Consider http://www.bom.gov.au/places/nsw/sydney/ as your system under test.
In scope:
1. Enter any valid postcode/suburb & view Weather overview
http://www.bom.gov.au/places/nsw/sydney/
2. MAP View - Click Map view & verify Map with legends
Out of scope:
Features except weather overview & Map view are out of scope for this exercise
Q1. What would be your testing approach? What are the different levels of testing you would
come up/propose to gain confidence before release?
Q2. Assume team A adds feature A in release X, how & at what stage you verify regression
for existing features?
Q3. List down the high-level end-end test scenarios (Note: detailed test steps are not
required)
Q4. Pick any one end-end user journey & automate the test using either
Selenium - java & generate report (share git repo with readMe).
Q5. Pick any one end-end user journey & automate the test using either
Cypress & generate report (share git repo with readMe).
Consider http://www.bom.gov.au/places/nsw/sydney/ as your system under test. In scope: 1. Enter any valid postcode/suburb & view Weather overview http://www.bom.gov.au/places/nsw/sydney/ 2. MAP View - Click Map view & verify Map with legends Out of scope: Features except weather overview & Map view are out of scope for this exercise Q1. What would be your testing approach? What are the different levels of testing you would come up/propose to gain confidence before release? Q2. Assume team A adds feature A in release X, how & at what stage you verify regression for existing features? Q3. List down the high-level end-end test scenarios (Note: detailed test steps are not required) Q4. Pick any one end-end user journey & automate the test using either Selenium - java & generate report (share git repo with readMe). Q5. Pick any one end-end user journey & automate the test using either Cypress & generate report (share git repo with readMe). public static int{] conv_rgb_num(String colorstr){ int[] rgb = new int(3]; String s1,s2,s3; int holdint; if (colorstr.indexOf ("black") > -1){ rgbl0 ) else if rgbl0 ) else if rgbl0 ) else if rgbl0 ) else if rgbl0] ) else if rgbl0 i else if rgbl0 ) else if rgbl0 ) = 0; rgbll] = 0; xgbl2] = 0; (colorstr.indexof ("red") > -1){ = 255; rgb(l] = 0; rgbl2] = 0; (colorstr.indexof ("blue") > -1){ = 0; rgbl1] = 0; rgbl2] = 255; (colorstr.indexof ("cyan") > -1){ = 0; rgbl1] = 255; rgbl2] = 255; (colorstr. indexof ("darkgray™) > -1){ = 80; rgbl1] = 80; rgbl2] = 80; (colorstr.indexof ("gray") > -1){ = 128; rgp(1] = 128; rgbl2] = 128; (colorstr. indexof ("magenta™) > -1){ = 255; rgbll] = 0; rgbl2] = 255; (colorstr.indexOf ("lightgray") > -1){ = 192; rgb(l] = 192; rgbl2] = 192; 15:25 Gd & @ TERE aE {3 A bom.govau/australia/m + (3) [—— MetEye - your eye on the environment © ® @ F401 ekg Disclamer | tact | startyping tho select frm in town, cy, postcode alvin) | _Locate || © Fda | Tinozoon AEDT wTESTWEATHER |) ro rion nd] Gurtent Temp, Rain, Wind . [ES — 0 Sete views fr oction FORECASTS oa Skt TAB MD SUN smi nz Tes | weds TL o 8 Be TH RR [ira ~~ LppLbnp © Wot spe vs gecton tom) wo nw mw wow ® ® [ea ~ @ uremia waco = 2 |W 8 ds ww Co nas Gaceoanty = mw ® ww ® Omang ese Ny fasten) ~ | owz | 001 0 0 0 | ows can wo tec Od | OR (Oda Oo) (Ow oe — ori ~ yaver onic on Boe onin pt 3 ded 90 223,221 PART Clemsoatosremnorn | rer mond Woes Forecasts © Temperature Forecasts ~ Storms, Snow Fog Frost ~ Humidty Forecasts ~ UV index Forecasts ~ Pacerames 8 Pseuchraker (1) 9 Swed locations] @ Forcast locations focus memes (fosirighuan (wstiee [gomns A was 5 3 § Mae Bree [ge i Bae mew aes | cunure | ommomen me Hotora Wester Srces ; pon ws rato str smn 2 8 Topealcyiares ant rcs Sr Cars | semep | rst Toma aig cove Seem outeoks ne Spr atr serves pene wr wh ond Cite varsity scars rot ttm [rere mst one Sse is ngs wes wietos wisn ——— Wy Sore Gos Raa fom conn var sane Sor ry pnt Sudesh © Comm Conmamest of Aula 222 ses of Mts (BN 9265 5352 CRISS Po 2015 Dil Zc Acs 11] Oo