya dogara da POST da ya gabata.
8. Aikace-aikace na Gaba & Hanyoyin Bincike
Makomar gwajin bazuwar na API tana cikin fagage masu mahimmanci da yawa: 1. Samarwa Mai Haɓaka AI: Haɗa Manyan Samfuran Harshe (LLMs) don fahimtar takaddun API na harshe na halitta inda ƙayyadaddun bayanai na yau da kullun suka rasa, ko don samar da ƙarin shigarwar bazuwar "mai hankali" waɗanda ke taruwa kusa da ƙimar iyaka. 2. Fuzzing Mai Yanayi don Microservices: Faɗaɗa ra'ayi don ba kawai samar da jerin abubuwa ba har ma don canza saƙon cibiyar sadarwa, allurar jinkiri, da kwaikwayon gazawar ɓangare (masu karya da'ira) don gwada juriya, kamar kayan aikin fuzzing na tsarin rarraba kamar Jepsen amma ta atomatik. 3. Haɗawa da Bututun CI/CD: Saka kayan aiki kamar Autotest Assist azaman ƙofar daidaitacce a cikin bututun turawa, yana ba da ci gaba, bincike ta atomatik na yanayin mataki. 4. Samfurin Dogaro na Sabis-Sabis: Girman ƙirƙirar samfur don sarrafa rikitattun microservices masu yawa, yana ƙaddara ƙuntatawa na rawa ta atomatik daga hanyoyi ko raga na sabis. Bincike ya kamata ya mayar da hankali kan inganta ingancin binciken sararin yanayi da haɓaka mafi kyawun ma'auni don tantance "ban sha'awa" na jerin gwajin bazuwar da aka samar fiye da rufe lamba.
9. Nassoshi
- Farchi, E., Prakash, K., & Sokhin, V. (2022). Samfurin Gwajin Bazuwar don Hanyoyin Haɗin Aikace-aikace. arXiv preprint arXiv:2207.13143.
- Claessen, K., & Hughes, J. (2000). QuickCheck: kayan aiki masu sauƙi don gwajin bazuwar na shirye-shiryen Haskell. ACM Sigplan Notices, 35(9), 268-279.
- Martin-López, A., Segura, S., & Ruiz-Cortés, A. (2021). Bincike kan gwajin metamorphic. IEEE Transactions on Software Engineering, 48(1), 1-25.
- Ƙaddamar da OpenAPI. (2021). Ƙayyadaddun OpenAPI v3.1.0. An dawo daga https://spec.openapis.org/oas/v3.1.0
- Zhu, J. Y., Park, T., Isola, P., & Efros, A. A. (2017). Fassarar hoto zuwa hoto mara haɗin gwiwa ta amfani da cibiyoyin adawa na zagaye-daidaitacce. Proceedings of the IEEE international conference on computer vision (shafi na 2223-2232). (An ambata saboda amfani da ƙirƙira ta atomatik, mai ƙuntatawa a wani yanki daban).
- Kingsbury, B. (2019). Jepsen: Binciken Amincin Tsarin Rarraba. An dawo daga https://jepsen.io
10. Bincike na Asali & Sharhin Kwararru
Fahimta ta Asali: Autotest Assist ba wani kayan aikin sarrafa gwaji ba ne kawai; canji ne na dabarun daga tabbatarwa ta hanyar gini (gwaje-gwaje da aka tsara) zuwa tabbatarwa ta hanyar bincike. A cikin rikice-rikicen gaskiya na rarraba na tattalin arzikin API, ba za ku iya rubuta kowane yanayin gazawa ba—dole ne ku farauta su. Wannan takarda ta gano daidai cewa ainihin maƙalar ba aiwatar da gwaji ba ne, amma ƙirar gwaji. Fahimtar amfani da ƙayyadaddun API azaman tushen gaskiya guda ɗaya don samarwa yana da ƙarfi, yana mai da takaddun daga abu mai wucewa zuwa mai duba mai aiki.
Kwararar Hankali & Ƙarfuka: Hankalin hanyar yana da inganci: fassara ƙayyadaddun bayanai, ƙirƙirar samfur, samar da tafiya bazuwar mai ƙuntatawa. Babban ƙarfinsa shine kai hari ga matsalar "fashewar haɗin gwiwa". Inda ɗan adam zai iya gwada ƴan hanyoyi masu farin ciki da baƙin ciki, wannan hanyar tana iya samar da dubban canje-canjen yanayi na musamman, yana bincika zurfin halayen tsarin. Fa'idar biyu na fallasa kurakuran ƙayyadaddun bayanai babban fasaha ne—yana mai da kayan aikin gwaji zuwa madauki na ingancin ƙira, mai tunawa da yadda masu duba iri ke inganta ingancin lamba. Haɗin da aka tsara tare da komawar da aka tsara yana da aiki, yana guje wa tarko na "bazuwar kawai" maimakon yana ba da shawarar dangantakar haɗin gwiwa.
Kurakurai & Giba Masu Muhimmanci: Duk da haka, hangen nesa na takardar yana da gibobi. Na farko, ya dogara sosai akan kasancewar ƙayyadaddun bayanai mai inganci, mai karantawa ta inji. A duniyar gaskiya, kamar yadda kowane injiniya da ya yi fama da takaddun OpenAPI masu shubuha ya sani, wannan sau da yawa keɓancewa ne, ba ka'ida ba. Tasirin kayan aikin yana rushewa idan ƙayyadaddun bayanai ba daidai ba ne ko bai cika ba—misalin "shara a ciki, shara a waje". Na biyu, an lalata matsalar "mai duba". Tantance ko API "ya yi kamar yadda ake tsammani" (Ƙalubale #2) ba abu ne mai sauƙi ba don ƙira mai yanayi mai rikitarwa. Ƙayyadaddun bayanai na iya ayyana tsarin amsa, amma ba dabaru na kasuwanci masu rikitarwa ba. Ba tare da mai duba mai zurfi ba—watakila yana amfani da ra'ayoyin gwaji na tushen dukiya daga QuickCheck ko alaƙar metamorphic—kayan aikin na iya zama kawai samar da hayaniya. Na uku, tambayar rufe ba ta warware ba. Rufe gwajin bazuwar yana da yuwuwar kuma bai daidaita ba; hanyoyin lamba masu mahimmanci amma ƙananan yuwuwar ƙila ba za a taɓa yin su ba, suna haifar da tunanin tsaro na ƙarya.
Fahimta Mai Aiki & Hangen Nesa na Gaba: Ga masu aiki, fahimtar mai aiki ita ce fara ɗaukar ƙayyadaddun API azaman kayan aiki na farko, masu gwaji. Saka hannun jari a cikin ingancinsu. Ga masu bincike, hanyar gaba ita ce hankali gauraye. Haɗa hanyar tushen samfurin Autotest Assist tare da dabarun ML. Misali, yi amfani da bayanan kuskure na tarihi da na gwaji don karkatar da samarwar bazuwar zuwa tsarin API masu saurin kuskure ko haɗin sigogi, kamar yadda masu fuzzing ke amfani da martani na rufe. Haɗa tare da dandamali na lura: yi amfani da rajistan aiki na ainihin lokaci da ma'auni don ƙaddara yanayin tsarin da ba a zata ba yayin gwajin bazuwar da kuma jagorantar samarwa zuwa gare su. Manufa ta ƙarshe ya kamata ta zama tsarin gwaji mai warkar da kansa—inda binciken bazuwar, gwaje-gwaje da aka tsara, da sa ido na lokacin aiki suka zama madauki na ci gaba, suna gano kuma karewa daga komawa ta atomatik a cikin raga na microservice mai ci gaba da haɓaka. Wannan takarda ta kafa tushe mai ƙarfi, amma gina duniyar da ke tafiyar da API mai juriya yana buƙatar motsawa fiye da tafiya bazuwar zuwa bincike mai hankali, mai daidaitawa.