diff --git a/internal/adapters/parsers/base/base.go b/internal/adapters/parsers/base/base.go index 4a055d3..4fe2795 100644 --- a/internal/adapters/parsers/base/base.go +++ b/internal/adapters/parsers/base/base.go @@ -123,6 +123,15 @@ const ( MaxAttemptTraceRunes = 32768 ) +// Inline attachment limits for attachments that travel as base64 inside the +// report body rather than being uploaded separately. The budget is per parse, +// matching the JVM reporters' own 8 MiB so one family-wide number governs how +// much rides in a report body. +const ( + MaxInlineAttachmentBytes = 1 << 20 // 1 MiB for any single attachment + MaxInlineTotalBytes = 8 << 20 // 8 MiB across the whole run +) + // ClampOutput bounds captured output by lines first, then by runes, matching how // the server truncates on write. func ClampOutput(lines []string) []string { diff --git a/internal/adapters/parsers/e2e/xctest/xcresult_extras.go b/internal/adapters/parsers/e2e/xctest/xcresult_extras.go index 59d7fd9..a0a8382 100644 --- a/internal/adapters/parsers/e2e/xctest/xcresult_extras.go +++ b/internal/adapters/parsers/e2e/xctest/xcresult_extras.go @@ -10,6 +10,7 @@ import ( "strings" "time" + "qualflare-cli/internal/adapters/parsers/base" "qualflare-cli/internal/adapters/parsers/shared/toolrun" "qualflare-cli/internal/core/domain" ) @@ -30,13 +31,8 @@ import ( // nodeIdentifier, result) are safe; anything else would work in CI and break // on a developer's laptop. -// Attachments are inlined up to these limits and take the artifact route -// beyond them. The budget is per parse, matching the JVM reporters' own 8 MiB -// so one family-wide number governs how much rides in a report body. -const ( - maxInlineAttachmentBytes = 1 << 20 // 1 MiB for any single attachment - maxInlineTotalBytes = 8 << 20 // 8 MiB across the whole run -) +// Attachments are inlined up to base.MaxInlineAttachmentBytes and +// base.MaxInlineTotalBytes and take the artifact route beyond them. // testDetailsResponse mirrors `xcresulttool get test-results test-details`. type testDetailsResponse struct { @@ -241,7 +237,7 @@ func attachmentsFromManifest(manifest []byte, dir string) (map[string][]domain.A case strings.HasPrefix(att.MimeType, "image/"): att.LocalPath = path att.ArtifactKind = domain.ArtifactKindImage - case info.Size() <= maxInlineAttachmentBytes && inlined+info.Size() <= maxInlineTotalBytes: + case info.Size() <= base.MaxInlineAttachmentBytes && inlined+info.Size() <= base.MaxInlineTotalBytes: content, err := os.ReadFile(path) if err != nil { continue diff --git a/internal/adapters/parsers/unit/flutter/flutter.go b/internal/adapters/parsers/unit/flutter/flutter.go index 6893fef..71f938c 100644 --- a/internal/adapters/parsers/unit/flutter/flutter.go +++ b/internal/adapters/parsers/unit/flutter/flutter.go @@ -192,6 +192,11 @@ func (p *Parser) Parse(reader io.Reader) (*domain.Suite, error) { if st == nil || ev.MessageType != "print" { continue } + // Markers belong to the running test; one printed after its + // testDone is ignored rather than surfacing as output. + if st.done && isMarkerLine(ev.Message) { + continue + } if ev.Message == retryPrefix+st.name { st.retries = append(st.retries, retryMark{len(st.errors), len(st.prints)}) } else { @@ -209,6 +214,7 @@ func (p *Parser) Parse(reader io.Reader) (*domain.Suite, error) { } root := projectRoot(allPaths) + budget := &inlineBudget{} suite := &domain.Suite{ Name: "Flutter Tests", Category: domain.FrameworkFlutter.GetCategory(), @@ -223,7 +229,7 @@ func (p *Parser) Parse(reader io.Reader) (*domain.Suite, error) { if st.hidden { continue } - suite.Cases = append(suite.Cases, buildCase(st, root)) + suite.Cases = append(suite.Cases, buildCase(st, root, budget)) } suite.RecomputeCounts() return suite, nil @@ -246,8 +252,9 @@ func newTestState(t *testInfo, suitePath string, start int64) *testState { return st } -// buildCase turns a finished (or unfinished) test into a domain case. -func buildCase(st *testState, root string) domain.Case { +// buildCase turns a finished (or unfinished) test into a domain case. budget +// is the run's inline attachment budget, shared by every case. +func buildCase(st *testState, root string, budget *inlineBudget) domain.Case { file := relativePath(st.file, root) name := st.name // A failed load is named after the file; its raw name carries an absolute path. @@ -268,10 +275,18 @@ func buildCase(st *testState, root string) domain.Case { } slices := splitAttempts(st) + // Marker lines become case metadata and leave each attempt's output. + sets := make([]markerSet, len(slices)) + for i := range slices { + sets[i], slices[i].prints = extractMarkers(slices[i].prints) + } + warnings := applyMarkers(&c, sets, budget) + final := slices[len(slices)-1] finalOut := final.resolve(st.result) - // system-out is every attempt's output, exception blocks removed. + // system-out is every attempt's output, exception blocks removed, clamped; + // then the warnings, after the clamp so a long output cannot hide them. var outLines []string for i, s := range slices { if i == len(slices)-1 { @@ -280,7 +295,11 @@ func buildCase(st *testState, root string) domain.Case { outLines = append(outLines, s.resolve("").out...) } } - if out := strings.Join(base.ClampOutput(outLines), "\n"); out != "" { + outLines = base.ClampOutput(outLines) + for _, w := range warnings { + outLines = append(outLines, "qualflare: "+w) + } + if out := strings.Join(outLines, "\n"); out != "" { c.Properties[propSystemOut] = out } diff --git a/internal/adapters/parsers/unit/flutter/inline_budget_test.go b/internal/adapters/parsers/unit/flutter/inline_budget_test.go new file mode 100644 index 0000000..aecf218 --- /dev/null +++ b/internal/adapters/parsers/unit/flutter/inline_budget_test.go @@ -0,0 +1,109 @@ +package flutter + +import ( + "encoding/base64" + "fmt" + "strings" + "testing" + + "qualflare-cli/internal/core/domain" +) + +const mib = 1 << 20 + +// inlineRun builds a synthetic run of one test per entry in sizes, each +// attaching sizes[i] bytes as name att. of the given MIME type. +func inlineRun(t *testing.T, mime, ext string, sizes ...int) *domain.Suite { + t.Helper() + evs := make([]map[string]any, 0, 2+3*len(sizes)) + evs = append(evs, + map[string]any{"type": "start", "time": 0}, + map[string]any{"type": "suite", "suite": map[string]any{"id": 0, "platform": "vm", "path": "test/a_test.dart"}}, + ) + for i, size := range sizes { + id := i + 1 + data := base64.StdEncoding.EncodeToString(make([]byte, size)) + evs = append(evs, + map[string]any{"type": "testStart", "time": 1, "test": map[string]any{"id": id, "name": fmt.Sprintf("t%d", id), "suiteID": 0, "metadata": map[string]any{}}}, + map[string]any{"type": "print", "testID": id, "messageType": "print", "message": marker(t, map[string]any{ + "k": "att", "id": "a", "name": fmt.Sprintf("att%d.%s", id, ext), "type": mime, "n": 1, "i": 0, "data": data, + })}, + map[string]any{"type": "testDone", "time": 2, "testID": id, "result": "success"}, + ) + } + return parseString(t, jsonl(t, evs...)) +} + +func droppedPrefix(name string, size int, mime string) string { + return fmt.Sprintf("qualflare: attachment %q (%d bytes, %s) dropped: ", name, size, mime) +} + +// Synthetic: two tests each attach 4 MiB of JSON, over the 1 MiB inline limit. +func TestInlineBudget_LargeNonImageDropped(t *testing.T) { + suite := inlineRun(t, "application/json", "json", 4*mib, 4*mib) + for i, c := range suite.Cases { + if len(c.Attachments) != 0 { + t.Errorf("%s: attachments = %q, want none", c.Name, attNames(c)) + } + want := droppedPrefix(fmt.Sprintf("att%d.json", i+1), 4*mib, "application/json") + if !strings.Contains(c.Properties[propSystemOut], want) { + t.Errorf("%s: system-out %q lacks %q", c.Name, c.Properties[propSystemOut], want) + } + } +} + +// Synthetic: nine tests each attach 0.9 MiB of JSON; the ninth would take the +// run's inline total past 8 MiB. +func TestInlineBudget_RunTotalSpansCases(t *testing.T) { + size := 9 * mib / 10 + sizes := make([]int, 9) + for i := range sizes { + sizes[i] = size + } + suite := inlineRun(t, "application/json", "json", sizes...) + for i, c := range suite.Cases[:8] { + if len(c.Attachments) != 1 { + t.Errorf("case %d: attachments = %q, want one", i+1, attNames(c)) + } + if strings.Contains(c.Properties[propSystemOut], "dropped") { + t.Errorf("case %d: unexpected warning %q", i+1, c.Properties[propSystemOut]) + } + } + ninth := suite.Cases[8] + if len(ninth.Attachments) != 0 { + t.Errorf("ninth: attachments = %q, want none", attNames(ninth)) + } + if want := droppedPrefix("att9.json", size, "application/json"); !strings.Contains(ninth.Properties[propSystemOut], want) { + t.Errorf("ninth: system-out %q lacks %q", ninth.Properties[propSystemOut], want) + } +} + +// Synthetic: a 4 MiB PNG is offloaded by the upload, so the inline budget +// does not apply to it. +func TestInlineBudget_ImagesUnaffected(t *testing.T) { + c := inlineRun(t, "image/png", "png", 4*mib).Cases[0] + if got := attNames(c); len(got) != 1 || got[0] != "att1.png" { + t.Errorf("attachments = %q, want att1.png", got) + } + if out := c.Properties[propSystemOut]; out != "" { + t.Errorf("system-out = %q, want empty", out) + } +} + +// Synthetic: 250 plain print lines, more than the output clamp keeps, and an +// attachment missing a chunk; its warning must survive the clamp. +func TestWarnings_SurviveOutputClamp(t *testing.T) { + evs := make([]map[string]any, 0, 252) + for i := range 250 { + evs = append(evs, printEv(fmt.Sprintf("plain line %d", i))) + } + evs = append(evs, + printEv(marker(t, map[string]any{"k": "att", "id": "a", "name": "log.txt", "type": "text/plain", "n": 2, "i": 0, "data": "aGk="})), + map[string]any{"type": "testDone", "time": 5, "testID": 1, "result": "success"}, + ) + c := syntheticRun(t, []string{"test/a_test.dart"}, "chatty", nil, evs...).Cases[0] + want := `qualflare: attachment "log.txt" is missing chunks (1 of 2 arrived); dropped` + if out := c.Properties[propSystemOut]; !strings.HasSuffix(out, want) { + t.Errorf("system-out ends with %q, want %q", out[max(0, len(out)-120):], want) + } +} diff --git a/internal/adapters/parsers/unit/flutter/markers.go b/internal/adapters/parsers/unit/flutter/markers.go new file mode 100644 index 0000000..1368168 --- /dev/null +++ b/internal/adapters/parsers/unit/flutter/markers.go @@ -0,0 +1,494 @@ +package flutter + +import ( + "encoding/base64" + "encoding/json" + "fmt" + "strconv" + "strings" + "time" + + "qualflare-cli/internal/adapters/parsers/base" + "qualflare-cli/internal/core/domain" +) + +// The qualflare_flutter package prints one marker line per API call from +// inside the running test, which the JSON reporter records as that test's +// print output: +// +// ##qualflare[v1] {"k":"label","name":"feature","value":"checkout"} +// +// The parser turns them into case metadata and keeps them out of the output. +const ( + markerPrefix = "##qualflare[v1] " + // markerFamily starts every marker line, whatever its protocol version. + markerFamily = "##qualflare[" + + // Attachment caps in decoded bytes (at the cap is allowed), the same ones + // the package enforces; the per-test cap covers all attempts together. + maxAttachmentBytes = 5 * 1024 * 1024 + maxTestAttachmentBytes = 20 * 1024 * 1024 + // maxMarkerTextRunes bounds a name, value, URL, warning or step error. + maxMarkerTextRunes = 8192 + + stepUnfinishedMessage = "step did not finish" + defaultAttachmentMIME = "application/octet-stream" +) + +// offloadableMIME is the set the upload offloads out of the report body +// (offloadableExtensions in internal/core/services/report_service.go). Any +// other attachment travels base64 inside the body and counts against the +// run's inline budget. +var offloadableMIME = map[string]bool{ + "image/png": true, + "image/jpeg": true, + "image/gif": true, +} + +// inlineBudget is the run-wide total of attachment bytes that stay inline in +// the report body, shared by every case of one parse. +type inlineBudget struct{ used int } + +// admit reports why an attachment of size bytes cannot stay inline, or "" +// when it can, in which case it is counted. Offloadable images always pass. +func (b *inlineBudget) admit(mime string, size int) string { + switch { + case offloadableMIME[mime]: + return "" + case size > base.MaxInlineAttachmentBytes: + return fmt.Sprintf("over the %d-byte limit for an attachment sent inline (only PNG, JPEG and GIF are uploaded separately)", base.MaxInlineAttachmentBytes) + case b.used+size > base.MaxInlineTotalBytes: + return fmt.Sprintf("would take this run's inline attachments past %d bytes", base.MaxInlineTotalBytes) + } + b.used += size + return "" +} + +// markerSet is what one attempt's marker lines amount to. +type markerSet struct { + labels []domain.Label + links []domain.Link + tags []string + priority domain.Severity + steps []domain.Step + attachments []domain.Attachment + warnings []string +} + +// isMarkerLine reports whether a print is a marker line of any version. +func isMarkerLine(msg string) bool { + return strings.HasPrefix(msg, markerFamily) +} + +// rawMarker is the union of every marker kind's fields. id is an int for +// steps and a string for attachments, so it is decoded per kind. +type rawMarker struct { + K string `json:"k"` + ID json.RawMessage `json:"id"` + Parent *int `json:"parent"` + Name string `json:"name"` + Value string `json:"value"` + Type string `json:"type"` + URL string `json:"url"` + Tags []string `json:"tags"` + T *int64 `json:"t"` + Status string `json:"status"` + Error string `json:"error"` + N *int `json:"n"` + I *int `json:"i"` + Data string `json:"data"` + Msg string `json:"msg"` +} + +// openStep is a started step: its index in the steps slice and start time. +type openStep struct { + index int + start *int64 +} + +// pendingAttachment collects one attachment's chunks. +type pendingAttachment struct { + name, mime string + n int + chunks map[int]string +} + +// markerReader accumulates one attempt's markers. +type markerReader struct { + set markerSet + malformed int + badVersion int + unknownKind []string + seenWarn map[string]bool + steps map[int]openStep + ended map[int]bool + attOrder []string + atts map[string]*pendingAttachment +} + +// extractMarkers reads the marker lines out of one attempt's prints. rest is +// prints without them, and prints itself when there are none. Every problem +// (malformed JSON, an unknown kind, another protocol version, a dropped +// attachment) becomes one warning. +func extractMarkers(prints []string) (set markerSet, rest []string) { + r := markerReader{ + seenWarn: map[string]bool{}, + steps: map[int]openStep{}, + ended: map[int]bool{}, + atts: map[string]*pendingAttachment{}, + } + sawMarker := false + for i, p := range prints { + if !isMarkerLine(p) { + if sawMarker { + rest = append(rest, p) + } + continue + } + if !sawMarker { + sawMarker = true + rest = append(make([]string, 0, len(prints)-1), prints[:i]...) + } + r.read(p) + } + if !sawMarker { + return markerSet{}, prints + } + r.finish() + return r.set, rest +} + +func (r *markerReader) warn(msg string) { + if r.seenWarn[msg] { + return + } + r.seenWarn[msg] = true + r.set.warnings = append(r.set.warnings, msg) +} + +func (r *markerReader) read(line string) { + body, ok := strings.CutPrefix(line, markerPrefix) + if !ok { + if strings.HasPrefix(line, strings.TrimSpace(markerPrefix)) { + r.malformed++ // v1 without the separating space + } else { + r.badVersion++ + } + return + } + var m rawMarker + if err := json.Unmarshal([]byte(body), &m); err != nil { + r.malformed++ + return + } + switch m.K { + case "label": + r.label(m) + case "link": + r.link(m) + case "tag": + r.tag(m) + case "priority": + r.priority(m) + case "step+": + r.stepStart(m) + case "step-": + r.stepEnd(m) + case "att": + r.chunk(m) + case "warn": + if m.Msg == "" { + r.malformed++ + return + } + r.warn(capRunes(m.Msg, maxMarkerTextRunes)) + case "": + r.malformed++ + default: + kind := capRunes(m.K, 64) + for _, k := range r.unknownKind { + if k == kind { + return + } + } + r.unknownKind = append(r.unknownKind, kind) + } +} + +func (r *markerReader) label(m rawMarker) { + if m.Name == "" || m.Value == "" { + r.malformed++ + return + } + r.set.labels = appendLabel(r.set.labels, domain.Label{ + Name: capRunes(m.Name, maxMarkerTextRunes), + Value: capRunes(m.Value, maxMarkerTextRunes), + }) +} + +func (r *markerReader) link(m rawMarker) { + if m.URL == "" { + r.malformed++ + return + } + url := capRunes(m.URL, maxMarkerTextRunes) + switch m.Type { + case "issue", "tms", "custom": + default: + r.warn(fmt.Sprintf("link type %q is not one of issue, tms, custom; link %s ignored", capRunes(m.Type, 64), url)) + return + } + r.set.links = appendLink(r.set.links, domain.Link{Type: m.Type, Name: capRunes(m.Name, maxMarkerTextRunes), URL: url}) +} + +func (r *markerReader) tag(m rawMarker) { + if len(m.Tags) == 0 { + r.malformed++ + return + } + for _, t := range m.Tags { + if t != "" { + r.set.tags = appendTag(r.set.tags, capRunes(t, maxMarkerTextRunes)) + } + } +} + +func (r *markerReader) priority(m rawMarker) { + switch v := domain.Severity(m.Value); v { + case domain.SeverityLow, domain.SeverityMedium, domain.SeverityHigh, domain.SeverityCritical: + r.set.priority = v + default: + r.warn(fmt.Sprintf("priority %q is not one of low, medium, high, critical; ignored", capRunes(m.Value, 64))) + } +} + +// stepStart opens a step. It counts as an error that did not finish until its +// step- arrives. +func (r *markerReader) stepStart(m rawMarker) { + var id int + if json.Unmarshal(m.ID, &id) != nil || m.Name == "" { + r.malformed++ + return + } + if _, dup := r.steps[id]; dup { + r.malformed++ + return + } + s := domain.Step{Name: capRunes(m.Name, maxMarkerTextRunes), Status: domain.StatusError, Error: stepUnfinishedMessage} + if m.Parent != nil { + if parent, ok := r.steps[*m.Parent]; ok { + s.ParentIndex = domain.IntPtr(parent.index) + } + } + r.steps[id] = openStep{index: len(r.set.steps), start: m.T} + r.set.steps = append(r.set.steps, s) +} + +func (r *markerReader) stepEnd(m rawMarker) { + var id int + if json.Unmarshal(m.ID, &id) != nil { + r.malformed++ + return + } + open, ok := r.steps[id] + if !ok || r.ended[id] { + r.malformed++ + return + } + r.ended[id] = true + s := &r.set.steps[open.index] + switch m.Status { + case "passed": + s.Status, s.Error = domain.StatusPassed, "" + case "failed": + s.Status, s.Error = domain.StatusFailed, capRunes(m.Error, maxMarkerTextRunes) + default: + s.Status, s.Error = domain.StatusError, capRunes(m.Error, maxMarkerTextRunes) + } + if open.start != nil && m.T != nil && *m.T > *open.start { + s.Duration = time.Duration(*m.T-*open.start) * time.Millisecond + } +} + +func (r *markerReader) chunk(m rawMarker) { + var id string + if json.Unmarshal(m.ID, &id) != nil || id == "" || m.N == nil || m.I == nil || *m.N < 1 || *m.I < 0 || *m.I >= *m.N { + r.malformed++ + return + } + a := r.atts[id] + if a == nil { + name := capRunes(m.Name, maxMarkerTextRunes) + if name == "" { + name = "attachment" + } + mime := m.Type + if mime == "" { + mime = defaultAttachmentMIME + } + a = &pendingAttachment{name: name, mime: mime, n: *m.N, chunks: map[int]string{}} + r.atts[id] = a + r.attOrder = append(r.attOrder, id) + } + if _, dup := a.chunks[*m.I]; dup || *m.N != a.n { + r.malformed++ + return + } + a.chunks[*m.I] = m.Data +} + +// finish assembles the attachments, in order of their first chunk, and turns +// the counted problems into one warning each. +func (r *markerReader) finish() { + total := 0 + for _, id := range r.attOrder { + a := r.atts[id] + if len(a.chunks) < a.n { + r.warn(fmt.Sprintf("attachment %q is missing chunks (%d of %d arrived); dropped", a.name, len(a.chunks), a.n)) + continue + } + // The package splits one base64 string, so the chunks join back into it. + var b strings.Builder + for i := range a.n { + b.WriteString(a.chunks[i]) + } + content := b.String() + raw, err := base64.StdEncoding.DecodeString(content) + if err != nil { + r.warn(fmt.Sprintf("attachment %q is not valid base64; dropped", a.name)) + continue + } + if len(raw) > maxAttachmentBytes { + r.warn(fmt.Sprintf("attachment %q is %d bytes, over the %d-byte cap; dropped", a.name, len(raw), maxAttachmentBytes)) + continue + } + if total+len(raw) > maxTestAttachmentBytes { + r.warn(testCapWarning(a.name)) + continue + } + total += len(raw) + r.set.attachments = append(r.set.attachments, domain.Attachment{Name: a.name, MimeType: a.mime, Content: content}) + } + if r.malformed > 0 { + r.warn(fmt.Sprintf("skipped %d malformed marker %s", r.malformed, plural(r.malformed, "line", "lines"))) + } + for _, k := range r.unknownKind { + r.warn(fmt.Sprintf("skipped markers of unknown kind %q", k)) + } + if r.badVersion > 0 { + r.warn(fmt.Sprintf("skipped %d marker %s of an unsupported protocol version (this qf reads v1)", + r.badVersion, plural(r.badVersion, "line", "lines"))) + } +} + +func testCapWarning(name string) string { + return fmt.Sprintf("attachment %q would take this test past %d bytes of attachments; dropped", name, maxTestAttachmentBytes) +} + +// applyMarkers merges every attempt's markers into the case, in attempt order, +// and returns the warnings for its output. Labels, links and tags are +// deduplicated across attempts and the last priority wins; steps come from the +// final attempt; attachments come from every attempt, an earlier attempt's +// renamed `attempt : `, within the per-test cap and the run's inline +// budget. +func applyMarkers(c *domain.Case, sets []markerSet, budget *inlineBudget) []string { + var warnings []string + seen := map[string]bool{} + total := 0 + for i, s := range sets { + for _, l := range s.labels { + c.Labels = appendLabel(c.Labels, l) + } + for _, l := range s.links { + c.Links = appendLink(c.Links, l) + } + for _, t := range s.tags { + c.Tags = appendTag(c.Tags, t) + } + if s.priority != "" { + c.Priority = s.priority + } + final := i == len(sets)-1 + if final { + c.Steps = s.steps + } + pending := s.warnings + for _, a := range s.attachments { + if !final { + a.Name = "attempt " + strconv.Itoa(i+1) + ": " + a.Name + } + size := decodedSize(a.Content) + if total+size > maxTestAttachmentBytes { + pending = append(pending, testCapWarning(a.Name)) + continue + } + if why := budget.admit(a.MimeType, size); why != "" { + pending = append(pending, fmt.Sprintf("attachment %q (%d bytes, %s) dropped: %s", a.Name, size, a.MimeType, why)) + continue + } + total += size + c.Attachments = append(c.Attachments, a) + } + for _, w := range pending { + if !seen[w] { + seen[w] = true + warnings = append(warnings, w) + } + } + } + return warnings +} + +// decodedSize is the byte length of valid, padded standard base64. +func decodedSize(b64 string) int { + return len(b64)/4*3 - (len(b64) - len(strings.TrimRight(b64, "="))) +} + +func appendLabel(labels []domain.Label, l domain.Label) []domain.Label { + for _, have := range labels { + if have.Name == l.Name && have.Value == l.Value { + return labels + } + } + return append(labels, l) +} + +func appendLink(links []domain.Link, l domain.Link) []domain.Link { + for _, have := range links { + if have.Type == l.Type && have.URL == l.URL { + return links + } + } + return append(links, l) +} + +func appendTag(tags []string, t string) []string { + for _, have := range tags { + if have == t { + return tags + } + } + return append(tags, t) +} + +// capRunes bounds s to maxRunes runes without splitting one. +func capRunes(s string, maxRunes int) string { + if len(s) <= maxRunes { + return s + } + n := 0 + for i := range s { + if n == maxRunes { + return s[:i] + } + n++ + } + return s +} + +func plural(n int, one, many string) string { + if n == 1 { + return one + } + return many +} diff --git a/internal/adapters/parsers/unit/flutter/markers_test.go b/internal/adapters/parsers/unit/flutter/markers_test.go new file mode 100644 index 0000000..12c4161 --- /dev/null +++ b/internal/adapters/parsers/unit/flutter/markers_test.go @@ -0,0 +1,456 @@ +package flutter + +import ( + "bytes" + "encoding/base64" + "encoding/json" + "os" + "path/filepath" + "reflect" + "strings" + "testing" + "time" + + "qualflare-cli/internal/core/domain" +) + +var pngMagic = []byte("\x89PNG\r\n\x1a\n") + +// marker renders one `##qualflare[v1]` line the way the package does. +func marker(t *testing.T, fields map[string]any) string { + t.Helper() + raw, err := json.Marshal(fields) + if err != nil { + t.Fatal(err) + } + return markerPrefix + string(raw) +} + +func printEv(msg string) map[string]any { + return map[string]any{"type": "print", "testID": 1, "messageType": "print", "message": msg} +} + +func attNames(c domain.Case) []string { + names := make([]string, 0, len(c.Attachments)) + for _, a := range c.Attachments { + names = append(names, a.Name) + } + return names +} + +func findAtt(t *testing.T, c domain.Case, name string) domain.Attachment { + t.Helper() + for _, a := range c.Attachments { + if a.Name == name { + return a + } + } + t.Fatalf("case %q has no attachment %q; have %q", c.Name, name, attNames(c)) + return domain.Attachment{} +} + +func decodeAtt(t *testing.T, a domain.Attachment) []byte { + t.Helper() + b, err := base64.StdEncoding.DecodeString(a.Content) + if err != nil { + t.Fatalf("attachment %q is not base64: %v", a.Name, err) + } + return b +} + +func assertNoMarkersInOutput(t *testing.T, suite *domain.Suite) { + t.Helper() + for _, c := range suite.Cases { + if strings.Contains(c.Properties[propSystemOut], "##qualflare") { + t.Errorf("%s: marker line in system-out", c.ID) + } + for _, a := range c.Attempts { + for _, l := range a.Stdout { + if strings.Contains(l, "##qualflare") { + t.Errorf("%s attempt %d: marker line in stdout", c.ID, a.Number) + } + } + } + } +} + +// assertPackageCapture checks what the package's example suite records, the +// same on the host and on devices. +func assertPackageCapture(t *testing.T, fixture, dir string, wantNative bool) { + suite := parseFixture(t, fixture) + cases := byID(suite) + assertNoMarkersInOutput(t, suite) + + pays := mustCase(t, cases, dir+"#pays for the cart") + if pays.Status != domain.StatusPassed { + t.Errorf("pays for the cart: status = %s, want passed", pays.Status) + } + if want := []domain.Label{{Name: "feature", Value: "checkout"}}; !reflect.DeepEqual(pays.Labels, want) { + t.Errorf("labels = %+v, want %+v", pays.Labels, want) + } + if want := []domain.Link{{Type: "issue", Name: "QF-42", URL: "https://example.com/issues/42"}}; !reflect.DeepEqual(pays.Links, want) { + t.Errorf("links = %+v, want %+v", pays.Links, want) + } + if want := []string{"smoke", "checkout"}; !reflect.DeepEqual(pays.Tags, want) { + t.Errorf("tags = %q, want %q", pays.Tags, want) + } + if pays.Priority != domain.SeverityHigh { + t.Errorf("priority = %q, want high", pays.Priority) + } + wantSteps := []struct { + name string + parent *int + }{ + {"open the checkout", nil}, + {"see the total", domain.IntPtr(0)}, + {"apply a promo code", nil}, + {"pay", nil}, + } + if len(pays.Steps) != len(wantSteps) { + t.Fatalf("steps = %+v, want %d", pays.Steps, len(wantSteps)) + } + for i, w := range wantSteps { + s := pays.Steps[i] + if s.Name != w.name || s.Status != domain.StatusPassed || s.Error != "" || !reflect.DeepEqual(s.ParentIndex, w.parent) { + t.Errorf("step %d = %+v, want %q parent %v passed", i, s, w.name, w.parent) + } + } + if pays.Steps[0].Duration <= 0 || pays.Steps[0].Duration < pays.Steps[1].Duration { + t.Errorf("step durations = %v / %v", pays.Steps[0].Duration, pays.Steps[1].Duration) + } + if got, want := attNames(pays), []string{"order.json", "confirmed.png"}; !reflect.DeepEqual(got, want) { + t.Errorf("attachments = %q, want %q", got, want) + } + order := findAtt(t, pays, "order.json") + if order.MimeType != "application/json" || string(decodeAtt(t, order)) != `{"total":15,"promo":"SAVE5"}` { + t.Errorf("order.json = %s %q", order.MimeType, decodeAtt(t, order)) + } + if shot := findAtt(t, pays, "confirmed.png"); shot.MimeType != "image/png" || !bytes.HasPrefix(decodeAtt(t, shot), pngMagic) { + t.Errorf("confirmed.png is not a PNG (%s)", shot.MimeType) + } + + fails := mustCase(t, cases, dir+"#shows a receipt (fails on purpose)") + if fails.Status != domain.StatusFailed || !strings.Contains(fails.Error, `"Receipt"`) { + t.Errorf("failing test: status=%s error=%q", fails.Status, fails.Error) + } + if got, want := attNames(fails), []string{"failure.png"}; !reflect.DeepEqual(got, want) { + t.Errorf("failing test attachments = %q, want %q", got, want) + } + if shot := findAtt(t, fails, "failure.png"); shot.MimeType != "image/png" || !bytes.HasPrefix(decodeAtt(t, shot), pngMagic) { + t.Errorf("failure.png is not a PNG (%s)", shot.MimeType) + } + if len(fails.Labels)+len(fails.Links)+len(fails.Tags)+len(fails.Steps) != 0 || fails.Priority != "" { + t.Errorf("failing test picked up metadata: %+v", fails) + } + + if wantNative { + native := mustCase(t, cases, dir+"#captures the native screen") + if got, want := attNames(native), []string{"native.png"}; !reflect.DeepEqual(got, want) { + t.Errorf("native attachments = %q, want %q", got, want) + } + if shot := findAtt(t, native, "native.png"); !bytes.HasPrefix(decodeAtt(t, shot), pngMagic) { + t.Error("native.png is not a PNG") + } + } +} + +func TestPackageCapture_Widget(t *testing.T) { + assertPackageCapture(t, "package-widget.jsonl", "test/checkout_widget_test.dart", false) +} + +func TestPackageCapture_Android(t *testing.T) { + assertPackageCapture(t, "package-android.jsonl", "integration_test/checkout_test.dart", true) +} + +func TestPackageCapture_IOS(t *testing.T) { + assertPackageCapture(t, "package-ios.jsonl", "integration_test/checkout_test.dart", true) +} + +// The capture's retried test fails once (taking failure.png) and then passes. +func TestRetriedTest_AttachmentsFromBothAttempts(t *testing.T) { + for fixture, dir := range map[string]string{ + "package-widget.jsonl": "test/checkout_widget_test.dart", + "package-android.jsonl": "integration_test/checkout_test.dart", + "package-ios.jsonl": "integration_test/checkout_test.dart", + } { + t.Run(fixture, func(t *testing.T) { + c := mustCase(t, byID(parseFixture(t, fixture)), dir+"#recovers on the second attempt") + if c.Status != domain.StatusPassed || len(c.Attempts) != 2 { + t.Fatalf("status=%s attempts=%d", c.Status, len(c.Attempts)) + } + if got, want := attNames(c), []string{"attempt 1: failure.png"}; !reflect.DeepEqual(got, want) { + t.Errorf("attachments = %q, want %q", got, want) + } + if !bytes.HasPrefix(decodeAtt(t, findAtt(t, c, "attempt 1: failure.png")), pngMagic) { + t.Error("attempt 1: failure.png is not a PNG") + } + }) + } + + // Synthetic: both attempts attach, and only the final attempt's steps stay. + att := func(id, name, data string) string { + return marker(t, map[string]any{"k": "att", "id": id, "name": name, "type": "text/plain", "n": 1, "i": 0, "data": base64.StdEncoding.EncodeToString([]byte(data))}) + } + suite := syntheticRun(t, []string{"test/a_test.dart"}, "flaky", nil, + printEv(marker(t, map[string]any{"k": "step+", "id": 1, "name": "first try", "t": 10})), + printEv(att("a1", "log.txt", "one")), + printEv(marker(t, map[string]any{"k": "label", "name": "owner", "value": "ana"})), + map[string]any{"type": "error", "testID": 1, "error": "boom", "stackTrace": "", "isFailure": true}, + printEv("Retry: flaky"), + printEv(marker(t, map[string]any{"k": "step+", "id": 2, "name": "second try", "t": 20})), + printEv(marker(t, map[string]any{"k": "step-", "id": 2, "status": "passed", "t": 25})), + printEv(att("a2", "log.txt", "two")), + printEv(marker(t, map[string]any{"k": "label", "name": "owner", "value": "ana"})), + map[string]any{"type": "testDone", "time": 30, "testID": 1, "result": "success"}, + ) + c := suite.Cases[0] + if got, want := attNames(c), []string{"attempt 1: log.txt", "log.txt"}; !reflect.DeepEqual(got, want) { + t.Errorf("attachments = %q, want %q", got, want) + } + if string(decodeAtt(t, c.Attachments[0])) != "one" || string(decodeAtt(t, c.Attachments[1])) != "two" { + t.Errorf("attachment contents = %+v", c.Attachments) + } + if len(c.Steps) != 1 || c.Steps[0].Name != "second try" || c.Steps[0].Duration != 5*time.Millisecond { + t.Errorf("steps = %+v", c.Steps) + } + if want := []domain.Label{{Name: "owner", Value: "ana"}}; !reflect.DeepEqual(c.Labels, want) { + t.Errorf("labels = %+v", c.Labels) + } + if strings.Contains(c.Properties[propSystemOut], "did not finish") { + t.Errorf("an earlier attempt's open step was reported: %q", c.Properties[propSystemOut]) + } +} + +func TestMarkers_ChunksInterleavedAndOutOfOrder(t *testing.T) { + a := []byte(strings.Repeat("first attachment ", 20)) + b := bytes.Repeat([]byte{0, 1, 2, 250}, 30) + ea, eb := base64.StdEncoding.EncodeToString(a), base64.StdEncoding.EncodeToString(b) + chunk := func(id, name, data string, n, i, size int) string { + end := min((i+1)*size, len(data)) + return marker(t, map[string]any{"k": "att", "id": id, "name": name, "type": "application/octet-stream", "n": n, "i": i, "data": data[i*size : end]}) + } + // Chunk sizes are multiples of 4 characters, as the package's are. + prints := []string{ + chunk("b", "b.bin", eb, 3, 2, 64), + "plain output", + chunk("a", "a.txt", ea, 2, 1, 240), + chunk("b", "b.bin", eb, 3, 0, 64), + chunk("a", "a.txt", ea, 2, 0, 240), + chunk("b", "b.bin", eb, 3, 1, 64), + } + set, rest := extractMarkers(prints) + if !reflect.DeepEqual(rest, []string{"plain output"}) { + t.Errorf("rest = %q", rest) + } + if len(set.warnings) != 0 { + t.Errorf("warnings = %q", set.warnings) + } + if len(set.attachments) != 2 { + t.Fatalf("attachments = %+v", set.attachments) + } + // In order of first appearance. + got := map[string][]byte{} + for _, at := range set.attachments { + raw, err := base64.StdEncoding.DecodeString(at.Content) + if err != nil { + t.Fatal(err) + } + got[at.Name] = raw + } + if set.attachments[0].Name != "b.bin" || !bytes.Equal(got["b.bin"], b) || !bytes.Equal(got["a.txt"], a) { + t.Errorf("reassembled = %q", got) + } +} + +func TestMarkers_IncompleteAttachmentDropped(t *testing.T) { + suite := syntheticRun(t, []string{"test/a_test.dart"}, "partial", nil, + printEv(marker(t, map[string]any{"k": "att", "id": "a1", "name": "big.png", "type": "image/png", "n": 3, "i": 0, "data": "AAAA"})), + printEv(marker(t, map[string]any{"k": "att", "id": "a1", "name": "big.png", "type": "image/png", "n": 3, "i": 2, "data": "AAAA"})), + map[string]any{"type": "testDone", "time": 5, "testID": 1, "result": "success"}, + ) + c := suite.Cases[0] + if len(c.Attachments) != 0 { + t.Errorf("attachments = %+v", c.Attachments) + } + out := c.Properties[propSystemOut] + if !strings.Contains(out, "qualflare: ") || !strings.Contains(out, "big.png") || strings.Contains(out, "##qualflare") { + t.Errorf("system-out = %q", out) + } +} + +func TestMarkers_CapsReapplied(t *testing.T) { + att := func(id string, size int) string { + return marker(t, map[string]any{"k": "att", "id": id, "name": id + ".bin", "type": "application/octet-stream", "n": 1, "i": 0, + "data": base64.StdEncoding.EncodeToString(make([]byte, size))}) + } + // 5 MiB is allowed (inclusive); one byte more is not. Four at the cap fill + // the 20 MiB test budget exactly; a fifth is dropped. + set, _ := extractMarkers([]string{ + att("over", maxAttachmentBytes+1), + att("a", maxAttachmentBytes), att("b", maxAttachmentBytes), att("c", maxAttachmentBytes), att("d", maxAttachmentBytes), + att("e", 1), + }) + names := make([]string, 0, len(set.attachments)) + for _, a := range set.attachments { + names = append(names, a.Name) + } + if want := []string{"a.bin", "b.bin", "c.bin", "d.bin"}; !reflect.DeepEqual(names, want) { + t.Errorf("kept = %q, want %q", names, want) + } + if len(set.warnings) != 2 { + t.Errorf("warnings = %q", set.warnings) + } +} + +func TestMarkers_UnknownVersionWarned(t *testing.T) { + set, rest := extractMarkers([]string{ + `##qualflare[v2] {"k":"label","name":"a","value":"b"}`, + `##qualflare[v2] {"k":"label","name":"c","value":"d"}`, + marker(t, map[string]any{"k": "label", "name": "kept", "value": "yes"}), + }) + if len(rest) != 0 { + t.Errorf("rest = %q", rest) + } + if want := []domain.Label{{Name: "kept", Value: "yes"}}; !reflect.DeepEqual(set.labels, want) { + t.Errorf("labels = %+v", set.labels) + } + if len(set.warnings) != 1 || !strings.Contains(set.warnings[0], "version") { + t.Errorf("warnings = %q, want one about the version", set.warnings) + } +} + +func TestMarkers_MalformedSkipped(t *testing.T) { + set, rest := extractMarkers([]string{ + markerPrefix + `{"k":"label",`, + markerPrefix + `not json`, + markerPrefix + `{"k":"dance"}`, + markerPrefix + `{"k":"dance","x":1}`, + markerPrefix + `{"k":"link","type":"jira","url":"https://x"}`, + markerPrefix + `{"k":"priority","value":"urgent"}`, + marker(t, map[string]any{"k": "tag", "tags": []string{"ok"}}), + marker(t, map[string]any{"k": "warn", "msg": "screenshot \"x\" failed: no binding"}), + }) + if len(rest) != 0 { + t.Errorf("rest = %q", rest) + } + if !reflect.DeepEqual(set.tags, []string{"ok"}) || len(set.links) != 0 || set.priority != "" { + t.Errorf("set = %+v", set) + } + want := map[string]bool{"malformed": false, `"dance"`: false, "jira": false, "urgent": false, `screenshot "x" failed`: false} + for _, w := range set.warnings { + for k := range want { + if strings.Contains(w, k) { + want[k] = true + } + } + } + for k, seen := range want { + if !seen { + t.Errorf("no warning mentioning %s in %q", k, set.warnings) + } + } + if len(set.warnings) != len(want) { + t.Errorf("got %d warnings, want one each kind (%d): %q", len(set.warnings), len(want), set.warnings) + } +} + +func TestMarkers_StepUnfinishedIsError(t *testing.T) { + set, _ := extractMarkers([]string{ + marker(t, map[string]any{"k": "step+", "id": 1, "name": "outer", "t": 100}), + marker(t, map[string]any{"k": "step+", "id": 2, "parent": 1, "name": "inner", "t": 110}), + marker(t, map[string]any{"k": "step-", "id": 2, "status": "failed", "t": 150, "error": "Expected: 1"}), + }) + if len(set.steps) != 2 { + t.Fatalf("steps = %+v", set.steps) + } + outer, inner := set.steps[0], set.steps[1] + if outer.Status != domain.StatusError || outer.Error != "step did not finish" || outer.ParentIndex != nil { + t.Errorf("outer = %+v", outer) + } + if inner.Status != domain.StatusFailed || inner.Error != "Expected: 1" || inner.Duration != 40*time.Millisecond || + inner.ParentIndex == nil || *inner.ParentIndex != 0 { + t.Errorf("inner = %+v", inner) + } +} + +func TestMarkers_AfterTestDoneIgnored(t *testing.T) { + suite := syntheticRun(t, []string{"test/a_test.dart"}, "done", nil, + printEv(marker(t, map[string]any{"k": "tag", "tags": []string{"before"}})), + map[string]any{"type": "testDone", "time": 5, "testID": 1, "result": "success"}, + printEv(marker(t, map[string]any{"k": "tag", "tags": []string{"after"}})), + printEv("late plain output"), + ) + c := suite.Cases[0] + if !reflect.DeepEqual(c.Tags, []string{"before"}) { + t.Errorf("tags = %q", c.Tags) + } + if out := c.Properties[propSystemOut]; out != "late plain output" { + t.Errorf("system-out = %q", out) + } +} + +func TestMarkers_HiddenTestIgnored(t *testing.T) { + suite := syntheticRun(t, []string{"test/a_test.dart"}, "(setUpAll)", nil, + printEv(marker(t, map[string]any{"k": "tag", "tags": []string{"x"}})), + map[string]any{"type": "testDone", "time": 5, "testID": 1, "result": "success", "hidden": true}, + ) + if len(suite.Cases) != 0 { + t.Errorf("cases = %+v", suite.Cases) + } +} + +// goldenSuite renders a suite with its wall-clock timestamp zeroed. +func goldenSuite(t *testing.T, s *domain.Suite) []byte { + t.Helper() + s.Timestamp = time.Time{} + raw, err := json.MarshalIndent(s, "", " ") + if err != nil { + t.Fatal(err) + } + return append(raw, '\n') +} + +// The four Phase 1 captures, which carry no markers, parse exactly as v0.2.0 +// did. The goldens were written by v0.2.0's parser (QF_UPDATE_GOLDEN=1). +func TestMarkers_NoneParsesAsBefore(t *testing.T) { + for _, name := range []string{"widget-machine.jsonl", "widget-file-reporter.jsonl", "device-android.jsonl", "device-ios.jsonl"} { + t.Run(name, func(t *testing.T) { + got := goldenSuite(t, parseFixture(t, name)) + path := filepath.Join("testdata", "v0.2.0", strings.TrimSuffix(name, ".jsonl")+".golden.json") + if os.Getenv("QF_UPDATE_GOLDEN") == "1" { + if err := os.MkdirAll(filepath.Dir(path), 0o755); err != nil { + t.Fatal(err) + } + if err := os.WriteFile(path, got, 0o600); err != nil { + t.Fatal(err) + } + } + want, err := os.ReadFile(path) + if err != nil { + t.Fatal(err) + } + if !bytes.Equal(got, want) { + t.Errorf("%s parses differently from v0.2.0", name) + } + }) + } +} + +// The per-test cap covers every attempt together, as the package counts it. +func TestMarkers_TestCapAcrossAttempts(t *testing.T) { + full := base64.StdEncoding.EncodeToString(make([]byte, maxAttachmentBytes)) + att := func(name string) domain.Attachment { + return domain.Attachment{Name: name, MimeType: "image/png", Content: full} + } + var c domain.Case + warnings := applyMarkers(&c, []markerSet{ + {attachments: []domain.Attachment{att("a.png"), att("b.png"), att("c.png")}}, + {attachments: []domain.Attachment{att("d.png"), att("e.png")}}, + }, &inlineBudget{}) + if got, want := attNames(c), []string{"attempt 1: a.png", "attempt 1: b.png", "attempt 1: c.png", "d.png"}; !reflect.DeepEqual(got, want) { + t.Errorf("attachments = %q, want %q", got, want) + } + if len(warnings) != 1 || !strings.Contains(warnings[0], "e.png") { + t.Errorf("warnings = %q", warnings) + } +} diff --git a/internal/adapters/parsers/unit/flutter/testdata/package-android.jsonl b/internal/adapters/parsers/unit/flutter/testdata/package-android.jsonl new file mode 100644 index 0000000..beb529e --- /dev/null +++ b/internal/adapters/parsers/unit/flutter/testdata/package-android.jsonl @@ -0,0 +1,83 @@ +{"protocolVersion":"0.1.1","runnerVersion":null,"pid":3206,"type":"start","time":0} +{"suite":{"id":0,"platform":"vm","path":"/home/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart"},"type":"suite","time":0} +{"test":{"id":1,"name":"loading /home/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart","suiteID":0,"groupIDs":[],"metadata":{"skip":false,"skipReason":null},"line":null,"column":null,"url":null},"type":"testStart","time":1} +{"count":1,"time":8,"type":"allSuites"} +{"testID":1,"result":"success","skipped":false,"hidden":true,"type":"testDone","time":164452} +{"group":{"id":2,"suiteID":0,"parentID":null,"name":"","metadata":{"skip":false,"skipReason":null},"testCount":4,"line":null,"column":null,"url":null},"type":"group","time":164455} +{"test":{"id":3,"name":"pays for the cart","suiteID":0,"groupIDs":[2],"metadata":{"skip":false,"skipReason":null},"line":174,"column":5,"url":"package:flutter_test/src/widget_tester.dart"},"type":"testStart","time":164455} +{"testID":3,"messageType":"print","message":"##qualflare[v1] {\"k\":\"label\",\"name\":\"feature\",\"value\":\"checkout\"}","type":"print","time":164727} +{"testID":3,"messageType":"print","message":"##qualflare[v1] {\"k\":\"link\",\"type\":\"issue\",\"url\":\"https://example.com/issues/42\",\"name\":\"QF-42\"}","type":"print","time":164728} +{"testID":3,"messageType":"print","message":"##qualflare[v1] {\"k\":\"tag\",\"tags\":[\"smoke\",\"checkout\"]}","type":"print","time":164728} +{"testID":3,"messageType":"print","message":"##qualflare[v1] {\"k\":\"priority\",\"value\":\"high\"}","type":"print","time":164729} +{"testID":3,"messageType":"print","message":"##qualflare[v1] {\"k\":\"step+\",\"id\":1,\"name\":\"open the checkout\",\"t\":1791127774642}","type":"print","time":164730} 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\"}","type":"print","time":167304} 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\"}","type":"print","time":167510} +{"testID":4,"messageType":"print","message":"══╡ EXCEPTION CAUGHT BY FLUTTER TEST FRAMEWORK ╞════════════════════════════════════════════════════","type":"print","time":167659} +{"testID":4,"messageType":"print","message":"The following TestFailure was thrown running a test:","type":"print","time":167659} +{"testID":4,"messageType":"print","message":"Expected: exactly one matching candidate","type":"print","time":167661} +{"testID":4,"messageType":"print","message":" Actual: _TextWidgetFinder:","type":"print","time":167661} +{"testID":4,"messageType":"print","message":" Which: means none were found but one was expected","type":"print","time":167661} +{"testID":4,"messageType":"print","message":"","type":"print","time":167661} +{"testID":4,"messageType":"print","message":"When the exception was thrown, this was the stack:","type":"print","time":167661} +{"testID":4,"messageType":"print","message":"#4 main. (file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart:48:5)","type":"print","time":167661} +{"testID":4,"messageType":"print","message":"","type":"print","time":167664} +{"testID":4,"messageType":"print","message":"#5 runWithFailureScreenshot (package:qualflare_flutter/src/test_widgets.dart:47:5)","type":"print","time":167664} +{"testID":4,"messageType":"print","message":"","type":"print","time":167665} +{"testID":4,"messageType":"print","message":"#6 testWidgets.. (package:flutter_test/src/widget_tester.dart:192:15)","type":"print","time":167665} +{"testID":4,"messageType":"print","message":"","type":"print","time":167665} +{"testID":4,"messageType":"print","message":"#7 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)","type":"print","time":167665} +{"testID":4,"messageType":"print","message":"","type":"print","time":167666} +{"testID":4,"messageType":"print","message":"","type":"print","time":167666} +{"testID":4,"messageType":"print","message":"(elided one frame from package:stack_trace)","type":"print","time":167667} +{"testID":4,"messageType":"print","message":"","type":"print","time":167667} +{"testID":4,"messageType":"print","message":"This was caught by the test expectation on the following line:","type":"print","time":167667} +{"testID":4,"messageType":"print","message":" file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart line 48","type":"print","time":167667} +{"testID":4,"messageType":"print","message":"The test description was:","type":"print","time":167667} +{"testID":4,"messageType":"print","message":" shows a receipt (fails on purpose)","type":"print","time":167667} +{"testID":4,"messageType":"print","message":"════════════════════════════════════════════════════════════════════════════════════════════════════","type":"print","time":167667} +{"testID":4,"error":"Test failed. See exception logs above.\nThe test description was: shows a receipt (fails on purpose)","stackTrace":"","isFailure":false,"type":"error","time":167674} +{"testID":4,"result":"error","skipped":false,"hidden":false,"type":"testDone","time":167677} +{"test":{"id":5,"name":"recovers on the second attempt","suiteID":0,"groupIDs":[2],"metadata":{"skip":false,"skipReason":null},"line":174,"column":5,"url":"package:flutter_test/src/widget_tester.dart"},"type":"testStart","time":167678} +{"testID":5,"messageType":"print","message":"##qualflare[v1] 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\"}","type":"print","time":167807} +{"testID":5,"messageType":"print","message":"══╡ EXCEPTION CAUGHT BY FLUTTER TEST FRAMEWORK ╞════════════════════════════════════════════════════","type":"print","time":167851} +{"testID":5,"messageType":"print","message":"The following TestFailure was thrown running a test:","type":"print","time":167852} +{"testID":5,"messageType":"print","message":"Expected: exactly one matching candidate","type":"print","time":167852} +{"testID":5,"messageType":"print","message":" Actual: _TextWidgetFinder:","type":"print","time":167853} +{"testID":5,"messageType":"print","message":" Which: means none were found but one was expected","type":"print","time":167853} +{"testID":5,"messageType":"print","message":"","type":"print","time":167854} +{"testID":5,"messageType":"print","message":"When the exception was thrown, this was the stack:","type":"print","time":167854} +{"testID":5,"messageType":"print","message":"#4 main. (file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart:56:7)","type":"print","time":167854} +{"testID":5,"messageType":"print","message":"","type":"print","time":167855} +{"testID":5,"messageType":"print","message":"#5 runWithFailureScreenshot (package:qualflare_flutter/src/test_widgets.dart:47:5)","type":"print","time":167855} +{"testID":5,"messageType":"print","message":"","type":"print","time":167855} +{"testID":5,"messageType":"print","message":"#6 testWidgets.. (package:flutter_test/src/widget_tester.dart:192:15)","type":"print","time":167855} +{"testID":5,"messageType":"print","message":"","type":"print","time":167855} +{"testID":5,"messageType":"print","message":"#7 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)","type":"print","time":167855} +{"testID":5,"messageType":"print","message":"","type":"print","time":167856} +{"testID":5,"messageType":"print","message":"","type":"print","time":167856} +{"testID":5,"messageType":"print","message":"(elided one frame from package:stack_trace)","type":"print","time":167899} +{"testID":5,"messageType":"print","message":"","type":"print","time":167899} +{"testID":5,"messageType":"print","message":"This was caught by the test expectation on the following line:","type":"print","time":167899} +{"testID":5,"messageType":"print","message":" file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart line 56","type":"print","time":167900} +{"testID":5,"messageType":"print","message":"The test description was:","type":"print","time":167900} +{"testID":5,"messageType":"print","message":" recovers on the second attempt","type":"print","time":167900} +{"testID":5,"messageType":"print","message":"════════════════════════════════════════════════════════════════════════════════════════════════════","type":"print","time":167901} +{"testID":5,"error":"Test failed. See exception logs above.\nThe test description was: recovers on the second attempt","stackTrace":"","isFailure":false,"type":"error","time":167901} +{"testID":5,"messageType":"print","message":"Retry: recovers on the second attempt","type":"print","time":167901} +{"testID":5,"result":"success","skipped":false,"hidden":false,"type":"testDone","time":167934} +{"test":{"id":6,"name":"captures the native screen","suiteID":0,"groupIDs":[2],"metadata":{"skip":false,"skipReason":null},"line":174,"column":5,"url":"package:flutter_test/src/widget_tester.dart"},"type":"testStart","time":167935} +{"testID":6,"messageType":"print","message":"##qualflare[v1] 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\"}","type":"print","time":296204} +{"testID":3,"messageType":"print","message":"##qualflare[v1] 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\"}","type":"print","time":296208} 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\"}","type":"print","time":296928} +{"testID":4,"messageType":"print","message":"##qualflare[v1] {\"k\":\"att\",\"id\":\"a3\",\"name\":\"failure.png\",\"type\":\"image/png\",\"n\":2,\"i\":1,\"data\":\"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\"}","type":"print","time":296929} +{"testID":4,"messageType":"print","message":"══╡ EXCEPTION CAUGHT BY FLUTTER TEST FRAMEWORK ╞════════════════════════════════════════════════════","type":"print","time":297346} +{"testID":4,"messageType":"print","message":"The following TestFailure was thrown running a test:","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"Expected: exactly one matching candidate","type":"print","time":297372} +{"testID":4,"messageType":"print","message":" Actual: _TextWidgetFinder:","type":"print","time":297372} +{"testID":4,"messageType":"print","message":" Which: means none were found but one was expected","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"When the exception was thrown, this was the stack:","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"#4 main. (file:///Users/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart:48:5)","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"#5 runWithFailureScreenshot (package:qualflare_flutter/src/test_widgets.dart:47:5)","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"#6 testWidgets.. (package:flutter_test/src/widget_tester.dart:192:15)","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"#7 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"","type":"print","time":297372} +{"testID":4,"messageType":"print","message":"(elided one frame from package:stack_trace)","type":"print","time":297378} +{"testID":4,"messageType":"print","message":"","type":"print","time":297379} +{"testID":4,"messageType":"print","message":"This was caught by the test expectation on the following line:","type":"print","time":297379} +{"testID":4,"messageType":"print","message":" file:///Users/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart line 48","type":"print","time":297379} +{"testID":4,"messageType":"print","message":"The test description was:","type":"print","time":297379} +{"testID":4,"messageType":"print","message":" shows a receipt (fails on purpose)","type":"print","time":297379} +{"testID":4,"messageType":"print","message":"════════════════════════════════════════════════════════════════════════════════════════════════════","type":"print","time":297379} +{"testID":4,"error":"Test failed. See exception logs above.\nThe test description was: shows a receipt (fails on purpose)","stackTrace":"","isFailure":false,"type":"error","time":297610} +{"testID":4,"result":"error","skipped":false,"hidden":false,"type":"testDone","time":297613} +{"test":{"id":5,"name":"recovers on the second attempt","suiteID":0,"groupIDs":[2],"metadata":{"skip":false,"skipReason":null},"line":174,"column":5,"url":"package:flutter_test/src/widget_tester.dart"},"type":"testStart","time":297616} +{"testID":5,"messageType":"print","message":"##qualflare[v1] 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\"}","type":"print","time":297855} +{"testID":5,"messageType":"print","message":"##qualflare[v1] {\"k\":\"att\",\"id\":\"a4\",\"name\":\"failure.png\",\"type\":\"image/png\",\"n\":2,\"i\":1,\"data\":\"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\"}","type":"print","time":297860} +{"testID":5,"messageType":"print","message":"══╡ EXCEPTION CAUGHT BY FLUTTER TEST FRAMEWORK ╞════════════════════════════════════════════════════","type":"print","time":297895} +{"testID":5,"messageType":"print","message":"The following TestFailure was thrown running a test:","type":"print","time":297895} +{"testID":5,"messageType":"print","message":"Expected: exactly one matching candidate","type":"print","time":297895} +{"testID":5,"messageType":"print","message":" Actual: _TextWidgetFinder:","type":"print","time":297895} +{"testID":5,"messageType":"print","message":" Which: means none were found but one was expected","type":"print","time":297895} +{"testID":5,"messageType":"print","message":"","type":"print","time":297895} +{"testID":5,"messageType":"print","message":"When the exception was thrown, this was the stack:","type":"print","time":297895} +{"testID":5,"messageType":"print","message":"#4 main. (file:///Users/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart:56:7)","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"#5 runWithFailureScreenshot (package:qualflare_flutter/src/test_widgets.dart:47:5)","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"#6 testWidgets.. (package:flutter_test/src/widget_tester.dart:192:15)","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"#7 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"(elided one frame from package:stack_trace)","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"This was caught by the test expectation on the following line:","type":"print","time":297896} +{"testID":5,"messageType":"print","message":" file:///Users/runner/work/qualflare-flutter/qualflare-flutter/example/integration_test/checkout_test.dart line 56","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"The test description was:","type":"print","time":297896} +{"testID":5,"messageType":"print","message":" recovers on the second attempt","type":"print","time":297896} +{"testID":5,"messageType":"print","message":"════════════════════════════════════════════════════════════════════════════════════════════════════","type":"print","time":297896} +{"testID":5,"error":"Test failed. See exception logs above.\nThe test description was: recovers on the second attempt","stackTrace":"","isFailure":false,"type":"error","time":298072} +{"testID":5,"messageType":"print","message":"Retry: recovers on the second attempt","type":"print","time":298073} +{"testID":5,"result":"success","skipped":false,"hidden":false,"type":"testDone","time":298081} +{"test":{"id":6,"name":"captures the native screen","suiteID":0,"groupIDs":[2],"metadata":{"skip":false,"skipReason":null},"line":174,"column":5,"url":"package:flutter_test/src/widget_tester.dart"},"type":"testStart","time":298089} +{"testID":6,"messageType":"print","message":"##qualflare[v1] 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\"}","type":"print","time":298723} +{"testID":6,"messageType":"print","message":"##qualflare[v1] 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\"}","type":"print","time":298817} +{"testID":6,"messageType":"print","message":"##qualflare[v1] 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+{"testID":5,"messageType":"print","message":"══╡ EXCEPTION CAUGHT BY FLUTTER TEST FRAMEWORK ╞════════════════════════════════════════════════════\nThe following TestFailure was thrown running a test:\nExpected: exactly one matching candidate\n Actual: _TextWidgetFinder:\n Which: means none were found but one was expected\n\nWhen the exception was thrown, this was the stack:\n#4 main. (file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/test/checkout_widget_test.dart:49:5)\n\n#5 runWithFailureScreenshot (package:qualflare_flutter/src/test_widgets.dart:47:5)\n\n#6 testWidgets.. (package:flutter_test/src/widget_tester.dart:192:15)\n\n#7 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)\n\n\n(elided one frame from package:stack_trace)\n\nThis was caught by the test expectation on the following line:\n file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/test/checkout_widget_test.dart line 49\nThe test description was:\n shows a receipt (fails on purpose)\n════════════════════════════════════════════════════════════════════════════════════════════════════","type":"print","time":9277} +{"testID":5,"error":"Test failed. See exception logs above.\nThe test description was: shows a receipt (fails on purpose)","stackTrace":"","isFailure":false,"type":"error","time":9280} +{"testID":5,"result":"error","skipped":false,"hidden":false,"type":"testDone","time":9282} +{"test":{"id":6,"name":"recovers on the second attempt","suiteID":0,"groupIDs":[2],"metadata":{"skip":false,"skipReason":null},"line":174,"column":5,"url":"package:flutter_test/src/widget_tester.dart","root_line":52,"root_column":3,"root_url":"file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/test/checkout_widget_test.dart"},"type":"testStart","time":9282} +{"testID":6,"messageType":"print","message":"##qualflare[v1] 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+{"testID":6,"messageType":"print","message":"══╡ EXCEPTION CAUGHT BY FLUTTER TEST FRAMEWORK ╞════════════════════════════════════════════════════\nThe following TestFailure was thrown running a test:\nExpected: exactly one matching candidate\n Actual: _TextWidgetFinder:\n Which: means none were found but one was expected\n\nWhen the exception was thrown, this was the stack:\n#4 main. (file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/test/checkout_widget_test.dart:57:7)\n\n#5 runWithFailureScreenshot (package:qualflare_flutter/src/test_widgets.dart:47:5)\n\n#6 testWidgets.. (package:flutter_test/src/widget_tester.dart:192:15)\n\n#7 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)\n\n\n(elided one frame from package:stack_trace)\n\nThis was caught by the test expectation on the following line:\n file:///home/runner/work/qualflare-flutter/qualflare-flutter/example/test/checkout_widget_test.dart line 57\nThe test description was:\n recovers on the second attempt\n════════════════════════════════════════════════════════════════════════════════════════════════════","type":"print","time":9618} +{"testID":6,"error":"Test failed. See exception logs above.\nThe test description was: recovers on the second attempt","stackTrace":"","isFailure":false,"type":"error","time":9618} +{"testID":6,"messageType":"print","message":"Retry: recovers on the second attempt","type":"print","time":9618} +{"testID":6,"result":"success","skipped":false,"hidden":false,"type":"testDone","time":9666} +{"test":{"id":7,"name":"(tearDownAll)","suiteID":0,"groupIDs":[2],"metadata":{"skip":false,"skipReason":null},"line":null,"column":null,"url":null},"type":"testStart","time":9666} +{"testID":7,"result":"success","skipped":false,"hidden":true,"type":"testDone","time":9669} +{"success":false,"type":"done","time":9696} diff --git a/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/device-android.golden.json b/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/device-android.golden.json new file mode 100644 index 0000000..3d94300 --- /dev/null +++ b/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/device-android.golden.json @@ -0,0 +1,36 @@ +{ + "name": "Flutter Tests", + "category": "flutter", + "total": 2, + "passed": 1, + "failed": 1, + "skipped": 0, + "duration": 179436000000, + "timestamp": "0001-01-01T00:00:00Z", + "properties": { + "platform": "vm" + }, + "cases": [ + { + "id": "integration_test/app_test.dart#counter app starts at zero", + "name": "counter app starts at zero", + "className": "integration_test/app_test.dart", + "status": "passed", + "duration": 630000000, + "properties": { + "file": "integration_test/app_test.dart" + } + }, + { + "id": "integration_test/app_test.dart#counter app fails on device", + "name": "counter app fails on device", + "className": "integration_test/app_test.dart", + "status": "failed", + "duration": 472000000, + "error": "Expected: exactly one matching candidate\n Actual: _TextWidgetFinder:\u003cFound 0 widgets with text \"1\": []\u003e\n Which: means none were found but one was expected\n\n#4 main.\u003canonymous closure\u003e.\u003canonymous closure\u003e (file:///home/runner/work/qualflare-cli/qualflare-cli/spike_app/integration_test/app_test.dart:16:7)\n\u003casynchronous suspension\u003e\n#5 testWidgets.\u003canonymous closure\u003e.\u003canonymous closure\u003e (package:flutter_test/src/widget_tester.dart:192:15)\n\u003casynchronous suspension\u003e\n#6 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)\n\u003casynchronous suspension\u003e\n\u003casynchronous suspension\u003e\n(elided one frame from package:stack_trace)\n\nThis was caught by the test expectation on the following line:\n file:///home/runner/work/qualflare-cli/qualflare-cli/spike_app/integration_test/app_test.dart line 16\nThe test description was:\n fails on device", + "properties": { + "file": "integration_test/app_test.dart" + } + } + ] +} diff --git a/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/device-ios.golden.json b/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/device-ios.golden.json new file mode 100644 index 0000000..695aaa6 --- /dev/null +++ b/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/device-ios.golden.json @@ -0,0 +1,36 @@ +{ + "name": "Flutter Tests", + "category": "flutter", + "total": 2, + "passed": 1, + "failed": 1, + "skipped": 0, + "duration": 204115000000, + "timestamp": "0001-01-01T00:00:00Z", + "properties": { + "platform": "vm" + }, + "cases": [ + { + "id": "integration_test/app_test.dart#counter app starts at zero", + "name": "counter app starts at zero", + "className": "integration_test/app_test.dart", + "status": "passed", + "duration": 419000000, + "properties": { + "file": "integration_test/app_test.dart" + } + }, + { + "id": "integration_test/app_test.dart#counter app fails on device", + "name": "counter app fails on device", + "className": "integration_test/app_test.dart", + "status": "failed", + "duration": 16614000000, + "error": "Expected: exactly one matching candidate\n Actual: _TextWidgetFinder:\u003cFound 0 widgets with text \"1\": []\u003e\n Which: means none were found but one was expected\n\n#4 main.\u003canonymous closure\u003e.\u003canonymous closure\u003e (file:///Users/runner/work/qualflare-cli/qualflare-cli/spike_app/integration_test/app_test.dart:16:7)\n\u003casynchronous suspension\u003e\n#5 testWidgets.\u003canonymous closure\u003e.\u003canonymous closure\u003e (package:flutter_test/src/widget_tester.dart:192:15)\n\u003casynchronous suspension\u003e\n#6 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)\n\u003casynchronous suspension\u003e\n\u003casynchronous suspension\u003e\n(elided one frame from package:stack_trace)\n\nThis was caught by the test expectation on the following line:\n file:///Users/runner/work/qualflare-cli/qualflare-cli/spike_app/integration_test/app_test.dart line 16\nThe test description was:\n fails on device", + "properties": { + "file": "integration_test/app_test.dart" + } + } + ] +} diff --git a/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/widget-file-reporter.golden.json b/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/widget-file-reporter.golden.json new file mode 100644 index 0000000..1613071 --- /dev/null +++ b/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/widget-file-reporter.golden.json @@ -0,0 +1,128 @@ +{ + "name": "Flutter Tests", + "category": "flutter", + "total": 8, + "passed": 3, + "failed": 1, + "skipped": 1, + "errors": 3, + "duration": 2520000000, + "timestamp": "0001-01-01T00:00:00Z", + "properties": { + "platform": "vm" + }, + "cases": [ + { + "id": "test/setup_all_failure_test.dart#with a broken setUpAll (setUpAll)", + "name": "with a broken setUpAll (setUpAll)", + "className": "test/setup_all_failure_test.dart", + "status": "error", + "duration": 28000000, + "error": "Bad state: setUpAll exploded\n\ntest/setup_all_failure_test.dart 5:20 main.\u003cfn\u003e.\u003cfn\u003e", + "properties": { + "file": "test/setup_all_failure_test.dart", + "line": "5" + } + }, + { + "id": "test/broken_test.dart#loading test/broken_test.dart", + "name": "loading test/broken_test.dart", + "className": "test/broken_test.dart", + "status": "error", + "duration": 241000000, + "error": "Failed to load \"/home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/broken_test.dart\":\nCompilation failed for testPath=/home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/broken_test.dart: test/broken_test.dart:5:19: Error: A value of type 'String' can't be assigned to a variable of type 'int'.\n final int x = 'not an int';\n ^\n.", + "properties": { + "file": "test/broken_test.dart" + } + }, + { + "id": "test/widget_cases_test.dart#login screen shows a title", + "name": "login screen shows a title", + "className": "test/widget_cases_test.dart", + "status": "passed", + "duration": 393000000, + "properties": { + "file": "test/widget_cases_test.dart", + "line": "8" + } + }, + { + "id": "test/widget_cases_test.dart#login screen fails an expectation", + "name": "login screen fails an expectation", + "className": "test/widget_cases_test.dart", + "status": "failed", + "duration": 98000000, + "error": "Expected: exactly one matching candidate\n Actual: _TextWidgetFinder:\u003cFound 0 widgets with text \"Sign out\": []\u003e\n Which: means none were found but one was expected\n\n#4 main.\u003canonymous closure\u003e.\u003canonymous closure\u003e (file:///home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/widget_cases_test.dart:15:7)\n\u003casynchronous suspension\u003e\n#5 testWidgets.\u003canonymous closure\u003e.\u003canonymous closure\u003e (package:flutter_test/src/widget_tester.dart:192:15)\n\u003casynchronous suspension\u003e\n#6 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)\n\u003casynchronous suspension\u003e\n\u003casynchronous suspension\u003e\n(elided one frame from package:stack_trace)\n\nThis was caught by the test expectation on the following line:\n file:///home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/widget_cases_test.dart line 15\nThe test description was:\n fails an expectation", + "properties": { + "file": "test/widget_cases_test.dart", + "line": "13" + } + }, + { + "id": "test/widget_cases_test.dart#login screen throws an error", + "name": "login screen throws an error", + "className": "test/widget_cases_test.dart", + "status": "error", + "duration": 14000000, + "error": "StateError: Bad state: boom\n\n#0 main.\u003canonymous closure\u003e.\u003canonymous closure\u003e (file:///home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/widget_cases_test.dart:19:7)\n#1 testWidgets.\u003canonymous closure\u003e.\u003canonymous closure\u003e (package:flutter_test/src/widget_tester.dart:192:29)\n\u003casynchronous suspension\u003e\n#2 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)\n\u003casynchronous suspension\u003e\n\u003casynchronous suspension\u003e\n(elided one frame from package:stack_trace)\n\nThe test description was:\n throws an error", + "properties": { + "file": "test/widget_cases_test.dart", + "line": "18" + } + }, + { + "id": "test/widget_cases_test.dart#login screen is skipped", + "name": "login screen is skipped", + "className": "test/widget_cases_test.dart", + "status": "skipped", + "duration": 1000000, + "properties": { + "file": "test/widget_cases_test.dart", + "line": "22" + } + }, + { + "id": "test/widget_cases_test.dart#login screen prints output", + "name": "login screen prints output", + "className": "test/widget_cases_test.dart", + "status": "passed", + "duration": 8000000, + "properties": { + "file": "test/widget_cases_test.dart", + "line": "24", + "system-out": "hello from a widget test" + } + }, + { + "id": "test/widget_cases_test.dart#login screen passes on the third attempt", + "name": "login screen passes on the third attempt", + "className": "test/widget_cases_test.dart", + "status": "passed", + "duration": 20000000, + "retryCount": 2, + "isFlaky": true, + "attempts": [ + { + "attempt": 1, + "status": "failed", + "message": "Expected: \u003c3\u003e\n Actual: \u003c1\u003e", + "trace": "package:matcher expect\npackage:flutter_test/src/widget_tester.dart 473:18 expect\ntest/widget_cases_test.dart 31:7 main.\u003cfn\u003e.\u003cfn\u003e" + }, + { + "attempt": 2, + "status": "failed", + "message": "Expected: \u003c3\u003e\n Actual: \u003c2\u003e", + "trace": "package:matcher expect\npackage:flutter_test/src/widget_tester.dart 473:18 expect\ntest/widget_cases_test.dart 31:7 main.\u003cfn\u003e.\u003cfn\u003e" + }, + { + "attempt": 3, + "status": "passed" + } + ], + "properties": { + "file": "test/widget_cases_test.dart", + "line": "29" + } + } + ] +} diff --git a/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/widget-machine.golden.json b/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/widget-machine.golden.json new file mode 100644 index 0000000..376a3f0 --- /dev/null +++ b/internal/adapters/parsers/unit/flutter/testdata/v0.2.0/widget-machine.golden.json @@ -0,0 +1,128 @@ +{ + "name": "Flutter Tests", + "category": "flutter", + "total": 8, + "passed": 3, + "failed": 1, + "skipped": 1, + "errors": 3, + "duration": 7890000000, + "timestamp": "0001-01-01T00:00:00Z", + "properties": { + "platform": "vm" + }, + "cases": [ + { + "id": "test/setup_all_failure_test.dart#with a broken setUpAll (setUpAll)", + "name": "with a broken setUpAll (setUpAll)", + "className": "test/setup_all_failure_test.dart", + "status": "error", + "duration": 29000000, + "error": "Bad state: setUpAll exploded\n\ntest/setup_all_failure_test.dart 5:20 main.\u003cfn\u003e.\u003cfn\u003e", + "properties": { + "file": "test/setup_all_failure_test.dart", + "line": "5" + } + }, + { + "id": "test/broken_test.dart#loading test/broken_test.dart", + "name": "loading test/broken_test.dart", + "className": "test/broken_test.dart", + "status": "error", + "duration": 441000000, + "error": "Failed to load \"/home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/broken_test.dart\":\nCompilation failed for testPath=/home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/broken_test.dart: test/broken_test.dart:5:19: Error: A value of type 'String' can't be assigned to a variable of type 'int'.\n final int x = 'not an int';\n ^\n.", + "properties": { + "file": "test/broken_test.dart" + } + }, + { + "id": "test/widget_cases_test.dart#login screen shows a title", + "name": "login screen shows a title", + "className": "test/widget_cases_test.dart", + "status": "passed", + "duration": 380000000, + "properties": { + "file": "test/widget_cases_test.dart", + "line": "8" + } + }, + { + "id": "test/widget_cases_test.dart#login screen fails an expectation", + "name": "login screen fails an expectation", + "className": "test/widget_cases_test.dart", + "status": "failed", + "duration": 96000000, + "error": "Expected: exactly one matching candidate\n Actual: _TextWidgetFinder:\u003cFound 0 widgets with text \"Sign out\": []\u003e\n Which: means none were found but one was expected\n\n#4 main.\u003canonymous closure\u003e.\u003canonymous closure\u003e (file:///home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/widget_cases_test.dart:15:7)\n\u003casynchronous suspension\u003e\n#5 testWidgets.\u003canonymous closure\u003e.\u003canonymous closure\u003e (package:flutter_test/src/widget_tester.dart:192:15)\n\u003casynchronous suspension\u003e\n#6 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)\n\u003casynchronous suspension\u003e\n\u003casynchronous suspension\u003e\n(elided one frame from package:stack_trace)\n\nThis was caught by the test expectation on the following line:\n file:///home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/widget_cases_test.dart line 15\nThe test description was:\n fails an expectation", + "properties": { + "file": "test/widget_cases_test.dart", + "line": "13" + } + }, + { + "id": "test/widget_cases_test.dart#login screen throws an error", + "name": "login screen throws an error", + "className": "test/widget_cases_test.dart", + "status": "error", + "duration": 15000000, + "error": "StateError: Bad state: boom\n\n#0 main.\u003canonymous closure\u003e.\u003canonymous closure\u003e (file:///home/runner/work/qualflare-cli/qualflare-cli/spike_app/test/widget_cases_test.dart:19:7)\n#1 testWidgets.\u003canonymous closure\u003e.\u003canonymous closure\u003e (package:flutter_test/src/widget_tester.dart:192:29)\n\u003casynchronous suspension\u003e\n#2 TestWidgetsFlutterBinding._runTestBody (package:flutter_test/src/binding.dart:1953:5)\n\u003casynchronous suspension\u003e\n\u003casynchronous suspension\u003e\n(elided one frame from package:stack_trace)\n\nThe test description was:\n throws an error", + "properties": { + "file": "test/widget_cases_test.dart", + "line": "18" + } + }, + { + "id": "test/widget_cases_test.dart#login screen is skipped", + "name": "login screen is skipped", + "className": "test/widget_cases_test.dart", + "status": "skipped", + "duration": 0, + "properties": { + "file": "test/widget_cases_test.dart", + "line": "22" + } + }, + { + "id": "test/widget_cases_test.dart#login screen prints output", + "name": "login screen prints output", + "className": "test/widget_cases_test.dart", + "status": "passed", + "duration": 8000000, + "properties": { + "file": "test/widget_cases_test.dart", + "line": "24", + "system-out": "hello from a widget test" + } + }, + { + "id": "test/widget_cases_test.dart#login screen passes on the third attempt", + "name": "login screen passes on the third attempt", + "className": "test/widget_cases_test.dart", + "status": "passed", + "duration": 18000000, + "retryCount": 2, + "isFlaky": true, + "attempts": [ + { + "attempt": 1, + "status": "failed", + "message": "Expected: \u003c3\u003e\n Actual: \u003c1\u003e", + "trace": "package:matcher expect\npackage:flutter_test/src/widget_tester.dart 473:18 expect\ntest/widget_cases_test.dart 31:7 main.\u003cfn\u003e.\u003cfn\u003e" + }, + { + "attempt": 2, + "status": "failed", + "message": "Expected: \u003c3\u003e\n Actual: \u003c2\u003e", + "trace": "package:matcher expect\npackage:flutter_test/src/widget_tester.dart 473:18 expect\ntest/widget_cases_test.dart 31:7 main.\u003cfn\u003e.\u003cfn\u003e" + }, + { + "attempt": 3, + "status": "passed" + } + ], + "properties": { + "file": "test/widget_cases_test.dart", + "line": "29" + } + } + ] +}